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Is the Loudness Dependence of the Auditory Evoked Potential a Valid Marker of
Serotonin Function?
By
Valérie Guille M.Sc (Université Aix-Marseille I, France)
A thesis submitted for the degree
Doctor of Neuropsychopharmacology
2007
Brain Sciences Institute, Swinburne University of Technology
Australia
Declaration
I
Declaration
I hereby declare that, to the best of my knowledge, this thesis contains no material
previously published or written by another person, except where due reference is made
in the text. None of this work has been submitted for the award of any other degree at
any other university. I also declare that this thesis is less than 110,000 words in length,
exclusion of tables, bibliographies and appendices.
Valérie Guille
Acknowledgments
II
Acknowledgments
I would first like to acknowledge the Brain Sciences Institute and Swinburne University
for giving me the opportunity to do this PhD. I would like to thank the Centre of
Neuropsychology at Swinburne University for allowing me to use their facilities to
collect the EEG data related to the third study of this work and acknowledge Dr Jo
Ciacciori for this matter. I would like to extend sincere thanks and gratitude to my
supervisor Assoc Prof Maarten van den Buuse for encouraging me and providing me
with the help that I needed to finish this thesis. Maarten, without you I would not have
made it and I will be always be grateful to you for your help.
I am extremely grateful to Dr Andrea Gogos and Dr Janette Allison for providing me
with constant encouragement and guidance that I needed to write this work. I would
particularly like to thank Andrea for being an excellent friend, making me feel welcome
here in Australia and letting me share the 5-HT1A study with her. I would also like to
thank Cali Bartholomeusz for her encouragements and tireless support through my PhD
years and for being such a great friend. I am extremely grateful to Prof Michael Gilding
for his help, encouragements and support during the writing stage of this thesis and for
believing in me. I would not have been able to finish without his support.
I also wish to thank everybody at the BSI for their friendship. I particularly would like
to thank Sumie Leung, Barry O’Neill and Joanne O’Crane, for their help with the
Amino Acid depletion study, friendship and support. I also want to thank Dr Susanne
Ilic for conducting the medical examinations. I would like to thank Lundbeck
Pharmaceuticals for providing financial support and providing escitalopram and
citalopram tablets for the SSRI study of this work.
I wish to express my deep gratitude to my parents for always supporting me whatever
my decisions are and for their love.
Last, but not least, I would like to dedicate this work to my grandfather, Marcel Ferré,
my two aunts, Katia Ferré and Tante Odille, and my good friend and PhD mate Alan
Dunne, whom sadly passed away during the 3 years of this thesis.
Publications
III
Publications
The following articles and abstracts have been published or presented in support of this
work.
Publication:
Gogos, A, Nathan, PJ, Guille, V, Croft, RJ, and Van den Buuse, M, 2005. Estrogen prevents 5-HT(1A) receptor-induced disruptions of prepulse inhibition in healthy women. Neuropsychopharmacology. 31, 885-889.
O'Neill, BV, Croft, RJ, Leung, S, Guille, V, Galloway, M, Phan, KL and Nathan, PJ, 2006. Dopamine receptor stimulation does not modulate the loudness dependence of the auditory evoked potential in humans. Psychopharmacology (Berl). 188, 92-99.
Guille,V, Croft, RJ, O’Neill, BV, Illic, S, Luan Phan, K and Nathan, PJ. An Examination of Acute Changes in Serotonergic Neurotransmission Using the Loudness Dependence Measure of Auditory Cortex Evoked Activity: Effects of Citalopram, Escitalopram and Sertraline. Human Psychopharmacology. [in press] (Appendix J).
O’Neill, BV, Guille, V, Croft, RJ, Leung, S, Scholes, KE, Luan Phan, K and Nathan, PJ. Effects of Selective and Combined Serotonin and Dopamine Depletion on the Loudness Dependence of the Auditory Evoked Potential (LDAEP) in Humans. Human Psychopharmacology. [In press]
Conference proceedings:
Guille, V, Croft, RJ, Gonsalvez, CJ, Respondek, C, McIntosh, J, Takeuchi, A, and Nathan, PJ, 2004. The loudness dependence auditory evoked potential and depressive symptoms in a student population. Proceedings of the 13th ASP Conference, Hobart, Australia, Australian Journal of Psychology. V56. 43.
Gogos, A, Guille, V, Croft, RJ, Nathan PJ and Van den Buuse, M, 2004. Interaction of estrogen and 5-HT1A receptor stimulation on prepulse inhibition. Proceedings of the XXIV CINP, Paris, France. The International Journal of Neuropsychopharmacology. 7, S465.
O'Neill, B, Guille, V, Leung, S, Phan, KL, Croft, R and Nathan, PJ, 2006. Modulation of the loudness dependence of the auditory evoked potential (LDAEP) by monoamine depletion: implication for its use as an in vivo electrophysiological marker of central serotonergic function. Proceedings of the XXV CINP, Chicago. US. The International Journal of Neuropsychopharmacology. V9, S199.
Guille, V, Croft, RJ, Gogos, A, Van den Buuse, M and Nathan, PJ, 2005. The effect of Buspirone (5-HT1A partial agonist) on the loudness dependence auditory evoked potential. Proceedings of the 14th ASP Conference, Melbourne, Australia. Australian Journal of Psychology. 57, 25.
Abstract
IV
Abstract
The loudness dependence of the auditory evoked potential (LDAEP) has been suggested
as a reliable measure of central serotonin function in humans. However, while animal
studies suggest that LDAEP is sensitive to changes in central serotonin
neurotransmission, evidence in humans has been indirect and inconsistent.
The main aim of this thesis was to examine the effect of acute serotonin modulation on
LDAEP in healthy humans. We also compared two analysis methods, dipole source
analysis (DSA) and scalp topography analysis (ASF), to assess the outcome of serotonin
function modulation on LDAEP.
The first study examined the effect of acutely enhancing synaptic serotonin availability
with three selective serotonin reuptake inhibitors (SSRIs), citalopram, escitalopram or
sertraline. The results failed to replicate previous research in that we did not show
shallower LDAEP slopes with any of the drugs. In addition, no differences were found
between the effects of SSRIs using ASF- or DSA-derived LDAEP methods.
The second study examined the effect of decreasing central serotonin function using the
acute tryptophan depletion (ATD) paradigm. The results support previous research on
the effect of ATD on LDAEP in that they did not show steeper LDAEP slopes. Similar
to the first study, no differences were found between ASF- and DSA-derived LDAEP
methods.
The aim of the third study was to investigate the relationship between the serotonin-1A
(5-HT1A) receptor and LDAEP using acute administration of the 5-HT1A receptor partial
agonist, buspirone. In line with previous animal research, DSA revealed that acute
activation of 5-HT1A receptors resulted in a steeper LDAEP slope of the tangential
dipole. However, there were no effects observed using ASF. Thus, contrary to the two
previous studies, this experiment found a difference in the outcome between the two
LDAEP analysis methods, DSA and ASF.
Abstract
V
In conclusion, the present work does not support LDAEP as a marker for 5-HT function
in healthy humans, based upon the lack of effect of acute treatment with SSRIs or after
ATD. On the other hand, based upon the observed effect of buspirone, it is suggested
that the LDAEP may not reflect central serotonergic function per se but may be related
to specific receptor function, namely the 5-HT1A receptor.
Table of contents
VI
Tables of contents
Declaration....................................................................................................................... I
Acknowledgments ..........................................................................................................II
Publications................................................................................................................... III
Abstract......................................................................................................................... IV
Tables of contents......................................................................................................... VI
List of figures ................................................................................................................ XI
List of tables............................................................................................................... XIII
Abbreviations .............................................................................................................XIV
Units of measurement ................................................................................................XVI
Preface.......................................................................................................................XVII
General Introduction ......................................................................................................1
Introduction ...................................................................................................................2
1.1. Serotonin ...........................................................................................................5
1.1.1. Serotonin synthesis .......................................................................................5
1.1.2. Neuroanatomy of the 5-HT system...............................................................7
1.1.3. The 5-HT receptors .......................................................................................8
1.1.3.a. The 5-HT1A receptors ............................................................................9
1.1.3.b. Other 5-HT receptors ..........................................................................11
1.2. Electrophysiology ...........................................................................................13
1.2.1. Electroencephalography..............................................................................13
1.2.2. EEG generators ...........................................................................................14
1.2.3. Brain rhythmical activity.............................................................................17
1.2.4. Event-related potential ................................................................................18
Table of contents
VII
1.3. Loudness Dependence of the Auditory Evoked Potential...............................20
1.3.1. Auditory evoked potentials and their components......................................20
1.3.2. LDAEP: the scalp-derived analysis ............................................................22
1.3.3. Serotonergic modulation of LDAEP...........................................................23
1.3.4. Dipole source localisation ...........................................................................24
1.3.5. Is the LDAEP a reliable method? ...............................................................26
1.3.5.a. Inconsistencies in the LDAEP methodology ......................................26
1.3.5.b. Reliability in the LDAEP methodology..............................................33
1.4. Conclusion ......................................................................................................35
Loudness Dependence of the Auditory Evoked Potential and 5-HT Function........36
Introduction .................................................................................................................37
2.1. The LDAEP in animals ...................................................................................38
2.2. The LDAEP in healthy volunteers ..................................................................39
2.2.1. Acute tryptophan depletion .........................................................................39
2.2.2. Manipulation of 5-HT function using pharmaceutical compounds ............40
2.2.3. Conclusion ..................................................................................................41
2.3. The LDAEP in clinical populations ................................................................42
2.3.1. Depression...................................................................................................42
2.3.1.a. SSRIs...................................................................................................42
2.3.1.b. Lithium................................................................................................43
2.3.1.c. Summary on the LDAEP and depression ...........................................46
2.3.2. Schizophrenia..............................................................................................46
2.3.3. Migraine ......................................................................................................47
2.3.4. Drug dependence and neurological disorders .............................................47
2.3.4.a. Ecstasy users .......................................................................................48
2.3.4.b. Alcoholism ..........................................................................................49
2.3.4.c. Conclusion on the LDAEP and drug dependence...............................50
2.3.5. Conclusion on the LDAEP in clinical studies.............................................50
2.4. Genetic influence ............................................................................................51
Table of contents
VIII
2.5. Conclusion ......................................................................................................52
2.6. Aims ................................................................................................................53
Experiment 1: The Effect of Three Selective Serotonin reuptake Inhibitors on the
LDAEP ...........................................................................................................................54
Introduction .................................................................................................................55
3.1. Methods...........................................................................................................59
3.1.1. Participants..................................................................................................59
3.1.2. Study design................................................................................................59
3.1.3. Experimental procedure ..............................................................................60
3.1.4. Data acquisition...........................................................................................62
3.1.5. Stimuli .........................................................................................................63
3.1.6. Data analysis ...............................................................................................63
3.1.7. Statistical analysis .......................................................................................68
3.2. Results .............................................................................................................71
3.3. Discussion .......................................................................................................78
Experiment 2: The Effect of Acute Tryptophan Depletion on the LDAEP.............82
Introduction .................................................................................................................83
4.1. Methods................................................................................................................86
4.1.1. Participants..................................................................................................86
4.1.2. Study design................................................................................................86
4.1.3. Experimental procedure ..............................................................................87
4.1.4. Data acquisition...........................................................................................89
4.1.5. Stimuli .........................................................................................................89
4.1.6. Data analysis ...............................................................................................89
4.1.7. Statistical analysis .......................................................................................90
4.2. Results .............................................................................................................93
4.3. Discussion .......................................................................................................99
Table of contents
IX
Experiment 3: The Effect of the 5-HT1A Receptor Agonist Buspirone on the
LDAEP .........................................................................................................................102
Introduction ...............................................................................................................103
5.1. Methods.........................................................................................................106
5.1.1. Participants................................................................................................106
5.1.2. Study design..............................................................................................106
5.1.3. Experimental procedure ............................................................................108
5.1.4. Data acquisition.........................................................................................109
5.1.5. Stimuli .......................................................................................................110
5.1.6. Data analysis .............................................................................................110
5.1.7. Statistical analysis .....................................................................................111
5.2. Results ...........................................................................................................113
5.3. Discussion .....................................................................................................118
General Discussion-Conclusion..................................................................................123
Introduction ...............................................................................................................124
6.1. Summary of the key findings ........................................................................124
6.2. Discussion .....................................................................................................126
6.2.1. Interpretation of findings in the present thesis..........................................127
6.2.1.a. Methodological issues.......................................................................127
6.2.1.b. Possible individual differences in LDAEP .......................................129
6.2.1.c. 5-HT1A receptor vs central 5-HT function in LDAEP ......................132
6.2.1.d. Towards a neurophysiological model for an explanation of the
differential results found between DSA and ASF slope after serotonin
modulation ........................................................................................................133
6.2.1.e. Summary ...........................................................................................134
6.2.2. Future research..........................................................................................135
6.3. Conclusion ....................................................................................................137
Table of contents
X
References ....................................................................................................................138
Appendix A: Consent Forms......................................................................................165
Appendix B: Treatment randomisation....................................................................172
Appendix C: Participant information sheet .............................................................175
Appendix D: Medical forms .......................................................................................189
Appendix E: Visual Analogue Mood Scale ...............................................................196
Appendix F: Auditory stimulus presentation spreadsheet......................................198
Appendix G: Tryptophan depletion study-Low protein diet ..................................203
Appendix H: Poster presentation, Proceeding of the XXV CINP Congress, Chicago
(2006). ...........................................................................................................................206
Appendix I: Poster presentation, Proceeding of the 13th ASP Conference, Hobart,
Australia (2004). ..........................................................................................................208
Appendix J: Examination of Acute Changes in Serotonergic Neurotransmission
Using the Loudness Dependence Measure of Auditory Cortex Evoked Activity:
Effects of Citalopram, Escitalopram and Sertraline………………………………210
Appendix K: Effects of Selective and Combined Serotonin and Dopamine
Depletion on the Loudness Dependence of the Auditory Evoked Potential (LDAEP)
in Humans……………………………………………………………………………222
List of tables
XI
List of figures
Figure 1-1: Serotonin synthesis......................................................................................... 6
Figure 1-2: Serotonin pathways ........................................................................................ 7
Figure 1-3: 5-HT1A receptors structure ............................................................................. 9
Figure 1-4: 10/20 system ................................................................................................. 14
Figure 1-5: EEG rhythmic waves .................................................................................... 17
Figure 1-6: ERPs genesis models.................................................................................... 19
Figure 1-7: Auditory event-related potential................................................................... 21
Figure 1-8: LDAEP slope ................................................................................................ 23
Figure 1-9: LDAEP and 5-HT function ........................................................................... 24
Figure 1-10: AEP dipole localisation.............................................................................. 26
Figure 3-1: Structure of citalopram, escitalopram and sertraline .................................. 57
Figure 3-2: Participant set up for recording session ...................................................... 62
Figure 3-3: Example of results for the basic dipole model performed in CURRY® ....... 67
Figure 3-4: (a) DSA of LDAEP data in the placebo (PLAC) and citalopram (CIT)
condition, shown for the left and right tangential (top panel) and
radial (bottom panels) dipoles. A: Scatter graph of individual data.
B: Box-and-whiskers plot of LDAEP percentiles. (b) DSA of LDAEP
data in the placebo (PLAC) and escitalopram (ESCIT) condition,
shown for the left and right tangential (top panels) and radial dipoles
(bottom panels). A: Scatter graph of individual data. B: Box-and-
whiskers plot of LDAEP percentiles. (c) DSA of LDAEP data in the
placebo (PLAC) and sertraline (SERT) condition, shown for the left
and right tangential (top panels) and radial dipoles (bottom panels).
A: Scatter graph of individual data. B: Box-and-whiskers plot of
LDAEP percentiles, N = 15 .......................................................................... 72
Figure 3-5: Mean N1/P2 amplitude plotted against stimulus intensity for the four
treatments conditions placebo (PLAC), citalopram (CIT), escitalopram
(ESCIT) and sertraline (SERT), N = 15........................................................ 75
Figure 3-6: Grand mean ERPs at Cz of three intensities of auditory stimulus (i.e.
60, 80 and 100 dB), following treatment with citalopram,
escitalopram, sertraline and placebo, N = 15 .............................................. 76
List of tables
XII
Figure 3-7: ASF of LDAEP data in the placebo (PLAC), citalopram (CIT),
escitalopram (ESCIT) and sertraline (SERT) condition. A: Scatter
graph of individual data. B: Box-and-whiskers plot of LDAEP
percentiles ..................................................................................................... 77
Figure 4-1: DSA of LDAEP data in the balance (BAL) and acute tryptophan
depletion (ATD) condition, shown for the left and right tangential (top
panel) and radial (bottom panels) dipoles. A: Scatter graph of
individual data. B: Box-and-whiskers plot of LDAEP percentiles, N =
13................................................................................................................... 94
Figure 4-2: Mean N1/P2 amplitude plotted against stimulus intensity for the
balance (BAL) and acute tryptophan depletion (ATD) conditions,
N = 16 ........................................................................................................... 95
Figure 4-3: Grand mean ERPs at Cz of three intensities of auditory stimulus (i.e.
60, 80 and 100 dB) following the balance (BAL) and acute tryptophan
depletion (ATD) condition, N = 165 ............................................................. 96
Figure 4-4: ASF of LDAEP data in the balance (BAL) and acute tryptophan
depletion (ATD) conditions. A: Scatter graph of individual data. B:
Box-and-whiskers plot of LDAEP percentiles, N = 16 ................................. 97
Figure 5-1: Structurre of buspirone .............................................................................. 105
Figure 5-2: Schematic representation of ovulatory menstrual cycle of the
reproductive hormones and testing period ................................................. 107
Figure 5-3: DSA of LDAEP data in the placebo (PLAC) and buspirone (BUSP)
condition, shown for the left and right tangential (top panel) and
radial (bottom panels) dipoles. A: Scatter graph of individual data.
B: Box-and-whiskers plot of LDAEP percentiles........................................ 114
Figure 5-4: Mean N1/P2 amplitude plotted against stimulus intensity for the
placebo (PLAC) and buspirone (BUSP) conditions, N = 16 ...................... 115
Figure 5-5: Grand mean ERPs at Cz of three intensities of auditory stimulus (i.e.
60, 80 and 100 dB), following treatment with placebo and buspirone,
N = 16 ........................................................................................................ 116
Figure 5-6: ASF of LDAEP data in the placebo (PLAC) and buspirone (BUSP)
conditions. A: Scatter graph of individual data. B: Box-and-whiskers
plot of LDAEP percentiles, N = 16 ............................................................ 117
List of tables
XIII
List of tables
Table 1-1: Summary of methodological variations in the assessment of LDAEP in
healthy participants and in patients with or without treatment .................... 30
Table 2-1: LDAEP in pre-clinical and clinical trials using antidepressant
treatment ....................................................................................................... 45
Table 3-1: Comparison of serotonin receptors inhibition potencies, affinity and
pharmacokinetic parameters for citalopram, escitalopram and
sertraline ....................................................................................................... 57
Table 3-2: Timeline of experimental procedure for the SSRI experiment....................... 61
Table 3-3: Stereotaxic coordinates values for the primary (A1) and secondary
(A2) auditory cortex ...................................................................................... 66
Table 4-1: Timeline of experimental procedure for the ATD experiment ....................... 88
Table 4-2: Results for plasma concentrations of amino acids (µmol/L) for the
baseline and 4.5 hrs following ATD treatment ............................................. 98
Table 5-1: Timeline of experimental procedure for the buspirone experiment ............ 109
Table 6-1: Summary of the present thesis results for the placebo condition ................ 129
Abbreviations
XIV
Abbreviations
5-HIAA 5-hydroxyindoleacetic acid
5-HT 5-hydroxytryptamine (serotonin)
5-HTP 5-hydroxytryptophan
5-HTT Serotonin Transporter
8-OH-DPAT (±)-8-Hydroxy-dipropylami-notetralin
A1 Primary Auditory Cortex
A2 Secondary Auditory Cortex
AEP Auditory Evoked Potential
ANOVA Analysis of Variance
ASF Amplitude/Stimulus Intensity Function
ATD Acute Tryptophan Depletion
BAL Balanced Condition
BEM Bondary Element Model
BESA Brain Electrical Source Analysis
C Controls
CNS Central Nervous System
CSF Cerebrospinal Fluid
DRN Dorsal Raphe Nucleus
DSA Dipole Source Analysis
E2 Oestrogen
EEG Electroencephalogram
EOG Electro-Occulogram
ERP Event-Related Potential
fMRI Functional Magnetic Resonance Imaging
FSH Follicle Stimulating Hormone
GABA Gamma-Aminobutyric Acid
GH Growth Hormone
HAM-D The Hamilton Rating Scale for Depression
HDRS: Hamilton Depression Rating Scale
ICA Independent Component Analysis
Ile Isoleucine
ISI Interstimulus Interval
Abbreviations
XV
LDAEP Loudness Dependence of the Auditory Evoked Potential
Leu Leucine
LH Luteinizing hormone
LNAA Large Neutral Amino Acid
MDMA (±) 3,4 methylenedioxymethamphetamine (ecstasy)
MGFP Mean Global Field Power
MRN Median Raphe Nucleus
PAN Preauricular Points and Nasion
PET Positron Emission Tomography
Phe Phenylalanine
p-r Pseudo-randomised
Prime MD Primary care Evaluation of Mental Disorders
RL Radial Left Dipole
RR Radial Right Dipole
SEM Standard Error of Mean
SNR Signal to Noise Ratio
SOA Stimulus Onset Asynchronisation
SPL Sound Pressure Level
SPSS Statistical Package for Social Science
SSRI Selective Serotonin Reuptake Inhibitors
TL Tangential Left Dipole
TR Tangential Right Dipole
Trp Tryptophan
Tyr Tyrosine
Val Valine
VAMS Visual analogue mood scale
α Alpha
β Betha
δ Delta
θ Theta
Σ Somme
Female
Male
Units of measurement
XVI
Units of measurement
% Percentage
°C Degrees Celsius
µAmm Micro Ampere Per Millimetre
µL Microlitre
µmol Micromole
µV Microvolt
cm Centimetre
dB Decibel
g Gram
hr Hour
Hz Hertz
KDa Kilo Dalton
KΩ Kilo Ohms
L Litre
Log10 Base 10 Logarithm
mg Milligram
min Minute
mL Millilitre
mm Millimetre
ms Millisecond
N Number of participant
nmol Nanomole
rpm Revolutions Per Minutes
kg Kilogram
$ Dollar (Australian)
s Second
Preface
XVII
Preface
The experimental chapters in this thesis were conducted in conjunction with larger
experimental studies, which involved not only the LDAEP paradigm but also a number
of other auditory and visual tasks. These tasks are not presented in this thesis as they
are part of other students’ work. All work presented in this thesis, such as setting up the
protocol to measure the LDAEP and establishing a protocol to analyse the raw data for
the ASF and DSA slope and statistical analysis, was my own work.
Specifically, chapter 4 reports results that are part of a larger research project aimed at
examining the effects of dopamine depletion and serotonin depletion on emotional
processing and cognition. Only the LDAEP paradigm is reported for tryptophan
depletion (i.e. serotonin depletion) and the placebo condition, the other LDAEP data set
(i.e. dopamine) are part of another students’ thesis. Biochemical assays were performed
by Dr Bernie McInerney under the auspices of the Australian Proteome Analysis
Facility established under the Australian Government's Major National Research
Facilities program. The recruiting and testing of participants was done in equal share
with Sumie Leung and Alan Dune, Ph.D. students at the Brain Sciences Institute at the
time of the study.
Similarly, chapter 5 reports results that are part of a collaboration between the
Behavioural Neuroscience Laboratory, Mental Health Research Institute of Victoria,
and the Brain Sciences Institute. The recruiting and testing of participants was done in
equal share with Andrea Gogos, a Ph.D. student at the Mental Health Research Institute
at the time of the study. There were four treatment conditions: placebo/placebo,
oestradiol/placebo, placebo/buspirone and oestradiol/buspirone. Only the
placebo/placebo and placebo/buspirone conditions will be investigated in this thesis as
the two other conditions were part of Andrea Gogos’ Ph.D. thesis.
Chapter 1
1
Chapter 1
General Introduction
Chapter 1
2
Introduction
Advances in the neurosciences have resulted in rapid progress over the last decade in
the understanding of neurochemical function and its relation to behaviour and
neurological disorders. Serotonin is one of the principle neurotransmitters of the brain.
Since its discovery, significant progress has been made in terms of knowledge about the
central serotonin system. Serotonin plays an important role in many aspects of
behaviour such as feeding, risk-taking, aggression and sensory regulation (Jacobs et al.
1990). It is also implicated in the pathophysiology of a number of psychiatric disorders
including mood disorders, anxiety, depression, eating disorders and personality
disorders, with the initial pharmacological treatment for these disorders typically
involving some form of serotonin enhancement (e.g. the selective serotonin reuptake
inhibitors, SSRIs, such as “Prozac”).
Because of the implications of serotonin in the above-mentioned functions and
disorders, understanding serotonin function in the brain is an important field of
research. Valid indicators or markers of serotonin function could be useful in terms of
both diagnosis and treatment. Various techniques exist to measure serotonin function.
Central serotonin concentrations can be estimated by peripheral measures of plasma
platelet serotonin receptor binding and by measuring levels of the serotonin metabolite
5-hydroxyindoleacetic acid (5-HIAA) levels in the cerebrospinal fluid. While these two
measures give us some indication of serotonin function, they are indirect and invasive
(Murphy 1990). Another way to understand serotonin function in the brain is to
increase or decrease central serotoninergic activity using pharmaceutical compounds
that target serotonin receptors, and to evaluate consequent changes in behaviour. Such
methods indirectly assess serotonin function as they measure indirect constructs, such as
behaviour. Therefore, direct non-invasive markers of the serotonergic system are
needed as a means of identifying the function of serotonin in neurological disorders.
Currently, positron emission tomography (PET) of serotonin receptors and transporters
is a promising method that allows direct visualisation of the intracellular response to
modulation of serotonin function (Frankle and Laruelle 2002). However, PET studies
have some limitations, as they cannot provide information about changes in receptor
Chapter 1
3
function (Sargent et al. 2000). Another limitation is that repeated PET testing should be
avoided to minimise excessive radioactive exposure to subjects. PET imaging is also a
very expensive technique, and therefore its use is limited to hospitals. For these
reasons, it is difficult to use PET routinely to investigate serotonin function.
While each of the above-mentioned methods gives some indication of serotonin
function, they are not able to measure accurately central serotonin activity as it occurs in
real time, and researchers have had to rely on indirect methods. Direct and
non-invasive methods of investigation would be more appropriate to help understand
serotonin function. One non-invasive way to investigate serotonin function has been
proposed more than a decade ago by Hegerl and Juckel (1993) and it is called the
loudness dependence of the auditory evoked potential (LDAEP). This is a non-invasive
psychophysiological method, whereby patterns of electrical activity generated in the
brain (i.e. auditory evoked potentials), in response to tones of varying loudness, are
recorded by electroencephalogram (EEG). In this method, increasing tone loudness
causes an increase in the auditory evoked potential. A steep LDAEP slope has been
associated with a decrease in serotonin function, whereas, a shallow LDAEP slope has
been associated with an increase in serotonin function (Hegerl et al. 2001).
A number of studies conducted using animals and humans have provided support for the
relationship between the LDAEP and serotonin function characteristics. For instance, in
cats, a steeper LDAEP slope has been observed following administration of the
5-HT1A receptor agonist, (±)8-hydroxy-dipropylamino-tetralin (8-OH-DPAT) into the
dorsal raphe nucleus, presumably by causing a decrease in serotonin release (Juckel et
al. 1999). In the same study, a shallower LDAEP slope was found after the intra-raphe
administration of a 5-HT1A receptor antagonist, spiperone, which presumably increases
serotonin release (Juckel et al. 1999). In clinical studies, a steeper LDAEP slope has
been found in patients with conditions associated with low serotonin levels, such as
depression (Gallinat et al. 2000), generalised anxiety disorder (Senkowski et al. 2003),
and ecstasy use (Croft et al. 2001; Dauman et al. 2006). This relationship was also
reported in healthy participants following the administration of the SSRI citalopram
(Nathan et al. 2006).
Chapter 1
4
However, while there is evidence in the literature in support of the relationship between
the LDAEP and serotonin function in clinical populations and in animals, there are
some inconsistent findings in healthy populations. For instance, the results of Nathan
and colleagues (2006), who found a shallower LDAEP slope after citalopram treatment,
were not consistent with studies by Hegerl and colleagues (1991) and Uhl and
colleagues (2006), who found no effects on the LDAEP slope after the administration of
a SSRI to humans. Furthermore, genetic studies have found both a shallower (Gallinat
et al. 2003) and steeper (Strobel et al. 2003) LDAEP slope in participants carrying the
l/l genotype for the serotonin transporter gene which is associated with higher serotonin
reuptake. In view of the lack of consistent findings in previous studies regarding the
relationship between serotonin function and the LDAEP, further investigations are
needed to clarify this issue in healthy humans.
The aim of the current thesis was to examine the relationship between serotonin
function and the LDAEP in healthy participants. The present chapter (Chapter 1) of this
thesis will describe the serotonin system and the electrophysiology and methodology
underlying LDAEP. In chapter 2, a review of the literature examining the relationship
between LDAEP and serotonin function will be presented, followed by the specific aims
of the present thesis.
Chapter 1
5
1.1. Serotonin
Serotonin is an indoleamine described chemically as 5-hydroxytryptamine (5-HT) and
was first identified and named ‘serotonin’ by Rapport and colleagues (1948). 5-HT is a
crucial neurotransmitter involved in many physiological processes such as sleep,
appetite, pain, mood and hormone release (Jacobs et al. 1990). Dysfunction of 5-HT
neurotransmission has been implicated in depression (Coppen 1967; Price et al. 1991),
anxiety (Charney et al. 1990; Stein and Stahl 2000) and schizophrenia (Abi-Dargham et
al. 1997). Such a broad involvement has motivated extensive research on central 5-HT
pathways and biochemistry.
1.1.1. Serotonin synthesis
5-HT is mainly localised in the blood stream, gastrointestinal tract and neurons and it is
synthetised from its amino acid precursor, tryptophan. Only 5 % of the tryptophan in
the plasma is free and available to be transported into the brain through the blood-brain
barrier by competition with other large amino acids (i.e. valine, leucine, isoleucine,
phenylalanine and tyrosine). Once in the brain, tryptophan contributes to 5-HT
synthesis, which takes place in the neuron soma, where tryptophan is converted into 5-
hydroxytryptophan (5-HTP) by tryptophan hydroxylase. 5-HTP is then converted into
5-HT by 5-HTP decarboxylase (Figure 1-1B). After being synthesised, 5-HT is stored
in the serotonergic terminal vesicles from where it is released into the synaptic cleft by
calcium dependent depolarisation resulting from an action potential (Figure 1-1A).
After release and effects on postsynaptic receptors, 5-HT can either be broken down
into 5-hydroxyindoleacetic acid (5-HIAA) by monoamine-oxidase in the synapse or
taken up back into the neuron cytoplasm (serotonin reuptake) and stored either in the
terminal vesicles or if there is too much 5-HT in the neuron, broken down into 5-HIAA
(Figure 1-1) (for review see Azmitia and Whitaker-Azmitia 1995; Moulignier 1994).
Chapter 1
6
Figure 1-1: Serotonin synthesis A. Schematic diagram of serotonergic neurotransmission from it precursor (step ) to it breakdown into 5-hydroxyindoleacetic acid (step ). B. Serotonin synthesis from the amino acid precursor tryptophan. Tryptophan is converted into 5-hydroxytryptophan by tryptophan hydroxylase. The enzyme 5-hydroxytryptophan decarboxylase converts 5-hydroxytryptophan into serotonin (modified from Gray 2006).
Chapter 1
7
1.1.2. Neuroanatomy of the 5-HT system
The location of 5-HT neurons was first investigated by Dahlstrom and Fuxe (1962)
using histofluorescence techniques. They found that 5-HT neuron somas are mainly
located in the raphe nuclei in the midbrain (Dahlstrom and Fuxe 1962). In the raphe
region, 5-HT neurons are located in clusters of nine nuclei (Jacobs and Azmitia 1992),
divided into two main groups of nuclei, the rostral raphe nuclei and the caudal raphe
nuclei (Figure 1-2).
Figure 1-2: Serotonergic pathways The major serotonergic pathways from the raphe nuclei in the human brain. A: Lateral view of the brain illustrating the two main groups of 5-HT nuclei, rostal raphe nuclei and caudal raphe nuclei and their projections in the central nervous system. B: Coronal view of the brain illustrating some of the major targets of the serotonergic raphe nuclei neurons (figure reproduced from Kandel 1991).
These two raphe nuclei constitute the major projection centres for the 5-HT fibre
pathways in the brain. The 5-HT fibre pathways originating from the rostal raphe nuclei
innervate the striatum, frontal cortex, amygdala and hippocampus (Azmitia and
Whitaker-Azmitia 1995; Jacobs and Azmitia 1992; Figure 1-2). Such intensive
innervation of the cerebral cortex by 5-HT fibres suggests an important involvement of
Chapter 1
8
the 5-HT system in the modulation of cognitive functions (Graeff 1997). The 5-HT
fibre pathways originating from the caudal raphe nuclei innervate mainly the spinal cord
(Azmitia and Whitaker-Azmitia 1995) and are involved in sensory and motor down
regulation.
Immunohistochemical studies have shown that these two raphe nuclei not only contain
cell bodies and dendrites of 5-HT neurons but also contain a network of 5-HT fibres
(Kapadia et al. 1985; Leger et al. 2001; Li et al. 2001). The raphe nuclei also contain
high levels of 5-HT, which is released from 5-HT neurons within these nuclei, and/or
other raphe nuclei, in a concentration relatively greater than in the other forebrain
regions (Adell et al. 2002). Two nuclei among the rostal raphe nuclei, the dorsal raphe
nucleus (DRN) and the median raphe nucleus (MRN), are particularly important nuclei
in the 5-HT system. They do not only contain 5-HT neurons with 5-HT receptors, but
also dopamine, GABA, noradrenaline, and acetylcholine receptors that are involved in
the regulation of 5-HT neuronal activity (Adell et al. 2002). They also receive afferent
connections from different parts of the brain and body and send efferent connections
throughout most of the brain. This suggests two main factors involved in the regulation
of the 5-HT system: one intrinsically serotonergic and another one that involves other
neurotransmitters and/or their receptors (for review Adell et al. 2002).
In summary, major projections of the 5-HT system from the two main raphe nuclei
target the vast majority of the central nervous system (CNS) (Figure 1-2). Among the
raphe nuclei, the DRN and MRN are particularly important nuclei that contain 5-HT
neurons, 5-HT receptors and afferent connections from different parts of the brain and
body. These raphe nuclei are important relay centres in information processing.
1.1.3. The 5-HT receptors
5-HT acts on the CNS by binding to 5-HT receptors on the cell body or dendrites of
neurons. In 1957, Gaddum and Picarelli were the first to identify two receptors (D and
M) for 5-HT in an isolated guinea pig ileum preparation. With rapid advances in
research, an increasing number of 5-HT receptors have now been discovered.
Currently, fourteen 5-HT receptors are described (Barnes and Sharp 1999). These
Chapter 1
9
receptors have different pharmacological, molecular and functional characteristics,
however they can be classified into seven main families: 5-HT1, 5-HT2, 5-HT3, 5-HT4,
5-HT5, 5-HT6 and 5-HT7 (Barnes and Sharp 1999). Among these receptors, 5-HT1A is a
particularly important receptor as it is involved in the action of antidepressant and anti-
anxiety drugs (Graeff 1997) and is believed to be involved in schizophrenia
(Abi-Dargham et al. 1997). In the following section, the 5-HT1A receptor structure,
localisation and function will be reviewed. The other types of 5-HT receptors will also
be briefly reviewed.
1.1.3.a. The 5-HT1A receptors
The 5-HT1A receptor belongs to the 5-HT1 family that includes a number of other
receptor subtypes, such as 5-HT1B, 5-HT1D, 5-HT1E and 5-HT1F. The 5-HT1A receptor
was the first in the 5-HT1 receptor family to be sequenced and cloned (Fargin et al.
1988). 5-HT1 receptors contain seven transmembrane α-helices (Figure 1-3) and their
activation inhibits the adenylate cyclase system through G proteins, principally causing
neuronal hyperpolarisation by opening of the potassium channels.
Figure 1-3: 5-HT1A receptor structure (from Azmitia 1998)
5-HT1A receptors are widely distributed in the CNS. Quantitative autoradiographic
studies have mapped 5-HT1A receptors in the rat brain using selective 5-HT1A specific
Chapter 1
10
agonist radioligands such as [3H]8-OH-DPAT (Gozlan et al. 1983; Hall et al. 1985).
These studies showed that 5-HT1A receptors are abundant in the hippocampus, lateral
septum, frontal cortex, thalamus, amygdala and DRN (Barnes and Sharp 1999; Palacios
et al. 1990). In the human brain, the highest density of 5-HT1A receptors (as labelled
with [3H]8-OH-DPAT) is found in the raphe nuclei (DRN, MRN, linear raphe nucleus,
obscurus raphe nucleus), hippocampal formation (cornu ammonis 1, subiculum, dentate
gyrus, cornu ammonis 2), and cortical regions (frontal cortex layers I-II, entorhinal
cortex layers I-III) (Jacobs and Azmitia 1992; Palacios et al. 1990; Pazos et al. 1988).
Intermediate 5-HT1A receptor binding levels are found in the amygdala, locus coeruleus,
nucleus of the solitary tract, central gray and temporal, parietal, motor and occipital
cortices, while low levels are found in the basal ganglia (caudate, putamen, globus
pallidus) and thalamus (Hashimoto et al. 1981; Palacios et al. 1990; Pazos et al. 1988).
Distribution of 5-HT1A receptors in the human brain has been confirmed using PET
imaging (Passchier et al. 2000). 5-HT1A receptors have been found to be located on the
cell bodies and dentrites of 5-HT neurons.
5-HT1A receptors are located pre-synaptically on raphe neurons (autoreceptors), but are
also found postsynaptically on target neurons such as pyramidal cells in the cortex.
5-HT1A autoreceptors have been found to control DRN firing rate (Jacobs and Azmitia
1992). Their primary function is to slow down the activity of the serotonergic neurons;
hence 5-HT1A autoreceptors activation causes a reduction of neuronal firing, 5-HT
synthesis, and 5-HT terminal release (Sprouse and Aghajanian 1987).
Therapeutic indications for 5-HT1A receptor agonists include anxiety, depression,
aggression, alcoholism, ischemic stroke and emesis (for review see De Vry 1995).
While 5-HT1A receptors are important in neurological disorders, they are also important
in regulating normal physiological function, including immune function, sleep and
vascular tone (El Mestikawy et al. 1991). In addition to the neurotransmitter role of
5-HT1A receptors, they also mediate the neurotrophic effects of 5-HT
(Azmitia and Whitaker-Azmitia 1995; Barnes and Sharp 1999). Such a role of 5-HT1A
receptors may further implicate these receptors in neurological and psychiatric
disorders, and reinforces the potential of 5-HT1A receptors to be a beneficial target for
drugs development (Adell et al. 2002; Azmitia and Whitaker-Azmitia 1995).
Chapter 1
11
1.1.3.b. Other 5-HT receptors
5-HT and 5-HT receptors are well recognised in mammalian species and abundantly
found within the CNS. All the 5-HT receptor subtypes have distinct patterns of
distribution in the brain. For instance, 5-HT1 receptors have been found in the globus
pallidus, substantia nigra, periaquaductal grey and spinal cord (Castro et al. 1997).
5-HT2A receptors are found in many forebrain areas (Lopez-Gimenez et al. 1997),
amygdala, cingulate cortex and the olfactory tubercle (Barnes and Sharp 1999). 5-HT2C
receptors are found in the hippocampus, globus pallidus and substantia nigra (Graeff
1997). 5-HT3 receptors have been found in high concentrations within the dorsal vagal
complex (Pratt et al. 1990), hippocampus, amygdala and cerebral cortex, with low
concentrations in the forebrain (Graeff 1997). 5-HT4 receptors have been located in the
nigrostriatal and mesolimbic systems (for review see Barnes and Sharp 1999), and in
the gut (along with 5-HT3 and 5-HT7 receptors, Tonini 2005). 5-HT5B receptors have
been found in the hypothalamus, striatum, thalamus, cerebellum, pons and medulla
(Barnes and Sharp 1999). Finally, 5-HT6 receptors have been confirmed in CNS
regions such as the striatum, but they have also been found in the stomach and adrenal
gland (Barnes and Sharp 1999). These receptors are located at the postsynaptic level
where their activation depolarises the neuron (5-HT2A, 5-HT2c, 5-HT3, 5-HT4), whereas
some of them (5-HT1B,D, 5-HT2A,C, 5-HT3, 5-HT4) are also located on non-serotonergic
neuronal terminals where their function is to regulate neurotransmitter release (for
details see Barnes and Sharp 1999).
At the clinical level, these 5-HT receptors play important roles in the modulation of
various behaviours and in neurological and psychiatric disorders. For instance, 5-HT2A
receptors are implicated in a wide range of behavioural disorders such as anorexia,
obsessive compulsive disorder and schizophrenia (Graeff 1997), as well as in
physiological responses such as sleep (Moulignier 1994). The 5-HT2C receptor is also
an important receptor because of its role in feeding and anxiety disorders along with
5-HT3 (Graeff 1997; Moulignier 1994) and 5-HT4 receptors (Barnes and Sharp 1999).
5-HT1D receptors are thought to be involved in migraine, pain, anorexia and aggressive
behaviours (Moulignier 1994) and 5-HT6 receptors have been implicated in
schizophrenia and dementia (for review Mitchell and Neumaier 2005). The implication
of these 5-HT receptors in neurological and psychiatric disorders reinforces the
Chapter 1
12
potential of these receptors as a target for new drug treatments, such as SSRIs in the
treatment of depression, tryptan in migraine, or clorazine in schizophrenia to cite only a
few. In conclusion, 5-HT is an important neurotransmitter that targets a vast range of
5-HT receptors. These receptors are found throughout the CNS at both pre- and
post-synaptic levels.
Because of the widespread role of 5-HT in brain function and particularly affective
disorders, it is important to be able to investigate the function of 5-HT and its receptors
in humans in vivo. However, the indices currently available to do so are limited. One
example is the neuroendocrine serotonergic response, whereby upon stimulation of the
serotonergic system, hormones such as growth hormone, prolactin, adrenocorticotropin
and cortisol are released. The extent of this hormone release into the circulation can be
used to evaluate central serotonergic activity. However only a few studies have used
this method to investigate the function of the 5-HT1A receptors. For instance,
neuroendocrine responses to administration of the 5-HT1A receptor agonist, flesinoxan,
were examined in healthy participants (Pitchot et al. 2002). Flesinoxan treatment
induced a significant and dose-dependent release of adrenocorticotropin, cortisol,
prolactin and growth hormone. The neuroendocrine response technique has also been
used to demonstrate a decreased growth hormone response in patients with major
depression, possibly reflecting impairment of 5-HT1A postsynaptic receptor function
(Carpenter et al. 1998; Cowen and Charig 1987; Deakin et al. 1990). However, it
should be noted that others have found no difference in growth hormone response
between depressive patients and controls (Porter et al. 2003). These discrepant results
have been suggested to be related to different 5-HT1A postsynaptic receptors being
affected differentially in depression (McAllister-Williams and Massey 2003). A major
limitation of the neuroendocrine method is that it is an indirect measure of central
serotonergic activity, as it uses hormone release as an indicator of brain 5-HT
concentrations and 5-HT receptor activation. Once again, this emphasises the need for a
technique that could examine 5-HT receptors non-invasively and directly.
Chapter 1
13
1.2. Electrophysiology
LDAEP, an electrophysiological measure of auditory processing was proposed as a
marker of 5-HT function (Hegerl and Juckel 1993). LDAEP measures 5-HT function in
response to auditory stimuli using EEG recording. The processing of auditory stimuli in
the brain creates changes in the cellular activity in the auditory cortex, which can be
indirectly recorded using EEG. This is a rapid and non-invasive method to investigate
the activity of the living brain and it provides robust measures of neocortical activity.
EEG and its derivatives such as spectral power, event-related potentials (ERPs), and
event-related desynchronisation and synchronisation, are popular tools for investigating
and monitoring disorders related to brain activity dysfunction (Niedermeyer and Lopes
da Silva 1999). In particular, ERPs are a popular derivative of the EEG, and
specifically measure brain activity that is time-locked to a particular stimulus
presentation. ERPs are the basis of the LDAEP method. In order to understand the
basics of the LDAEP, a review of EEG, ERPs and their source generators is presented
in the next few sections.
1.2.1. Electroencephalography
EEG is a technique for studying the electrical fluctuations within the brain.
Specifically, electrodes attached to the scalp record electrical fluctuations of large
ensembles of neurons. According to Changeux (1983), cerebral activity was recorded
for the first time in 1875 by Caton, directly on the exposed surface of the cortex in
living monkeys. Caton not only initiated EEG research, but also was able to detect
brain responses to stimuli and for the first time track brain electrical activity in animals.
The next major advance was that of Berger in 1929, who reported the first human EEG
recording. Berger created a recording system for humans to measure electrical brain
activity using electrodes placed on the surface of the human scalp. Since then, many
developments in EEG recording equipment and methods have resulted in EEG
becoming a popular tool for the exploration of animal and human brain activity. This
popularity is mainly due to aspects such as high temporal resolution (milliseconds
compared to seconds or minutes for other methods) and EEG recordings being less
Chapter 1
14
expensive and complicated compared to other methods such as PET and functional
magnetic resonance imaging (fMRI).
An EEG recording includes electrodes conventionally placed on the scalp using a
standardised electrode placement scheme established in 1949, allowing universal
comparison and the advantage of accommodating different head sizes and shapes. This
scheme is called the 10/20 system (Figure 1-4).
Figure 1-4: 10/20 system A: Lateral view of the head indicating electrode position along the cerebrum’s midline. B: Superior view of the head displaying the electrode positions. The letters indicate the fontal (F), parietal (P), occipital (O), temporal (T), anteroposterior (A) or central area (C) of the head. Even numbers indicate the right side of the head and odd numbers the left side (modified from Malmivuo and Plonsey 1995).
1.2.2. EEG generators
EEG recordings predominantly reflect the summed activity of many cortical neurons in
the area underlying the EEG electrode. During the last three decades, efforts have been
made to define the cortical generators of EEG activity. Studies have been conducted in
patients with localised brain pathology (Stockard et al. 1977) and in patients using
intracranially-recorded brain-stem auditory-evoked potentials (Hashimoto et al. 1981),
Chapter 1
15
as well as in animals with selective brain lesions (Achor and Starr 1980b), or in animals
using intracranial and extracranial recordings (Achor and Starr 1980a). Of the large
amount of information currently available concerning the theories about the sources of
EEG waveforms, this section will describe the cells thought to be responsible for
waveforms recordedg during EEG and how these cells communicate with each other.
Dynamic brain activity, present during information processing, is the result of
interactions between neurons and assemblies of neurons organised in different layers
within the cerebrum. The outer portion of the cerebrum, the cerebral cortex, is
organised into six layers of neurons. Layer I contains few neuronal cell bodies and is
comprised mainly of axons. Layers II to VI contain different proportions of the two
main types of neurons: pyramidal cells and stellate cells. These cells are strongly
interconnected and organised into a functional unit; the cortical column.
Interconnections among adjacent and nearby columns are made by excitatory axons of
pyramidal cells. These columns receive input from the thalamus via thalamocortical
fibers, that terminate in excitatory synapses, primarily in layers III and IV. The activity
between and within columns in the neocortex can be measured using EEG (Nunez and
Srinivasan 2006; Manshanden et al. 2002). At the cellular level, the theory of volume
conduction suggests that EEG generators are produced by ionic currents, generated by
pyramidal cells that flow through the extracellular space.
Cellular communication at the synapse level occurs because of neurotransmitters.
Neurotransmitters can be excitatory or inhibitory, depending on the type of postsynaptic
potential that is generated. For instance, in the auditory cortex, in vitro and in vivo
studies have suggested that 5-HT1A and 5-HT2A receptors are key players that exert
opposite effects on the excitability and firing activity of pyramidal neurons. Projections
from the DRN activate 5-HT1A receptors located on the soma, leading to
hyperpolarisation of pyramidal neurons, and 5-HT2A receptors located on the dendrites
leading to depolarisation (Aghajanian and Marek 1997; Puig et al. 2003;
Amargos-Bosch et al. 2004). The hyperpolarisation or depolarisation generates ionic
current flows. The magnitude of these ionic current flows will depend on the synapse
distribution. For instance, if excitatory and inhibitory synapses are distributed relatively
close together, the ionic current flow will be small. Conversely, if the excitatory and
Chapter 1
16
inhibitory synapses are further apart (e.g. excitatory synapse on pyramidal cell dendrites
and inhibitory synapse in a deeper layer such as cell bodies), the ionic current flow will
be large. In spite of non-homogeneities regarding structure conductivity in the head,
such as the different conductivities of the white matter, grey matter and cerebrospinal
fluid, these ionic currents flow through brain tissue, cerebrospinal fluid, skull and scalp
and change the electrical potentials on the scalp recorded using EEG electrodes. A
group of pyramidal cells within a cortical column under the same activity state is
believed to contribute substantially to EEG as opposed to non-pyramidal cell activity.
This is because pyramidal cells are oriented parallel to one another and their dendrites
are oriented perpendicular to the surface of the cortex encouraging greater individual
synaptic sources.
The generator that triggers hyperpolarisation or depolarisation of the pyramidal cells
within the cortical columns has been found within the thalamus. The thalamus is a relay
station and an important centre for generating sensory input. Animal studies have
revealed that EEG rhythms in response to task and stimulation depend on
thalamocortical networks between the cortex and the thalamus. Simultaneous
recordings from the visual cortex and the associated thalamic nuclei exhibit identical
peak frequency and responses to visual stimulation (Lopes da Silva et al. 1980). This
clearly supports that thalamic structures generate EEG rhythms. The biocircuitry of the
reticular thalamic nuclei acts as a pacemaker, recruiting thalamic nuclei by means of
powerful inhibitory postsynaptic potential. Based on these studies the physiology of
EEG rhythmic waveforms due to brain activity has been summarised into a general
model. The model explains that firing neurons generate intrinsic oscillations, which are
regulated by the pacemaking reticular thalamic circuitry. This thalamic circuitry
incorporates actions of single pyramidal cells into larger ensembles of pyramidal cells
within a cortical column. Synchronisation of pyramidal cell firing results in a
summation of electrical potentials that can be recorded at the scalp. Desynchronisation
appears when pyramidal cell groups are recruited out of the active group of pyramidal
cell, and become implicated into specific information processing.
Chapter 1
17
1.2.3. Brain rhythmical activity
The analysis of electric activity of the brain recorded by EEG is separated into subfields
of investigation derived from EEG recording. The most used recordings include
spontaneous potentials and ERPs, and they are intensively used and are easy to perform
routinely.
The spontaneous potentials have been a popular measure for investigation for both
research and clinical purposes, as they occur in the absence of specific stimuli and they
are described in terms of magnitude and frequency of rhythmic activity. This activity
was first described by Berger and termed “waves”. Berger described four major
rhythmical activity waves that are recorded during EEG in humans: alpha (α), beta (β),
theta (θ) and delta (δ) (Figure 1-5).
Figure 1-5: EEG rhythmic waves Characteristic brain waves, amplitude and frequency ranges for the four major EEG rhythmic activities (McAnalley et al. 2002).
α rhythms are important EEG waves that have been associated with visual processing
and a relaxed state, and they occur between 8-13 Hz (Lesevre et al. 1967). β rhythms
reflect brain activity when individuals are actively engaged in mental activity and these
rhythms occur between 13-30 Hz (Remy 1955). β waves are generally recognised as
Chapter 1
18
being associated with activation or deactivation of the CNS and are predominantly
recorded from frontal and parietal regions (Regan 1989). θ rhythms are characterised
by frequencies of 4-8 Hz. They are seen in sleep, creativity, intuition state and are
associated with memory, emotion and sensation (Banquet and Saillan 1974). δ rhythms
occur at slow frequencies (less than 3 Hz) and are traditionally considered as a sign of
brain abnormality if they occur frequently in the awake state. However, the above
definitions are historical classifications and somewhat limited. EEG rhythmic waves
also contain frequencies outside the above-mentioned EEG rhythm’s bandwidth. For
instance, the upper β range (35-45 Hz) is known as the gamma (γ) range and has been
associated with vigilant state (Jones and Barth 1997) and with auditory stimulation
(Jones and Barth 1997; MacDonald and Barth 1995).
1.2.4. Event-related potential
Other than the spontaneous potentials mentioned above, EEG includes another method
to investigate brain activity. A stimulus such as a sound or light elicits an electrical
response in the brain, which can be recorded using EEG. This scalp-recorded pattern is
called an ERP and it is time-locked to the presentation of the stimulus. ERPs are
embedded in the EEG and their extraction requires advanced post-recording signal
processing. ERPs can be used to investigate cognitive processes such as those involved
in stimulus encoding. For instance, when stimulating a subject using paradigms
comprising different stimulus characteristics, the experimenter can observe when
stimuli detection occurs and when the information processing occurs within the relevant
brain structure. However, ERPs are not visible in a single measurement. They are
small, with amplitudes from less than a microvolt to several microvolts, and are
contaminated by other ongoing activity in the brain. In order to see these ERPs, the
experimenter needs to average many individual samples. The result of this averaging is
a waveform containing a series of peaks (positive or negative), where each component
of this waveform can be studied in connection with the cognitive task. ERPs are a
major advance in the study of neurophysiology as they allow us to observe basic
responses to stimuli, information processing and cognitive capabilities.
Chapter 1
19
As mentioned in section 1.2.2., rhythmic EEG activity is attributed to corticocortical
and corticothalamic circuits. This can be considered as the “classical” view of the
physiological basis of the EEG, reflecting the electro-activity in neurons in terms of
excitatory and inhibitory postsynaptic potentials. The generation of ERPs in the cortex
is complex and therefore cannot be definitively described. Two conflicting theories
have been used to explain ERP generation (Figure 1-6). The classic hypothesis is that
ERPs measured from the scalp are presumed to be a function of the postsynaptic
potentials of millions of pyramidal cells in cortical layers IV and V. In this model, the
evoked potentials are due to an evoked signal (i.e. summation of electrical potentials)
that occurs on the top of the EEG waves rhythms (Figure 1-6). The second hypothesis
claims that ERPs are produced by phase resetting of ongoing oscillation activity. This
phase resetting hypothesis states that normally the EEG is composed of different signals
that are produced out of phase. When a stimulus is processed, it results in this phase
resetting, so that the signal is then in phase. By averaging these phase-coherent rhythms
a detectable ERP is possible (Figure 1-6; Hanslmayr et al. 2007; Jansen et al. 2003;
Makeig et al. 2002).
Figure 1-6: ERPs genesis models
The two main models underlying the genesis of ERPs. A: EEG rhythms are composed of different signals (colour lines) out of phase. ERPs (black line) are generated by an averaged process on the top of the background. B: EEG rhythms have been reset to the same phase at T0 generating the ERPs (From Streltsova et al. 2006).
Chapter 1
20
1.3. Loudness Dependence of the Auditory Evoked Potential
As mentioned in the introduction of the present chapter, LDAEP has been suggested as
a possible non-invasive electrophysiological marker of central 5-HT function (Hegerl
and Juckel 1993). In this method, individuals listen to a series of tones of varying
loudness and the changes in the related ERPs are recorded from the Cz electrode using
EEG. The following sections will describe the auditory ERPs involved in the LDAEP
and the basics of its classic analysis method (scalp-derived analysis method i.e. ASF).
Serotonergic modulation of the LDAEP will also be presented, followed by a
description of a derivative analysis method the dipole source analysis (DSA). A review
of the literature on the reliability and consistency of the LDAEP is also discussed.
1.3.1. Auditory evoked potentials and their components
The processing of auditory stimuli in the brain creates changes in the brain cell activity.
The event-related potential waveform that is generated in response to auditory stimuli is
called the auditory event-related potential or auditory evoked potential (AEP). The
auditory cortex is the major source of AEP components in humans (Celesia and Puletti
1969; Giard et al. 1990; Knight et al. 1988) and in animals (Simpson and Knight 1993a;
Sukov and Barth 2001). Different elements within this AEP waveform have been
conventionally classified with respect to their latencies and time from stimulus onset.
The auditory evoked potential consists of two set of deflections generated by different
components of the auditory system. The brain stem evoked potential are the first set of
deflection that is produced by the inner ear, immediately followed by potentials
produced by the auditory relay nuclei in the pons and midbrain. The second set of
deflections has longer latencies than the brain stem evoked potentials and are generated
in the auditory cortex. The first component of interest in this second set of deflection is
a prominent increase in negative electrical activity that occurs 100 ms after the stimulus.
This is called the N1 peak (Figure 1-7). The N1 peak is the most studied component of
the AEP. It is assumed to reflect selective attention to basic stimulus characteristics and
its latency and amplitude depend on the stimulus modality (Näätänen and Picton 1987).
N1 generators have been localised within Heschel’s gyrus in the temporal plane using
intracerebral recording (Yvert et al. 2005). This N1 peak is directly followed by an
Chapter 1
21
increase in positive electrical activity (P2) at around 200 ms (Figure 1-7). P2 sources
were found in the temporo-parietal region (Knight et al. 1988) but also found in
posterior medial frontal regions (Picton et al. 1999). Recently, the P2 generators have
been reported to have a more central location within the cingular cortex (Bentley et al.
2002).
Figure 1-7: Auditory event-related potential The characteristic waveform of the AEP N1/P2 complex, following an auditory stimulation (tone) at the electrode Cz. Only the most negative peak (N1) and the positive peak (P2) are reported.1
Following an auditory stimulus, N1 and P2 often occur together and form a major
pattern in the AEP. This is called the N1/P2 complex of the AEP (Davis 1939) and is
thought to reflect the early phase of auditory stimulus identification in the auditory
cortex (Deary 2000). The N1/P2 complex increases with stimulus intensity and its
amplitude varies across the scalp, with maximal amplitude over the vertex. In terms of
N1/P2 generator location, early topographic data reports that they are located within the
superior temporal plane in the vicinity of the auditory cortex (Peronnet et al. 1974; Hari
et al. 1980 ; Elberling et al. 1982; Juckel et al. 1997, 1999; Kaga et al. 1980; Simpson
and Knight 1993b; Vaswani et al. 2003).
1 In electrophysiological figures, the negativity is conventionally display upward and the positivity downward.
Chapter 1
22
Many aspects of AEPs make it an ideal tool for the exploration of changes in brain
activity following acoustic stimulation. AEPs have been reported to provide valid
measures and information regarding central auditory pathways (Starr and Don 1988).
AEPs could also be a valuable tool in clinical care as indices of hearing function and
may be of benefit in early diagnosis of hearing impairments. Finally, measuring AEPs
is a non-invasive tool, making it a technically easy way of investigating the auditory
system.
1.3.2. LDAEP: the scalp-derived analysis
In AEPs, the intensity of the stimulus (i.e. loudness of the tone) influences the
amplitude of the N1/P2 complex. For instance, loud tones evoke an increase in the
amplitude of the N1/P2 complex (Figure 1-8A). This increase in the N1/P2 complex
amplitude in response to increasing loudness of the stimulus represents the LDAEP
(Hegerl and Juckel 1993). To measure the extent to which N1/P2 amplitude increases
with increasing loudness, maximum amplitudes of the N1/P2 complex are graphed
against the loudness of the stimulus tone. A single slope is calculated using these points
(Figure 1-8B). This slope represents the LDAEP and it is called the the “slope of the
amplitude/stimulus intensity function” (ASF slope; Hegerl et al. 1987, 1992b; 1993).
The steepness of the ASF slope reflects the degree of loudness dependency: steep slopes
represent a greater increase in the N1/P2 complex amplitude with increasing loudness of
the stimulus. A shallow ASF slope indicates lesser changes in amplitude with
increasing loudness levels (Hegerl and Juckel 1993).
Chapter 1
23
A 60 dB
100 dB
70 dB80 dB90 dB
Time (ms)
0 100 200 300 400
Am
plitu
de (µ
V)
0
-5
-10
5
10
Stimulus onset
0
10
20
30
60 70 80 90 100
Loudness (dB)
N1/
P2 a
mpl
itude
(µV
)
//
BA 60 dB
100 dB
70 dB80 dB90 dB
Time (ms)
0 100 200 300 400
Am
plitu
de (µ
V)
0
-5
-10
5
10
Stimulus onset
0
10
20
30
60 70 80 90 100
Loudness (dB)
N1/
P2 a
mpl
itude
(µV
)
//
B
Figure 1-8: LDAEP slope A: AEP waveform response to auditory stimuli at five intensities at Cz. The amplitude of the N1/P2 complex increases with increasing loudness. B: Maximum amplitudes of the N1/P2 complex for five levels of loudness, with the slope of the amplitude/stimulus intensity (ASF slope).
1.3.3. Serotonergic modulation of LDAEP
According to Hegerl and colleagues (1987, 1989), LDAEP estimates 5-HT function in
the brain by measuring auditory cortex activity. The underlying cellular mechanisms
responsible for these effects are not fully understood. Based on the EEG theory of
volume conduction, it has been postulated that the LDAEP is the consequence of the
global activity of cortical pyramidal cells in response to various stimulus intensities.
This may be related to neuromodulatory systems located subcortically (Connolly and
Gruzelier 1982). There are a number of lines of evidence to support the argument of a
relationship between LDAEP and 5-HT function. First, it has been suggested that the
N1/P2 component of the LDAEP is generated within the auditory cortex (Hegerl and
Juckel 1993; Scherg and Von Cramon 1986), where a high serotonergic innervation and
a high 5-HT synthesis rate have been detected (Azmitia and Gannon 1986; Lewis et al.
1986). Second, layer IV of the auditory cortex is mostly innervated by serotonergic
fibres from the DRN (Lewis et al. 1986; Thompson et al. 1994). Third, 5-HT has been
argued to play a modulatory role in general cortical function (Jacobs and Azmitia 1992).
This suggests that serotonergic projections from the DRN are in a position to modulate
auditory cortical signal processing, including LDAEP (Hegerl and Juckel 1993).
Chapter 1
24
According to Hegerl and colleagues (1993), a high serotonergic neurotransmission
associated with a high firing rate of the 5-HT neurons from the DRN results in a
shallower ASF slope. Conversely, a low serotonergic neurotransmission associated
with a low firing rate of 5-HT neurons from the DRN is thought to result in a steeper
ASF slope (Figure 1-9).
Figure 1-9: LDAEP and 5-HT function
Relationship between N1/P2 amplitude and serotonin function (modified from Hegerl et al. 2001).
1.3.4. Dipole source localisation
ERPs predominantly reflect the summed activity of many cortical neurons in the area
under the EEG electrode. This does not clearly indicate which specific part of the brain
is active. In the LDAEP method, the use of the ASF slope derived from AEPs has been
criticised because it has been argued to reflect overlapping subcomponents generated by
primary (A1), as well as secondary (A2), auditory cortices (Beauducel et al. 2000;
Carrillo-de-la-Peña 1992, 1999). About two decades ago, a derivative method for the
description of the ERPs was proposed called the “dipole source potential” (Scherg and
Von Cramon 1986). This method is based on physical laws describing scalp potentials
and reflects the activity of a particular restricted region of the brain. These dipole
source potentials have been referred to in the literature as either to dipole source
Chapter 1
25
localisation or dipole source analysis (DSA). In the present work, it will be referred to
as the DSA.
DSA has been adapted to the LDAEP by Scherg and Picton (1991). DSA-derived
LDAEP analysis allows the separation of the auditory evoked N1/P2 complex into
subcomponents generated by A1 and A2. Scherg and von Cramon (1986) studied these
two subcomponents of the N1/P2 complex recorded at the vertex (Cz electrode). They
found that these two subcomponents might be modelled by two separate dipoles in each
temporal lobe: a tangential dipole that represents the activity in the superior temporal
plane (mainly in the A1) and a radial dipole that represents the activity in lateral
temporal structure (mainly in the A2) (Figure 1-10). These findings have been
confirmed by magnetoencephalographic studies (Pantev et al. 1990), fMRI studies
(Brechmann et al. 2002; Jancke et al. 1998), lesion studies in humans (Knight et al.
1988), and in animal studies (Juckel et al. 1997, 1999). The dipole source potentials are
determined using the linear approach described by Scherg and Picton (Scherg and
Picton 1991). The LDAEP slope of the dipole (i.e. DSA slope) is calculated using the
same mathematical procedure described for the ASF slope (see 1.3.2).
In summary, DSA does not only allow for a separation of overlapping components of
the ERPs recorded at the scalp, but it also allows for localisation of the cortical
structures responsible for generating the LDAEP (Scherg et al. 1989). This can provide
valuable information about the LDAEP generators. The DSA slope has also been found
to be more reliable than the ASF slope in assessing LDAEP (for detail see 1.3.5.).
Chapter 1
26
Figure 1-10: AEP dipole localisation Dipole localisation from the AEP grand mean of 32 healthy subjects using BESA®. Tangential dipoles (1 and 2) represent the activity of the primary auditory cortex. Radial dipoles (3 and 4) represent the activity of the secondary auditory cortex (adapted from Hegerl and Juckel 2000).
1.3.5. Is the LDAEP a reliable method?
Over the past two decades, LDAEP has been intensively used in clinical studies to
determine its validity as a marker for 5-HT dysfunction in neurological disorders.
However, the reliability of the LDAEP has been criticised due to inconsistent findings
reported in the literature (Beauducel et al. 2000; Carrillo-de-la-Peña 1992, 2001).
Beauducel and colleagues (2000) suggest that theses inconsistencies may be due to
methodological variations in the assessment of the LDAEP. The present section will
review the inconsistencies in the methodology used in LDAEP studies, for both the ASF
slope and DSA slope. The reliability of the LDAEP method will also be reviewed.
1.3.5.a. Inconsistencies in the LDAEP methodology
Early LDAEP studies mainly reported the ASF slope at the Cz electrode of the 10/20
electrode system placement while the DSA slope has been used in more recent studies.
In the present review, 19 LDAEP studies used the ASF slope methodology, 10 studies
used the DSA slope methodology and 3 studies used both analyses. Many
inconsistencies appear in the methodology of these LDAEP studies that may affect the
results reported. Table 1-1 summarises the most important methodological
Chapter 1
27
characteristics of a sample of preclinical and clinical LDAEP studies. The methodology
parameters in these LDAEP studies varied with respect to stimulus intensity levels,
interstimulus interval (ISI), randomised or pseudo-randomised stimuli presentation
order, participation of healthy participants and/or patients, treatment, sex of the
participants, ASF slope and/or DSA slope and the cortical sites analysed.
In terms of stimulus intensity level, most of the studies used five stimulus intensities
(ranging from 60 to 100 dB; Croft et al. 2001; Hegerl and Juckel 1993; Mulert et al.
2002; Pogarell et al. 2004; to cite only a few) but, some used less than five intensity
levels (Afra et al. 2000; Ambrosini et al. 2003; Carrillo-de-la-Peña 1999, 2001; Hegerl
et al. 1989, 1992a; Proietti-Cecchini et al. 1997; Wang et al. 1999a). A range of
intensities has been used across studies, the most common being the 60, 70, 80, 90 and
100 dB range, while others used a range of intensities that were lower (i.e. 40, 50, 60
and 70 dB; Afra et al. 2000; Prioetti-Cecchini et al. 1997). For some of the studies, the
highest stimulus intensity levels were close to the lowest intensity levels used in other
studies. For instance, Ambrosini and colleagues (2003) used 70 and 80 dB as their
highest intensity levels however, Wang and colleagues (1999a) used 70 and 80 dB as
their lowest intensity levels. As mentioned previously, N1 and the N1/P2 complex
depend on the intensities of the stimulus, therefore such disparities in stimulus
intensities across studies makes comparing their results difficult. Furthermore, the use
of high intensity levels has been reported to result in fewer individual differences
(Schwerdtfeger and Baltissen 1999). After investigating the reliability of the LDAEP
methodology, Beauducel and colleagues (2000) concluded that in order to yield
consistency between studies, stimulus intensity should vary between 60 to 95 dB with at
least five different intensity levels.
The ISI has also been suggested to vary in LDAEP studies (Beauducel et al. 2000). In
Table 1-1, ISI can range from 0.5 s (Wang et al. 1999a) to 9 s (Mulert et al. 2005), with
most studies using an ISI range between 1.6-2.2 s (Croft et al. 2001; Hegerl et al. 1996a;
Gallinat et al. 2003; Strobel et al. 2003; to cite only a few). Little has been reported in
the literature regarding the influence of the ISI on the LDAEP. However, early studies
on augmenting/reducing report a relationship between augmenters and sensation
seeking when AEPs with a 2 s ISI and visual evoked potentials with 17 s ISI
Chapter 1
28
(Zuckerman 1990) are used. Further, the N1 AEP component has been found to have
subcomponents that depend upon the ISI (Näätänen and Picton 1987).
Stimulus presentation order has also been argued to be responsible for the discrepancies
in published LDAEP results. Carrillo-de-la-Peña (1999) reported that differences in the
AEP amplitude are dependent on the mode of presentation of the stimuli. She
furthermore reported that a pseudo-randomised sequence of stimuli of different
intensities evoked higher AEP amplitude at Cz when compared to stimuli presented in
blocks. In the present literature review, most of the stimulus presentation orders have
been consistent and presented in pseudo-randomised sequence or randomised sequence.
Therefore, differences in AEP amplitude are not likely due to sequence.
Another difference that appears in studies using the ASF method listed in Table 1-1 is
the difference in the scalp site analysed. Some studies used only the vertex electrode
(Cz; Croft et al. 2001; Debener et al. 2002; Wang et al. 1999a to cite only a few) while
others used Cz, C3 and C4 (Brocke et al. 2000; Hegerl et al. 1989, 1992a; Massey et al.
2004) or Fz, Cz and FCz (Linka et al. 2004). This difference in recording sites further
complicates comparisons between studies, especially since the morphology of the
N1/P2 waveform used in the ASF-derived method has been reported to be different
across recording sites (Lolas et al. 1987; Näätänen and Picton 1987). For instance,
Lolas and colleagues (1987) reported differences in the AEP components in men
between the right hemisphere (C4) and left hemisphere (C3). However, Beauducel and
colleagues (2000) and Brocke and colleagues (2000) did not corroborate these findings
and found no significant difference between C4, C3 and Cz. In a similar study,
Carrillo-de-la-Peña (1999) reported a steeper ASF slope at Cz than for Fz, T3 or T4.
The Cz location has therefore been argued to be the best location with high reliability
because it has the highest peak to peak amplitude in the scalp LDAEP topography
(Beauducel et al. 2000; Buchsbaum et al. 1983; Carrillo-de-la-Peña 1999).
Different AEP components (P1, N1, P2, P1/N1-slope and N1/P2-slope) have been used
in the assessment of the scalp-derived LDAEP recording methodology. However, few
studies have systematically investigated this topic (Beauducel et al. 2000; Brocke et al.
2000; Carrillo-de-la-Peña. 1999; Lolas et al. 1987). Lolas and colleagues (1987)
Chapter 1
29
reported that the P1/N1-slope correlates negatively with extraversion while the ASF
slope correlates positively with extraversion. In their methodological investigation,
Beauducel and colleagues (2000) concluded that the ASF slope is more reliable than the
P1/N1-slope, the P1-based slope or the N1-based slope. Accordingly, no reliability was
found for the P1, the N1 and the P1/N1 amplitude in healthy participants (Brocke et al.
2000). Further, Hegerl and colleagues (1994) reported a high reliability of the N1/P2
amplitude when compared to the N1 and P2 amplitude separately. Hegerl and
colleagues (1994) suggested that the N1/P2 complex could be used to measure the ASF
slope. In contrast, Linka and colleagues (2004) failed to find any relationship between
with P1/N1 and N1/P2 complex however; they did report a relationship between SSRI
treatment outcome and N1.
In most clinical trials, separate analyses by sex are rarely conducted. Those studies that
have investigated possible sex difference show varying findings. Hegerl and colleagues
(1994) reported no significant gender effects on the intensity dependence of the
tangential dipole. However, gender was found to affect both latency and amplitude of
the AEP, where women had shorter latencies and higher amplitudes compared to men
(Camposano and Lolas 1992; Michalewski et al. 1980). Other research has also
reported sex differences, in particular in 5-HT neurotransmission (Anderson et al. 1990;
Goodwin et al. 1994). Nishizawa and colleagues (1997) reported that 5-HT synthesis in
normal women is 52 % lower when compared to men. This indicates that women may
be less able to maintain adequate storage of 5-HT. Based on the above-mentioned
findings, and the assumption that there is a relationship between the LDAEP and the
5-HT system, it is reasonable to consider a possible gender effect on the LDAEP and
therefore further investigation is required.
Chapter 1
30
Study
Treatment/ clinical type Sex (number) Stimulus Intensity
levels dB (SPL) ISI (s) Presentation order
Analysed sites ASF/DSA slope
Healthy participants with treatment
Debener et al. (2002) ATD (18) 59, 71, 79, 88, 92, 96 1.6-2.1 p-r Cz ASF Dierks et al. (1999) ATD (6) (6) 60, 70, 80, 90, 100 1.6-2.1 r 28 sites DSA Hegerl et al. (1992b) Lithium (11) (23) 52, 62, 72, 82 2.1 r Cz, C3, C4 N1, P2, ASF
Juckel et al. (1995) Ethanol 5-HT agonist (16) 60, 70, 80, 90, 100 1.8-2.2 p-r 32 sites DSA
Massey et al. (2004) ATD (14) 54, 64, 74, 84, 94 - r Cz, C3, C4 ASF
Healthy participants without treatment
Beauducel et al. (2000) Healthy (8) (16) 59, 71, 79, 88, 92, 96 1.6-2.1 p-r Cz, C3, C4 ASF, P1/N1 P1, P2, N1
Carrillo-de-la-peña (1999) Healthy (8) (21) 60, 80, 90, 100 1.5±1 p-r Fz, Cz, T3, T4
ASF, P1/N1, Ta/Tb, Tb/P2, T3, T4
Carrillo-de-la-peña (2001) Healthy (5) (16) 60, 80, 90, 100 1.5±1 p-r Fz, Cz, T3, T4 ASF and DSA
Croft et al. (2001) Ecstasy 61 60, 70, 80, 90, 100 1.8-2.2 p-r Cz ASF
Gallinat et al. (2003) Healthy (96) (89) 79, 87.5, 96, 104.5, 113 1.8-2.2 Cz ASF
Hegerl et al. (1989) Healthy (5) (4) 58; 68; 78; 88 2.1 r Cz, C3, C4 ASF
Hegerl et al. (1992a) Healthy (17) (16) 58, 68, 78, 88 2.1 r Cz, C3, C4 ASF
Hegerl et al. (1995a) Healthy (19) (21) 60, 70, 80, 90, 100 1.6-2.1 p-r Cz DSA
Mulert et al. (2005) Healthy (7) (7) 60, 80, 100 9 p-r ASF and DSA
Raine et al. (1981) ? 60, 70, 80, 90, 100 2 r in blocks P1N1, ASF
Strobel et al. (2003) Healthy (25) (35) 59, 71, 79, 88, 92, 96 1.6-2.1 p-r Cz, C3, C4 ASF
Wang et al. (1999a) Healthy (36) (47) 70; 80; 90; 100 0.5 p-r Cz ASF, N1, P2
Table 1-1: Summary of methodological variations in the assessment of LDAEP in healthy participants and in patients with or without treatment
Chapter 1
31
Study
Treatment/ clinical type Sex (number) Stimulus Intensity
levels dB (SPL) ISI (s) Presentation order
Analysed sites AEP components
Patients with treatment
Brocke et al. (2000)
tricyclic antidepressant, SSRI; lithium; neuroleptic; carbamazepine UPD and BAD
C: (8) (16) UPD: (8) (12)BAD: (13) (8)
59, 71, 79, 88, 92, 96 1.6-2.1 p-r Cz, C3, C4 ASF, P1/N1, P1, P2, N1
Gallinat et al. (2000)
paroxetine sertraline citalopram Depressive
Dep : (15) (14) C : (29) 54, 64, 74, 84, 94 1.8-2.2 p-r 32 sites DSA
Hegerl et al. (1998) Paroxetine Depressive Dep: -(11) -(31) 60, 70, 80, 90, 100 1.8-2.2 p-r DSA
Hegerl et al. (1996b) Ethanol 5-HT agonist Alcoholics
Alc: (25) -alc (3) C (14) 60, 70, 80, 90, 100 1.8-2.2 p-r 32 sites DSA
Juckel et al. (2004) Lithium UPD UPD -(11) -(19) 50, 60, 70, 80, 90 1.8-2.2 p-r Cz DSA
Juckel et al. (2003) Clozapine olanzepine schizophrenics
schizo (14) (11) C (14) (11) 50, 60, 70, 80, 90 1.8-2.2 p-r Cz DSA
Linka et al. (2004) Citalopram Depressive Dep: -(5) -(11) 60, 70, 80, 90, 100
randomised between 500 and 900 ms
r Fz, Cz and FCz
ASF; P1/N1; P1; P2; N1
Mulert et al. (2002) Citalopram Depressive (resp and non resp)
resp (4) (6) non resp (1) (4) 60, 70, 80, 90, 100 1.8-2.2 p-r Cz DSA
Proietti-Cecchini et al. (1997) 311C90 Migrainer
mig (7) (9) C (11) (16) 40, 50, 60, 70 - r Cz ASF
Table 1-1: Continued
Chapter 1
32
Study
Treatment/clinical type Sex (number) Stimulus Intensity
levels dB (SPL) ISI (s) Presentation order
Analysed sites AEP components
Patients without treatment
Afra et al. (2000) Migrainer mig (13) (46) C (5) (18) 40; 50; 60; 70 - r
Cz (needle
electrode) ASF
Ambrosini et al. (2003) Migrainer mig (5) (9) C (4) (10) 50; 60; 70; 80 - p-r Cz N1, P2, ASF
Pogarell et al. (2004) Alcoholics (5) (5) 60; 70; 80; 90; 100 1.8-2.3 p-r 32 ASF
Preuss et al. (2000) Alcoholics (46) (8) 60, 70, 80, 90, 100 1.8-2.2 p-r
Wang et al. (1999b) Migrainer mig (24) (28) C (10) (20) 70; 80; 90; 100 - p-r Cz ASF
p-r = pseudo-randomised order presentation for stimuli, r = randomised order presentation for stimuli ASF = N1/P2 peak amplitude slope ; DSA = Dipole source slope = male = female SPL = sound pressure level ISI = Interstimulus interval ATD = acute tryptophan depletion C = Controls, mig = migrainers, dep = depressive, alc = alcoholics, UBD = uni-bipolar disorder
Table 1-1: Continued
Chapter 1
33
The DSA-derived LDAEP analysis methodology reported in the literature is more
consistent when compared to the scalp-derived analysis (ASF slope). This may be due
to the use of BESA®, which was developed by M. Scherg (Scherg and Picton 1991) to
conduct DSA analysis. BESA® is the most widely used software for source analysis
and dipole localisation in LDAEP research. It contains tools and scripts to assist in
extracting ERP data from EEG data, making it a valuable tool to potentially reduce
methodological discrepancies between studies. However, as can be seen in Table 1-1,
DSA-derived LDAEP studies can also differ in the same respect as the scalp-derived
LDAEP studies differ. For instance, while most studies consistently use the five
specific stimulus intensity levels (60, 70, 80, 90 and 100 dB) one study used five
different intensity levels (i.e. 54, 64, 74, 84, 94; Gallinat et al. 2000), and another study
used only three stimulus intensity levels (60, 80 and 100 dB; Mulert et al. 2005). Such
differences can make comparing findings difficult.
In summary, differences in experimental protocol in LDAEP studies have made
comparing results across studies difficult. Few of the above-mentioned reports have
attempted to provide justification for the methodology employed. It has been suggested
that at least five intensity stimuli with values ranging from 60 to 100 dB are required to
yield consistency across studies (Beauducel et al. 2000). High intensity levels have also
been reported to reduce individual differences (Schwerdtfeger and Baltissen 1999).
Furthermore, the N1/P2 component of the AEP appear to lead to better consistency
(Hegerl et al. 1994) when the Cz recording electrode is used (Beauducel et al. 2000,
Carrillo-de-la-Peña 1999).
1.3.5.b. Reliability in the LDAEP methodology
In spite of the differences in methodology used across LDAEP studies, some reliability
of the LDAEP has been reported. For instance, a high reliability has been found when
AEPs are measured from Cz during high intensity stimuli presentation, presented in a
pseudo-random sequence (Carrillo-de-la-Peña 2001). Importantly, differences in
test-retest reliability were found between patients and controls. In patients no reliability
was found for the ASF slope (Brocke et al. 2000), whereas a good reliability of the ASF
slope was found in healthy participants (Brocke et al. 2000; Hegerl et al. 1989). DSA
Chapter 1
34
analysis has been found to enhance the reliability of slope measure in the LDAEP
method (Carrillo-de-la-Peña 2001) represented by a higher amplitude of the slope at the
tangential dipole, when compared to the radial dipole (Carrillo-de-la-Peña 1999; Hegerl
et al. 1994). A comparison of the two methods; ASF and DSA revealed that the DSA
slope has a higher reliability (r = 0.88) when compared to the ASF slope (r = 0.71-0.78;
Hegerl et al. 1994). Beauducel and colleagues (2000) proposed methodological
parameters to improve reliability in the LDAEP methodology. For instance, since the
Cz recording site has been reported to be the best recording location, with the highest
peak to peak amplitude in the scalp-derived LDAEP (Beauducel et al. 2000; Carrillo-de-
la-Peña 1999), it is likely to increase reliability when recording at the Cz site. With
regard to LDAEP test-retest reliability, Hegerl and colleagues (1988) found reliability of
the ASF slope at Cz over a three-week period. Reliability of the tangential DSA slope
was also found over a three-week period (Hegerl et al. 1994). More recently, reliability
has been reported over a one-year period for the ASF slope and for the tangential DSA
slope using Cz and Fz recording sites, over a one-year period (Carrillo-de-la-Peña
2001).
In summary, previous research highlights that methodological discrepancies in the
LDAEP make it difficult to compare findings across studies and has lead to criticism of
the method. In spite of this, the LDAEP has good test-retest reliability when consistent
methodological parameters are used such as consistent recording site, number of
stimulus intensity levels, stimulus intensity decibel level and stimulus presentation
order. The DSA-derived LDAEP has also been suggested to be more reliable and
consistent across studies when compared to the scalp-derived LDAEP analysis method.
Chapter 1
35
1.4. Conclusion
Serotonin is an important neurotransmitter widely present in the CNS. It plays a major
role in many psychiatric disorders such as depression, schizophrenia and anxiety.
Currently, non-invasive markers of serotonin function are not routinely available. The
LDAEP has been proposed as a non-invasive marker for serotonin function. LDAEP is
derived from the EEG method, however, it has been criticised due to inconsistent results
throughout the literature. These criticisms have been argued to be due to discrepancies
in methodology. However, reliability of the LDAEP is reported when methodological
parameters are consistent. Therefore, when consistency in the methodology is used,
LDAEP method remains an important tool to investigate the serotonin system and the
relationship between LDAEP and disorders with a serotonergic basis.
Chapter 2
36
Chapter 2
Loudness Dependence of the Auditory Evoked Potential and
5-HT Function
Chapter 2
37
Introduction
As outlined in the previous chapter, the LDAEP was proposed more than a decade ago
by Hegerl and Juckel (1993) as a non-invasive psychophysiological method for
measuring 5-HT function in the brain. While the relationship between LDAEP and
5-HT function has been identified mainly using clinical studies, some studies have
investigated this relationship in animals and in healthy participants. The present chapter
will present an overview of this LDAEP literature, and review the influence of genetic
variation of 5-HT function on the LDAEP.
Chapter 2
38
2.1. The LDAEP in animals
The most consistent information regarding the relationship between the LDAEP and
5-HT function comes from animal studies. These studies have shown a steeper LDAEP
slope after local administration of the 5-HT1A receptor agonist, 8-OH-DPAT, into the
DRN, which presumably leads to reduced 5-HT function (Juckel et al. 1999). Recently,
a study which involved recording from the vertex electrode in rats, found a shallower
LDAEP slope after intraperitoneal administration of 100 mg/kg of L-tryptophan or
3 mg/kg of the 5-HT receptor agonist, quipazine. The opposite effect (i.e. a steeper
LDAEP slope) was found after administration of 1 mg/kg of the 5-HT receptor
antagonist, spiperone (Manjarrez et al. 2005). These studies reveal that modulation of
5-HT function by 5-HT receptor agonists or antagonists is reflected by the LDAEP
slope. However, these findings are from non-human studies and need to be considered
with caution. The LDAEP should be investigated further using healthy humans in order
to fully establish the relationship between the LDAEP and 5-HT function and whether it
is a valid indicator of 5-HT function in neurological and psychiatric disorders.
Chapter 2
39
2.2. The LDAEP in healthy volunteers
In studies involving healthy participants, the evidence supporting a relationship between
the LDAEP and 5-HT function appears circumstantial. Early studies have found a
correlation between the LDAEP and personality traits such as “sensation seeking” and
have made indirect inferences about 5-HT function associated with these traits (Hegerl
et al. 1989, 1992a, 1995a; Wang et al. 1999a). Few studies have tested the Hegerl and
Juckel (1993) hypothesis by direct experimental manipulation of 5-HT function in
healthy participants. A better understanding of the action of 5-HT in the healthy human
brain can be gained by various methods, such as by reducing central 5-HT stores with
acute depletion of the 5-HT precursor, tryptophan (the “acute tryptophan depletion”:
ATD method) or by manipulating 5-HT levels in the brain with pharmaceutical
compounds targeting the 5-HT system such as SSRIs. These two methods are reviewed
below.
2.2.1. Acute tryptophan depletion
ATD is a non-invasive direct method used to reduce overall 5-HT function and is based
on a dietary intervention that rapidly lowers tryptophan levels in plasma and
consequently acutely depletes 5-HT and its metabolites in the brain (Carpenter et al.
1998; Nishizawa et al. 1997; Williams et al. 1999). Several ATD studies investigating
the relationship between LDAEP and the 5-HT system in healthy participants have
found no effect on the ASF slope (Debener et al. 2002; Dierks et al. 1999; Massey et al.
2004; Norra et al. 2004). On the other hand, ATD induced a shallower intensity
dependence of the auditory-evoked magnetic dipole slope (N1m/P2m slope; Kahkonen
et al. 2002). Several reasons may explain the negative results with the ASF slope.
First, the same depletion mixture was not used across studies. For instance, Massey and
colleagues (2004) used a 100 g amino acid mixture, while other researchers (Debener et
al. 2002; Dierks et al. 1999; Kahkonen et al. 2002) used a 50 g mixture as developed by
Young and colleagues (1989). In addition, in some studies, either a mixed sample of
men and women were tested (Dierks et al. 1999; Kahkonen et al. 2002), whereas in
other studies only women were tested (Debener et al. 2002; Norra et al. 2004) or only
men were tested (Massey et al. 2004). Sex difference in ATD should be investigated
further, as a recent study using healthy participants found a high variability in response
Chapter 2
40
to ATD between men and women (Neumeister 2003). Finally, the extent of tryptophan
depletion in the brain could not be confirmed in these studies, because measurement of
the ratio of plasma free tryptophan concentrations vs the concentration of large neutral
amino acids (Trp/LNAA ratio) was not included. This ratio has been recognised as an
accurate measure of the central effect of tryptophan depletion on monoamine synthesis
because the competition of tryptophan with other animo acids determines its entry into
the brain (Reilly et al. 1997). Therefore, in view of the discrepancies in the
methodology across studies, it is difficult to conclude that no relationship between
LDAEP and the 5-HT system exists.
2.2.2. Manipulation of 5-HT function using pharmaceutical compounds
In recent LDAEP studies in healthy participants, enhancement of 5-HT function was
attempted by treatment with an SSRI, which is believed to enhance synaptic 5-HT
levels by blocking its re-uptake into the neurons. In one study, participants received 20
mg of citalopram orally and this treatment resulted in a shallower ASF slope (Nathan et
al. 2006). Co-administration of citalopram (20 mg) with the 5-HT1A receptor
antagonist, pindolol (10 mg), which clinically has been postulated to enhance the action
of SSRIs, did not result in greater effects on LDAEP (Segrave et al. 2006). In healthy
participants, a shallower ASF slope was also reported after chronic dosing (four weeks)
of sertraline (Simmons et al. 2003). These findings support an inverse relationship
between the LDAEP and 5-HT function. In contrast, other studies reported no
difference in the LDAEP slope after acute intravenous administration of 20 mg of
citalopram (Uhl et al. 2006). Furthermore, studies using administration of the 5-HT1B/1D
receptor agonist, zolmitriptan, to healthy participants reported either a steeper LDAEP
slope (Proietti-Cecchini et al. 1997) or no difference in the LDAEP slope (Roon et al.
1999). No difference in the LDAEP slope has also been reported after acute treatment
with zolmitriptan, naratriptan or both combined (Roon et al. 1999). Such discrepancies
in findings may be due to differences in methodology. For instance, Nathan and
colleagues (2006) used five stimulus intensity levels ranging from 60 to 100 dB,
whereas, Roon and colleagues (1999) used only four stimulus intensity levels ranging
from 40 to 70 dB. Furthermore, Roon and colleagues (1999) tested a mixed sample of
participants with a high proportion of men. Therefore, due to discrepancies between the
Chapter 2
41
above-mentioned studies, the relationship between the LDAEP and 5-HT function in
healthy participants cannot be confirmed and further investigation is needed.
2.2.3. Conclusion
Healthy control studies do not directly confirm the relationship between the LDAEP
and 5-HT function. The inconsistency in findings may be due to differences in
methodology across studies (for details see 1.3.5.) such as stimulus intensity levels,
gender etc. Further studies using healthy participants need to be carried out in order to
investigate the relationship between the LDAEP and the 5-HT function.
Chapter 2
42
2.3. The LDAEP in clinical populations
The LDAEP has been used in psychological disorders such as anxiety, schizophrenia
and depression, in neurological disorders such as migraines, and in drug dependencies
such as alcohol and ecstasy dependence. However, not all studies agree on the nature of
the relationship between the LDAEP and 5-HT function. The following section
discusses some of the main findings from clinical studies.
2.3.1. Depression
Considerable evidence has accrued over the last three decades to support the hypothesis
that alterations in serotonergic function in the central nervous system occur in patients
with depression. This hypothesis is based on the following findings: (1) reduced
5-HIAA cerebrospinal fluid concentrations in drug-free depressed patients, (2) reduced
concentrations of 5-HT and 5-HIAA in postmortem brain tissue of depressed patients,
(3) decreased tryptophan concentrations in plasma in depressed patients and (4)
effective treatment of depression using 5-HT-targeted treatments such as SSRIs
(Montgomery et al. 1993) or lithium (Price et al. 1990).
2.3.1.a. SSRIs
Although there are many serotonergic drugs available to treat major depression, the
overall treatment outcome is usually far from optimal. Regardless of the initial choice
of antidepressant used, approximately 30 % to 50 % of patients with major depression
will not respond sufficiently to treatment (Bauer et al. 2002). It has been suggested that
the response to antidepressant treatment is partly influenced by genetic mechanisms
(Lesch 2001). Two polymorphisms of the 5-HT transporter gene have been described
and proposed as a possible explanation for the differences in antidepressant treatment
response across patients. These polymorphisms include a long (l) and a short (s)
version of the transporter gene. The s/s genotype has been associated with lower 5-HT
reuptake compared to l/l or l/s genotype group and s/s carriers have been associated
with mood disorders when compared to controls (Bellivier et al. 1998; Collier et al.
1996). The l/l genotype group has been associated with higher 5-HT reuptake.
Chapter 2
43
Based on the hypothesis that the LDAEP reflects change in 5-HT function and that low
5-HT function is associated with depression, the LDAEP appears to be a promising tool
in the investigation of depression and effectiveness of antidepressant treatment.
Specifically, a steeper LDAEP slope is expected in depressed patients. A number of
studies have been carried out in an effort to predict response to treatment in depressed
patients using the LDAEP. For example, prior to the commencement of SSRI
treatment, depressed patients who became non-responders to treatment showed a
significantly shallower DSA slope compared to controls. Conversely, patients with a
steep LDAEP slope prior to treatment had a significant reduction in their Hamilton scale
for depression score after SSRI treatment. However, depressed patients who were
responders to SSRIs treatment did not show a significant difference in the DSA slope
compared to controls (Gallinat et al. 2000). Consistent with the Hegerl and Juckel
(1993) hypothesis that a shallow LDAEP slope represents a higher 5-HT function, these
results could be interpreted as showing that depressed patients who were non-
responders to SSRI treatment had higher 5-HT function and showed a significantly
shallower DSA slope when compared to responders who had lower 5-HT function prior
to SSRI treatment. However, the lack of difference in the DSA slope between
responders and controls prior to treatment, would appear in contrast to the Hegerl and
Juckel hypothesis (1993) (Gallinat et al. 2000). Also other studies suggested that a
better clinical response to SSRI treatment could be found in patients who had a steeper
initial LDAEP slope (Lee et al. 2005; Paige et al. 1994). Furthermore, acutely
enhancing 5-HT availability with fluvoxamine resulted in a shallower LDAEP slope in
depressed patients (Lee et al. 2005). Overall, these findings support the hypothesis that
the LDAEP is a good predictor for SSRI treatment outcome in a depressed population
and indirectly supports a relationship between the LDAEP and 5-HT function
(Table 2-1). Notably, this relationship appears more consistent than that directly
investigated in healthy participants (Table 2-1; see section 2.2.2. for more details).
2.3.1.b. Lithium
In the 1940’s lithium was found to have effects on mood. For many years, it has been
the main medication used for manic depressive (bipolar) disorders. Studies indicate that
lithium effects are due to a net enhancing effect on 5-HT function (Price et al. 1990,
Chapter 2
44
Odagaki et al. 1992). Based on this, LDAEP studies have been carried out to assess
whether patients with a steep LDAEP slope (i.e. presumably low 5-HT function) would
respond better to lithium treatment. Several studies have indeed reported such a
relationship using either the ASF-derived LDAEP method (Hegerl et al. 1987, 1992b)
and later the DSA-derived LDAEP method (Hegerl et al. 1996a; Juckel et al. 2003).
However, the effect of lithium was only seen after chronic treatment (Hegerl et al.
1996a; Juckel et al. 2004). Nevertheless, these findings support the hypothesis that the
LDAEP slope is a good predictor for lithium treatment outcome. Based on the
assumption that lithium has a functional 5-HT enhancing effect, these findings
indirectly support a relationship between the LDAEP and 5-HT function. It should be
noted that healthy participants showed no effect of chronic administration of lithium on
the ASF slope which could indicate that this relationship is only valid in a patient
population (Hegerl et al. 1990, see Table 2-1).
Chapter 2
45
Study Participants Treatment (Dose) Acute/Chronic Analysis Method
DSA/ASF Outcome
Gallinat et al. (2000) Depressed patients and healthy controls
Paroxetine, Sertraline and Citalopram (free dose)
Chronic (4 weeks) DSA
Before treatment: shallower LDAEP slope for non-responders than for responders and controls. After treatment, NS between patients
Hegerl et al. (1990) Healthy controls Lithium (660 g) Chronic (10 days) ASF NS
Hegerl et al. (1991) Depressed patients Fluvoxamine (150 mg)
Acute + 1 week light Therapy ASF
Negative correlation between change of LDAEP slope and blood 5-HT concentration
Hegerl et al. (1996a) Patients with affective disorders Lithium (?) Chronic (in last 4
years) DSA (tangential dipole only)
Responders to lithium treatment were characterised by significant steeper LDAEP slope
Hegerl et al. (1998) Depressed patients Paroxetine (means: 23.5-43.2 mg/day)
? DSA Negative correlation between SSS and LDAEP slope for the tangential dipole
Juckel et al. (2004) Patient (uni- and bipolar disorder) Lithium (?) Chronic for at least 3
years DSA LDAEP is related to favourable outcome after lithium treatment
Lee et al. (2005) Depressed patients Fluoxetine (20 mg) Chronic (4 weeks) ASF Decrease in HDRS after treatment in group with high and shallow initial LDAEP slope
Linka et al. (2004) Depressed patients Citalopram (20-40 mg) Chronic (21-28 days) ASF Correlation for N1 at Fz with HDRS
NS at Cz
Nathan et al. (2006) Healthy Citalopram (20 mg) Acute ASF Shallower LDAEP slope
Paige et al. (1994) Depressed patients SSRI (Fluoxetine, Desipramine, Buproprion)
Chronic (4 weeks) DSA/ASF Better response to treatment when patient has a steeper initial LDAEP slope
Segrave et al. (2006) Healthy Citalopram (20 mg) + Pindolol (10 mg) Acute ASF Shallower LDAEP slope with citalopram
NS citalopram + pindolol
Uhl et al. (2006) Healthy Citalopram (20 mg) Acute ASF No change in the ASF slope after
citalopram administration
Table 2-1: LDAEP in pre-clinical and clinical trials using antidepressant treatment
HDRS: Hamilton Depression Rating Scale, DSA: Dipole source analysis, ASF: Amplitude/stimulus intensity function (scalp-derived LDAEP method), SSS: Sensation seeking syndrome, NS: Non-significant differences between groups.
Chapter 2
46
2.3.1.c. Summary on the LDAEP and depression
Clinical depression research supports a possible relationship between the LDAEP and
5-HT function, and the LDAEP can be viewed as a promising predictor of
antidepressant treatment outcome in a patient population. However, based on some
inconsistencies across studies administering antidepressants, the relationship between
the LDAEP and 5-HT system requires further investigation.
2.3.2. Schizophrenia
Schizophrenia is a chronic mental illness with debilitating symptoms. The causes of
schizophrenia are yet to be determined. Some evidence suggests a link between
schizophrenia and an increase in 5-HT function (Abi-Dargham et al. 1997; Meltzer
1989), for example, 5-HT2A receptor antagonists improve schizophrenia symptoms. A
valid marker of 5-HT function may therefore be a useful tool to investigate further this
illness.
The schizophrenic population can be characterised using ERP methodology. For
instance, disruptions of AEPs, such as P50, MMN, P3 and N1/P2, have been found in
schizophrenia (Bougerol et al. 1997). AEP studies using schizophrenia patients
consistently show a shallower N1, P2, N1/P3 and N1/P2 complex amplitude (Adler and
Gattaz 1993; Chen et al. 1998; Hegerl et al. 1988; Schlor et al. 1985; Van Sweden et al.
1997). These consistent AEP results and the fact that schizophrenia has been linked to
5-HT function, support that the LDAEP may be a promising tool in schizophrenia
research. Only one study examined the LDAEP in schizophrenia patients and showed a
significantly shallower LDAEP slope when compared to controls (Juckel et al. 2003).
While this study supports a possible relationship between the LDAEP and 5-HT
function in schizophrenia, it is worth mentioning that schizophrenia has also been found
to be associated with dysfunction of other neuronal systems such as glutamate and
dopamine (Carlsson et al. 1999). Furthermore, in the brain, interactions between the
5-HT and dopamine systems are complex, involving different 5-HT receptor subtypes
that affect different aspects of the dopaminergic function. Generally, the serotonergic
system inhibits dopaminergic function, thus serotonergic antagonists release the
Chapter 2
47
dopaminergic system from this inhibition (Kapur and Remington 1996). These findings
suggest that the results of Juckel and colleagues (2003) may have been in part
influenced by the dopamine system.
2.3.3. Migraine
Migraines have been related to a lower 5-HT function among other factors, such as
genetics (Gardner and Hoffman 1998) and hormones (estrogen; Brandes 2006).
5-HT1B/1D receptor agonists (e.g. sumatriptan) have been found to be highly effective in
the acute treatment of migraines (Dahlof et al. 1995), confirming 5-HT involvement in
migraine symptoms. In humans, the central action of migraine treatment cannot be
assessed directly. Therefore, based on the hypothesis that the LDAEP reflects 5-HT
function and that migraines are related to 5-HT function, the LDAEP could be a good
tool to investigate central mechanisms involved in migraine and to indirectly assess
migraine treatments in patients (Afra et al. 2000; Proietti-Cecchini et al. 1997;
Wang et al. 1996, 1999b).
Two studies reporting on LDAEP and migraines found that treatment with zolmitriptan,
a 5-HT1B/1D receptor agonist, increased LDAEP slope in migraine sufferers
(Proietti-Cecchini et al. 1997; Wang et al. 1996). However, this finding could not be
reproduced in other studies using the same or other tryptan drugs (Afra et al. 2000; Sand
and Vanagaite 2000; Wang et al. 1999b). In one of these studies, as a positive control
the 5-HT releasing drug, dexfenfluramine, induced the expected shallower LDAEP
slope in migraine patients (Proietti-Cecchini et al. 1997). Based on the inconsistencies
in the results mentioned above, the LDAEP cannot be considered a reliable marker for
assessing treatment in migraine sufferers. Migraine sufferers showed a steep LDAEP
slope at baseline which has been suggested to be the result of an AEP habituation deficit
at high intensity stimulation (Ambrosini et al. 2003).
2.3.4. Drug dependence and neurological disorders
Some drug dependence, such as ecstasy dependence and alcohol dependence, has been
related to an imbalance in the 5-HT system. Based on the hypothesis that there is a
Chapter 2
48
relationship between the LDAEP and 5-HT function, the LDAEP has been used to
investigate 5-HT function in drug dependent individuals.
2.3.4.a. Ecstasy users
Ecstasy, (±) 3,4 methylenedioxymethamphetamine (MDMA), is a synthetic,
psychoactive drug chemically similar to the stimulant methamphetamine and the
hallucinogen, mescaline. Ecstasy leads to an increase in levels of 5-HT and 5-HIAA in
the brain (Battaglia et al. 1987), by stimulation of 5-HT release and inhibition of its
reuptake. A steep LDAEP slope is therefore expected in ecstasy users. This is based on
the hypothesis that people with low 5-HT function (steep LDAEP slope) would gain
greater reinforcement from ecstasy use, when compared to those with normal 5-HT
function and that long term and repeated administration of ecstasy will cause a depletion
of 5-HT in the brain (Ricaurte et al. 1988).
Individual LDAEP responses to ecstasy use have been investigated in some studies.
First, Croft and colleagues (2001) reported a steeper ASF slope in long-term ecstasy
users, supporting that the LDAEP reflects low 5-HT function. Second, Tuchtenhagen
and colleagues (2000) reported a significant difference in the N1/P2 amplitude between
ecstasy users compared to controls, at a high intensity level (i.e. 90 dB), but not at low
intensity levels (i.e 60 to 80 dB). They also reported that ecstasy users, but not controls,
exhibited an increase in the tangential dipole amplitude with increasing stimulus
loudness. Due to the lack of information on the DSA slope between ecstasy users and
controls, and the fact that controls did not show steeper LDAEP slope with increasing
stimulus intensity levels, it cannot be inferred from these two studies, that steep LDAEP
slopes reflect a low 5-HT function in ecstasy users. Interestingly, investigating this
relationship using the DSA, Daumann and colleagues (2006) reported that several
aspects of ecstasy uses, such as frequency of use and drug dose, were associated with
the LDAEP slope.
Chapter 2
49
2.3.4.b. Alcoholism
Alcoholism has been linked with alterations of serotonergic neurotransmission (Topel
1985; Virkkunen and Linnoila 1997) and 5-HT related genetic parameters (Preuss et al.
2000). Early ERP studies have reported ethanol-induced changes in EEG rhythms and
ERPs (Järvilehto et al. 1975). Specifically, the length and the amplitude of the AEP
peaks was reduced after administration of a low dose of alcohol (0.4 g/kg; Gross et al.
1966; Hari et al. 1979) and after a high dose (1 ml/kg; Campbell and Lowick 1987).
More recently, in social drinkers, a decrease in the N1/P2 complex amplitude was
observed with increasing ethanol doses (Teo and Ferguson 1986). A decrease in the N1
and the P2 peak amplitude has also been found in healthy participants experiencing a
state of ‘hangover’ after alcohol administration (Järvilehto et al. 1975). These findings
have been replicated in animals studies (Ehlers 1988; Ehlers and Chaplin 1991). These
studies suggest a dysfunction of the AEP system after alcohol consumption and in view
of this, the LDAEP appears to be a valid tool in the investigation of alcoholism.
LDAEP studies using alcoholics have been carried out and report a steeper LDAEP
slope in alcoholics with a family history (Hegerl et al. 1995b; Preuss et al. 1997). This
relationship, however, could not be confirmed in LDAEP and genetic research (Preuss
et al. 2000). A few studies have investigated the ethanol effect in healthy participants
using the LDAEP. They consistently found a shallower tangential DSA slope after
ethanol challenges (Hegerl et al. 1996b; Juckel et al. 1995).
Based on the LDAEP thesis, the above-mentioned findings suggest that alcohol
increases serotonergic function and are in line with animal studies showing an increase
in serotonergic function after acute alcohol administration (McBride et al. 1990). These
studies clearly suggest a relationship between the LDAEP and alcohol consumption
and/or alcoholism. However, they only indirectly support the relationship between the
LDAEP and 5-HT system, since alcohol not only influences the 5-HT system, but also
the GABA and dopamine systems (McBride et al. 1990). In this context, it is relevant
to note that a shallower tangential DSA slope has been found in healthy participants
after acute administration of acamprosate, a GABA receptor agonist/glutamate receptor
antagonist, which has been used efficiently in patients for the treatment of alcohol
dependence (Gallinat et al. 1996). Therefore, previous findings on the relationship
between the LDAEP and 5-HT function should therefore be interpreted with caution.
Chapter 2
50
2.3.4.c. Conclusion on the LDAEP and drug dependence
In the alcoholic population, consistent results support a relationship between the
LDAEP and alcoholism. However, due to evidence suggesting the involvement of other
neuronal systems in alcoholism (GABA and dopamine), the relationship between the
LDAEP and the 5-HT system remains unclear. Ecstasy studies support the LDAEP as a
possible marker of 5-HT function in drug dependence. However, the relationship
between the LDAEP and drug use may be due to a predisposing factor in subjects for
drug use in general, rather than a consequence of the use of the drug itself. This is
particularly relevant to the issue that individuals with low 5-HT levels in the brain are
more likely to engage in novelty-seeking activities, such as drug taking, than individuals
with normal 5-HT levels (Kelly et al. 2006; Zuckerman 1986, 1990). Therefore, these
studies do not directly support a relationship between the LDAEP and 5-HT function.
2.3.5. Conclusion on the LDAEP in clinical studies
This review revealed substantial inconsistencies in LDAEP characteristics in clinical
populations. The LDAEP has been found to be a reliable tool in predicting treatment
outcome in a depressed population and in alcoholics. However, it remains to be
examined whether or not the LDAEP can be used in the assessment of treatment
outcome in schizophrenia and migraines. In addition, the possible involvement of other
neurotransmitter systems in the LDAEP need to be further investigated. The
above-mentioned clinical populations have all been found to be related to 5-HT
dysfunction. Therefore, the LDAEP may be a good indicator of 5-HT function in
individuals with these disorders and may be used to assess treatment outcome.
However, these studies cannot be used as evidence for a specific relationship between
the LDAEP and the 5-HT system (see Table 1-1 and section 1.3.5).
Chapter 2
51
2.4. Genetic influence
Individual differences in 5-HT function have been found to be due, at least in part, to
polymorphisms in the promoter of the 5-HT transporter (5-HTT) gene. Individuals
expressing the l/l genotype have higher 5-HT reuptake and therefore lower levels of
5-HT in the synaptic cleft compared to individuals expressing either the l/s or s/s
genotype (Lesch et al. 1996; Preuss et al. 2000). The different phenotypes of the 5-HT
transporter gene have been associated with anxiety, alcoholism and suicidal behavior
(for review see Lesch 2001). Because of the importance of the 5-HTT genes in the
modulation of the 5-HT function, several studies have been carried out to assess directly
the relationship between the LDAEP and 5-HT function in humans, while taking into
account individual 5-HTT phenotype variation. Gallinat and colleagues (2003) found a
shallower LDAEP slope for the l/l carriers than for l/s or s/s carriers. In contrast, some
others showed a steeper LDAEP slope in l/l carriers than in l/s or s/s carriers (Hensch et
al. 2006; Strobel et al. 2003). These studies clearly suggest some correlation between
genetic factors and the LDAEP. However, the genetic influence in the LDAEP requires
further investigation because of the discrepancies across previous studies.
Chapter 2
52
2.5. Conclusion
The relationship between the LDAEP and 5-HT function in humans is unclear, with the
most convincing evidence for a direct relationship coming from animal studies that have
investigated the 5-HT1A receptor system (Juckel et al. 1997, 1999; Manjarrez et al.
2005). In addition, studies which have been undertaken using humans, are indirect
correlational studies, that have assumed an underlying serotonergic abnormality in
patient groups (Hegerl et al. 1998; Juckel et al. 2003; Pogarell et al. 2004; Senkowski et
al. 2003). Also in humans, both clinical and healthy control studies have yielded
inconsistent results, which may be due to differences in study methodology. As
mentioned previously, some researches have suggested that the DSA-derived LDAEP is
a more reliable and effective measure than the ASF-derived LDAEP. The specificity of
the LDAEP to the 5-HT system remains unclear, and should be further investigated.
Chapter 2
53
2.6. Aims
The main aim of the current thesis was to increase our understanding of the relationship
between the LDAEP and 5-HT function using healthy participants, by conducting a
series of studies acutely increasing or decreasing 5-HT function. This thesis contains
three experimental chapters. The first specific aim was to examine the direct effect on
LDAEP of increases of 5-HT function induced by acute treatment with SSRIs. This
investigation further extends the findings of Nathan and colleagues (2006) in a larger
participant sample and using three different SSRIs. Further to Nathan and colleagues
(2006), who conducted their study using only the ASF-derived LDAEP analysis, the
present investigation will use two analysis methods, i.e. DSA- and ASF-derived
analysis in order to compare LDAEP methodologies. The second specific aim was to
investigate the effect on LDAEP of acutely decreasing 5-HT function using the ATD
method. Unlike many previous ATD LDAEP studies, the plasma ratio of free
tryptophan/LNAA will also be reported as a measure of central 5-HT depletion. Similar
to the SSRI investigation, DSA- and ASF-derived analysis methods will be compared.
Animal studies have reported changes in the LDAEP slope after stimulation of the
5-HT1A receptor (Juckel et al. 1997, 1999), however this has not been investigated in
humans. Furthermore, 5-HT1A receptors have been implicated in psychiatric disorders,
such as depression, where changes in LDAEP slope have been described (see section
2.3.1). The third specific aim therefore, was to examine the effect on the LDAEP of
5-HT1A receptor stimulation using the 5-HT1A receptor partial agonist, buspirone based
on evidence that buspirone predominantly activates presynaptic 5-HT1A autoreceptor,
leading to a decrease in 5-HT release at postsynaptic levels (Blier et al. 1990).
Finally, the results of each experimental investigation will be reviewed and discussed
about how they relate to one another. Further investigations will be proposed in view of
the present work these findings.
Chapter 3
54
Chapter 3
Experiment 1: The Effect of Three Selective Serotonin
reuptake Inhibitors on the LDAEP
Chapter 3
55
Introduction
Depression is the most common psychiatric disorder in the Western World, with a
lifetime prevalence of up to 17 % (Blair-West et al. 1999; Kessler et al. 1994). Low
5-HT activity, such as impairment in postsynaptic 5-HT1A receptor function, has been
linked to depression (Young et al. 1985). Serotonergic antidepressant drugs, such as
SSRIs, have been found to be effective and safe in the treatment of depression
(Montgomery et al. 1993). However, there is a considerable number of patients who are
non-responsive to SSRI treatment. This raises the need to identify individual clinical
responses to SSRI treatment.
As reviewed in chapter 1, there is substantial literature suggesting that the LDAEP
provides a good estimate of 5-HT function in the brain. The LDAEP is achieved by
measuring auditory cortex activity using EEG recordings and could therefore, be a
valuable non-invasive tool to investigate SSRI-responsiveness in patients with
depression. As discussed in section 2.3.1, a few studies have investigated the LDAEP
slope in depressed patients using SSRIs. For example, acutely enhancing 5-HT
availability with the SSRI fluvoxamine, resulted in a shallower LDAEP slope in
depressed patients (Hegerl et al. 1991). Also, patients who responded to lithium
treatment were characterised by a steep LDAEP slope before treatment compared to
those who did not respond to lithium treatment (Hegerl et al. 1996a, Juckel et al. 2004).
However, no effect on the LDAEP slope was reported after chronic administration of
SSRIs such as paroxetine, sertraline and citalopram (Gallinat et al. 2000).
Four studies have directly examined the relationship between the LDAEP and enhanced
5-HT function using SSRIs in healthy participants. One study found a shallower
LDAEP slope after acutely enhancing 5-HT availability with the SSRI, fluvoxamine
(Hegerl et al. 1991). Nathan and colleagues (2006) also showed that acutely enhancing
5-HT availability with a more selective SSRI, citalopram, resulted in a shallower
LDAEP slope, however this was not replicated in a study using intravenous citalopram
(Uhl et al. 2006) or using co-administration of SSRIs and pindolol (Segrave et al. 2006).
The findings of Hegerl and colleagues (1991) and of Nathan and colleagues (2006) are
consistent with the animal literature where increasing 5-HT function resulted in a
Chapter 3
56
shallower LDAEP slope (Juckel et al. 1997; for more details on animal literature refer to
section 2.1.). The findings in healthy participants are thus less consistent than those of
the depression literature (see section 2.2 for more details), although they do support the
findings of Hegerl and colleagues (1991) in that LDAEP is a marker for serotonergic
function.
The discrepancies across studies in depressed patients may be related to differences in
selectivity of the SSRIs for inhibition of 5-HT reuptake, which in turn would influence
the extent of increasing availability of extracellular 5-HT. The decreasing order of
selectivity for 5-HT uptake is citalopram, sertraline, paroxetine and fluvoxamine
(Hiemke and Härtter 2000). Citalopram is the most selective SSRI developed with little
effect on noradrenaline or dopamine uptake (Pollock 2001), while other SSRIs, such as
sertraline, have been found to also bind to the dopamine transporter (Richelson 1994).
Thus, it is possible that the discrepancies between the negative results in depressed
patients (Gallinat et al. 2000) and more positive results in healthy controls (Nathan et al.
2006) may be related to the relative selectivity of the different drugs used, with Nathan
and colleagues (2006) using the more selective compound (citalopram), which may be
necessary to demonstrate modulation of the LDAEP. However, it should be noted that
this interpretation has difficulties, in that Gallinat and colleagues (2000) failed to find
an effect of citalopram on LDAEP in depressed patients, suggesting that premorbid
factors may also affect the purported 5-HT/LDAEP relationship.
Given the discrepancies in the literature, the present study will investigate the
relationship between LDAEP and 5-HT function using three different SSRIs
(citalopram, escitalopram and sertraline). Citalopram is a racemic mixture consisting of
R(-) and S(+)-enantiomers in a 1:1 ratio. Citalopram (Figure 3-1) is a bicyclic,
phthalane derivative with high affinity for the 5-HTT (Table 3-1) and no known
intrinsic activity at any of the 5-HT receptor subtypes or other neurotransporter systems
(Hyttel 1994). Escitalopram (Figure 3-1), is the therapeutically active S-enantiomer of
citalopram and has been shown to have a high affinity for the 5-HTT (Table 3-1, Waugh
and Goa 2003). Animal studies using a variety of in vitro and in vivo measures (i.e.
reuptake inhibition, receptor binding, behavioural models) suggest that escitalopram is
twice as efficient as citalopram when containing the same amount of the S-enantiomer
Chapter 3
57
(Sanchez et al. 2004; Waugh and Goa 2003). In support of this, clinical studies
demonstrate superior efficacy of escitalopram when compared to citalopram
at pharmacologically equivalent doses (Montgomery et al. 2001; Sanchez et al. 2004).
Furthermore, a number of microdialysis studies have shown that escitalopram alone is
more effective at increasing extracellular 5-HT levels in the brain than an equivalent
dose of citalopram (Sanchez et al. 2004). Amongst the SSRIs, animal studies suggest
that sertraline is the most potent inhibitor of 5-HT reuptake, although it has less
selectivity compared to citalopram (Sanchez et al. 2004).
Figure 3-1: Structure of citalopram, escitalopram and sertraline
Table 3-1: Comparison of serotonin receptors inhibition potencies, affinity and pharmacokinetic parameters for citalopram, escitalopram and sertraline
Drugs Potency (IC50) (nmol/L)
Affinity for [3H]-5-HT Ki (nmol/L)
T1/2 (hr)
Tmax (hr)
Citalopram 3.9a 9.6e,f 36h 2-4b
Escitalopram 2.1a 2.5e,f 27i 3.2-9.2c
Sertraline 1.8d 2.8e 22.4g 4-5a
a: Waugh and Goa (2003) d: Fabre and Hamon (2003) g: Hiemke et al. (2000) b: Pollock (2001) e: Sandeep and Sánchez (2002) h : Kragh-Sørensen et al. (1981) c: DeVane et al. (2002) f: Owens et al. (2001) i: Søgaard et al. (2005)
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Another issue this study will address is the difference between the analysis methods
used in literature, i.e. the scalp topography analysis (ASF) and the dipole source
analysis (DSA) method. Indeed, both methods have been used in LDAEP studies with
SSRIs. For instance, the ASF-derived LDAEP analysis method has been used in
healthy participants to determine the relationship between SSRIs and LDAEP (Hegerl et
al. 1990; Nathan et al. 2006; Uhl et al. 2006), while the DSA-derived LDAEP analysis
method has been used in depressed patients (Gallinat et al. 2000; Juckel et al. 2004).
The DSA-derived LDAEP method has been reported to be an important methodological
advance over the ASF-derived LDAEP method (Mulert et al. 2002; Scherg and Picton
1991). The purported advantage of the DSA method over the ASF is that DSA allows,
in part, the separation of the primary (A1) and secondary (A2) auditory cortices, with
the former but not the latter, thought to relate to 5-HT function (Hegerl et al. 1994).
The N1/P2 complex is explained by the activity of two dipoles per hemisphere, a
tangential that is thought to represent the activity of A1 and a radial that is thought to
represent the activity of A2, which means that activity changes in the 5-HT-innervated
A1 can be measured separately (Hegerl and Juckel 1993; Hegerl et al. 1994; Scherg and
Picton 1991; refer to section 1.3.4 for more details). Consistent with this view, animal
studies reported a significant change in the LDAEP recorded in A1 after administration
of serotonergic drugs (8-OH-DPAT, ketanserin), while the LDAEP recorded in A2 was
unaffected (Juckel et al. 1997, 1999). Therefore, only the LDAEP measured with the
tangential dipole is expected to represent 5-HT function.
In summary, the primary aim of the present investigation was to replicate and extend the
results of Nathan and colleagues (2006). The acute effects of pharmaceutically
equivalent doses of escitalopram, citalopram and sertraline on the LDAEP slope were
examined in healthy participants, in order to further investigate the discrepancies found
in the literature between the LDAEP results with different types of SSRIs. Furthermore,
differences between the DSA-derived LDAEP slope and ASF-derived LDAEP slope
were investigated by comparing the effects of the SSRIs using both analysis methods.
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3.1. Methods
3.1.1. Participants
Twenty-two non-smoking, adult male participants were recruited for this study using
advertising employment websites at Swinburne University of Technology (Hawthorn,
Vic, Australia), the University of Melbourne (Parkville, Vic, Australia) and Monash
University (Clayton, Vic, Australia). Of these participants, only 16 completed the study
and one was further excluded from analysis due to poor EEG recording. The remaining
15 participants were aged between 18 and 36 years (Mean = 23.3, SD = 6 years).
Participants received $200 for their time, which was paid upon completion of the study.
To avoid any possible drug interactions with test drugs administered during the study,
participants who reported taking any medication were excluded. In addition,
participants were excluded from the study if they reported a personal or family history
of psychological or psychiatric illness, use of nicotine or illicit drugs, hearing
difficulties or consumption of large quantities of vitamin supplements or soy products.
The study measures and procedure were thoroughly explained to all participants prior to
the beginning of the study and written informed consent was obtained (Appendix A-1).
3.1.2. Study design
The present study was approved by the Swinburne University of Technology Human
Research Ethics Committee. This study used a double-blind, placebo-controlled,
repeated-measures design. Each participant underwent the same testing procedures in
each testing session. All participants attended four full-day testing sessions, separated
by a minimum 1-week washout period. This washout period was chosen following the
Food and Drug Administration guidelines, which specify 5 half-lives as a suitable
washout period. The longest drug half-life in the present study was 36 hours for
citalopram (Table 3-1), therefore a minimum 1-week washout is sufficient to minimize
any possibility that the treatment administered first can affect the outcome of the
subsequent treatment. The treatment conditions were: (i) sertraline (Zoloft®, 50 mg,
Pfizer, West Ryde, NSW, Australia); (ii) escitalopram (Lexapro®, 10 mg, Lundbeck
Australia); (iii) citalopram (Cipramil®, 20 mg, Lundbeck Australia); (iv) one capsule of
placebo (flour and gelatine). For blinding purposes, all tablets were enclosed within a
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gelatine capsule, filled with plain flour, giving equivalent appearance for each
condition. The doses for escitalopram and citalopram were selected based on the
evidence that the given dose of escitalopram (10 mg) would be equivalent
(i.e. containing the same amount of S-enantiomer) to twice the dose of citalopram
(20 mg) (Owens et al. 2001; Sanchez et al. 2003). The sertraline dose (50 mg) selected
is regarded to be pharmaco-equivalent to the citalopram dose with regard to
pharmacodynamic effects (i.e. reuptake inhibition and clinical effects; Stahl 2000).
The timing of the drug administration, 3.5 hrs before EEG recording, was chosen to be
within the range for the peak plasma level for each treatment condition: sertraline
(tmax = 3.2-9.2 hrs; DeVane et al. 2002), escitalopram (tmax = 4-5 hrs; Waugh and Goa
2003), citalopram (tmax = 2-4 hrs; Hyttel 1994; Pollock 2001). The treatment
administration was randomised and was counterbalanced using a latin square design
(Appendix B-1), to ensure that an equal number of participants were tested under each
acute treatment condition. Participants were tested at the same time of day, for each of
the four testing sessions.
3.1.3. Experimental procedure
Participant screening and pre-experimental procedure
Study applicants were given the study information sheet (Appendix C-1) and if they
agreed to participate in the study, they were pre-screened over by telephone by the
experimenter using an exclusion criteria questionnaire and semi-structured psychiatric
interview (Prime MD). If they satisfied the criteria, a full description of the
experimental procedure and the drug side effects was explained to the participant.
Participants then underwent a medical interview conducted by a physician (for medical
forms, see Appendix D) to check for any obvious medical conditions and that the
participants fit all the selection criteria. They were then given a numerical identifier,
which was used throughout the study to ensure confidentiality.
Testing day
The day before the testing session, participants were contacted by telephone to
encourage compliance with the experimental conditions and were requested not to
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consume alcohol or caffeinated products for at least 24 hours prior to testing. Table 3-2
summarises the procedure for each testing session. On each testing day, participants
arrived at 9:30 am at the Brain Sciences Institute (Swinburne University of
Technology), and were asked to complete the Visual Analogue Mood Scales (VAMS;
Bond and Lader 1974). This survey consists of sixteen 100 mm horizontal scales (e.g.
Happy, Sad, Sociable, Withdrawn, Relaxed, Tense; Appendix E) and participants were
asked to place a mark on each line that described their current mood state. Upon
completion, they were administered the treatment. The participant was then asked to
wait in a quiet room and was offered a standard selection of magazines of neutral
content and allowed to do personal study. The participant was regularly visited by the
experimenter in order to determine if there were any treatment side effects. At the end
of the waiting period, the participant was set up for the EEG recording. Electrode
locations were then digitised, the VAMS test was done again, and the EEG recording
session commenced. Each EEG recording session lasted for approximately one hour,
with breaks in-between tasks to give instructions to the participant and also for rest.
Upon completion of the testing session, the EEG cap and the face electrodes were
removed, and the participant’s hair was washed.
Table 3-2: Timeline of experimental procedure for the SSRI experiment
Time Activity
9:30 am Participant arrives, completion of baseline mood rating questionnaires (VAMS1)
T0 (10 am) Treatment administration (placebo, escitalopram, citalopram or sertraline)
T+2 ½ hrs (12:30-12:45 pm) Completion of mood rating questionnaires (VAMS 2)
T+2 ¾-+3 ½ hrs (12:45-1:30 pm) EEG set-up + 3D Map recording
T+3 ½ hrs (1:30 pm) EEG recording starts
T+4 ½ hrs (2:30 pm) EEG recording completed, hair washing
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3.1.4. Data acquisition
EEG recordings were conducted in a sound-attenuated and electrically shielded room.
Participants sat comfortably in an armchair with their eyes 60 cm from a computer
screen and they were instructed to avoid excessive movements during the testing
session. The EEG was recorded from 68 scalp sites, at locations based on the
International 10/20 recording system using tin electrodes inserted in a highly elastic
fabric cap (Quik-Caps, NeuroScan Inc, Sterling, VA, USA), referenced to an electrode
midway between Cz and CPz.
As part of an electro-oculogram (EOG) correction protocol and prepulse inhibition
paradigm (data not shown here), the participants’ skin was cleaned at the location of
face electrodes using alcohol wipes (WEBCOL®, Kendal Healthcare, Mansfield, MA,
USA) and abrasive gel (Nuprep ™ gel, D.O Weaver & Co, Aurora, CO, USA) to assist
in maintaining the impedance of these face electrodes below 5 kΩ. Five face electrodes
were used: a bipolar montage (EMG1 and EMG2) below the right eye to record
electro-myographic activity, and monopolar recordings from electrodes below (E3) and
above (E1) the left eye to record eye movement activity (EOG), and on the nose as
reference in the prepulse inhibition experiment (Figure 3-2).
Figure 3-2: Participant set up for recording session
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To reduce electrode impedances, a small amount of water-based gel (Electro-cap
International Inc., Eaton, OH, USA) was used for each electrode (scalp and face
electrodes). At the start of the recording, impedances were less than 5 kΩ. Data were
recorded using NeuroScan equipment with SynampTM amplifiers (NeuroScan Inc).
EEG was continuously recorded, digitised at 500 Hz and filtered using a 0.05-500 Hz
band-pass filter. Electrode locations were digitised before the EEG session using a
Polhemus 3-D digitiser (Polhemus Inc, Colchester, VT, USA), with the electrode
locations digitised in relation to three anatomical landmarks (left and right preauricular
points, and nasion: PAN landmarks). This process allows electrode locations to be
determined relative to the participant’s head anatomy and to match the EEG data for the
dipole source analysis.
3.1.5. Stimuli
Stimuli were presented using the STIM Audio System and STIM software (NeuroScan
Inc), with sounds applied to the participant binaurally using foam ear inserts (Aero
Company Auditory System, Indianapolis, IN, USA). Stimuli of the LDAEP task
consisted of 100 ms (10 ms rise and fall time) binaural 1000 Hz tones of five intensities
(60, 70, 80, 90, 100 dB, SPL). The stimuli were presented in a pseudorandom fashion
(Appendix F) with 1.85 ± 0.2 s SOA. This task lasted for eight minutes. During the
LDAEP paradigm, an additional task was given to the participants to distract their
attention from the stimuli as attention effects on the LDAEP have been previously
reported in humans (Carrillo-de-la-Peña 1999). This “distracter” task involved
participants being instructed to look at the screen and press a keypad when a face with a
nose flashed up onto the screen (as opposed to a face without a nose). These appeared
on average every 10.5 s, with a range of 1-21 s.
3.1.6. Data analysis
VAMS
The sixteen 100 mm scales (Appendix E) were scored by measuring in millimetres
from the end of the line to the participant’s mark according to the method described by
Bond and Lader (1974). The scales were then allocated into three factors (factor 1:
sedation (nine scales), factor 2: content (five scales) and factor 3: anxiety (two scales);
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64
for more details see Bond and Lader 1974). The mean of each factor was computed for
each participant and used in the statistical analysis.
ERP Analysis
For each participant and testing session, data were EOG-corrected (Croft and Barry
2000), visually inspected to remove non-ocular artefacts, re-referenced to a common
average reference, epoched -100 to 400 ms post-stimulus and then averaged (separately
for each stimulus intensity; e.g. 60, 70, 80, 90 and 100 dB).
Furthermore, a number of summary averages were created from these individual ERP
averages in order to facilitate the DSA analysis. First, a “grand average” was created,
being the average of the above ERPs across all participants, treatments (placebo,
citalopram, escitalopram and sertraline) and stimulus intensities (60, 70, 80, 90 and
100 dB). Second, for each participant separately, the above ERPs across all treatments
and stimulus intensities were averaged; “subject average”. Finally, for each participant
and treatment separately, the above ERPs across the five stimulus intensities were
averaged; “subject-treatment average”.
Dipole Source Analysis (DSA)
One participant was excluded from the DSA due to a corrupted 3Dmap file. DSA was
performed with CURRY® 5.0 software (NeuroScan Inc) on the above ERP data. The
BEM-interpolated method was used for the dipole localisation instead of the classical
spherical 3 or 4 shells model, as BEM models have been shown to be superior in the
non-spherical part of the head (Fuchs et al. 1998). In CURRY®, the BEM-interpolated
model consists of 16, 074 triangles overall, 8043 nodes (brain: 3858, skull: 2681 and
skin: 1504 nodes) and edge lengths of: 3.3 mm (brain), 5.1 mm (skull) and 7.5 mm
(skin). The optimal location and orientation of the dipole were found by an iterative
process derived from the model described by Scherg and Picton (1991). The dipoles
were fitted using a two stage fit procedure consisting of a “basic dipole model”
followed by an “individual dipole model” (Hegerl et al. 1994):
The “basic dipole model” analysis procedure was performed to provide an estimation of
the centre of activity within A1 and A2 separately in each hemisphere of the
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65
components underlying the N1/P2 complex. This procedure was done for the grand
average of the entire experimental data set (including all participants, conditions and
intensity ERPs) in order to reduce individual differences in term of the localisation of
the centre of activity within A1 and A2 separately and for each hemisphere separately.
This centre of activity was used to fit the dipole for each participant separately in the
“individual dipole model”. This procedure involved two steps:
1. The number of components underlying the scalp N1/P2 complex was estimated
using a series of substeps. First, the noise level was estimated as the standard
deviation of a noisy period within the prestimulus interval. Second, the time range
of the N1/P2 complex was manually determined from the mean global field power
(MGFP) waveform (i.e. from the start of the first peak deflection around 100 ms
(N1) to the end of the peak deflection around 200 ms (P2) after the stimulus, Figure
3-3A). Finally, the number of independent components was estimated from the
results of an independent component analysis (ICA; Hyvarinen and Oja 2000) of the
time range of the N1/P2 complex (68-296 ms), using the above defined noise
estimate. In line with the DSA model proposed by Scherg and Von Cramon (1986),
four components with a signal-to-noise ratio (SNR) above 10 were chosen to
explain the measured data (Figure 3-3C).
2. The locations of the above four dipoles were fitted to the above time range (two
dipoles per hemisphere, one each for A1 and A2 for each hemisphere; Scherg and
Von Cramon 1986). This dipole location was performed using a regional dipole
model, whereby for each fixed dipole separately, its strength was taken to be the
largest value generated within the N1/P2 complex time range. These dipoles were
constrained within 10 mm of the A1 and A2 centroids separately and for each
hemisphere separately (according to the centroid stereotaxic coordinates for A1 and
A2 given by Brown et al. 2004; see Table 3-3 for coordinates). The location of the
dipole does not change over time and the strength is computed as a function of time.
This provides comparability with BESA results.
The two dipoles per hemisphere explained 97.4 % of the variance of the grand average
scalp data in the time window of the N1/P2 component (68-296 ms). The resulting
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dipole locations (dipole 3D coordinates) were recorded in three-dimensional space (i.e.
x, y, z) to be used in the following “individual dipole model”.
Table 3-3: Stereotaxic coordinates for the primary (A1) and secondary (A2) auditory cortex
Brain atlas values are in millimetres and the corresponding Brodmann area in parentheses (from Brown et al. 2004).
Hemisphere Region x y
A1 (41) 48 -18 Right
A2 (42) 58 -8
A1 (41) -42 -18 Left
A2 (42) -54 -14
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Figure 3-3: Example of results for the Basic Dipole Model performed in CURRY® Two dipoles per hemisphere were found in the N1/P2 complex time range (68-296 ms): the tangential dipoles (green and purple) and the radial dipoles (red and blue). A: Superimposition of EEG waveforms (blue lines) with the Mean Global Field Power (in red line) for the N1/P2 complex epoched time range. B: Display of the 3D map electrode placement with the dipoles. C: Independent component analysis (ICA) results output for the four selected dipoles. D: IRM display with the dipoles fitted.
The “individual dipole model” analysis procedure was performed in order to determine
a more accurate estimate of the dipole location for each individual, by allowing
variation from the “basic dipole model” above. This procedure involved three steps:
1. For each participant, the “basic dipole model” fitting procedure was performed on
the “subject average” (i.e. ERP composed of all sessions and stimulus intensities),
with two differences. First, the dipole 3D coordinates derived from the “basic
dipole model” for the A1 and A2 centroid activity were used in place of the Brown
and colleagues (2004) A1 and A2 centroid coordinates. Second, the dipole was
constrained within 5 mm of these locations (as opposed to 10 mm), to determine a
more accurate location of the dipole source.
2. For each participant, the fitting procedure of step 1 was then used on the
“subject-treatment average” (i.e. ERP composed of the five stimulus types
combined, for each session separately), different only in that the dipole 3D
A
C
B
D
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coordinates derived in the “individual dipole model” step 1, were used in place of
those derived from the “basic dipole model”.
3. For each participant and each session, the fit procedure of the “individual dipole
model” step 2 was then used on the ERP of the five intensity stimuli separately,
differing only in that the dipole 3D coordinates derived in the “individual dipole
model” step 2 were used in place of those derived from the “individual dipole
model” step 1.
Scalp topography (ASF) method
ERPs were analysed in terms of peak-to-peak N1/P2 amplitude. N1 and P2 amplitudes
were calculated as the minimum (N1) and maximum (P2) amplitudes (relative to
baseline) in the 80-140 ms and 110-240 ms time windows, respectively, at Cz.
DSA and ASF slope estimation
For each participant and each session, the DSA slope of the dipole strength by loudness
(dB level) function was estimated using least squares linear regression, where dipole
strength was the criterion variable and loudness of the stimulus (60 dB to 100 dB) was
the predictor variable. This was performed separately for the tangential and radial
dipoles, resulting in “tangential slope” and “radial slope” respectively. For each
participant and session, the ASF slope of the N1/P2 amplitude by loudness (dB level)
function was estimated using least squares linear regression, where N1/P2 amplitude
was the criterion variable and loudness of the stimulus (60 dB to 100 dB) was the
predictor variable.
3.1.7. Statistical analysis
All statistical analyses were performed using SPSS 14 software package for Windows
(SPSS Inc., Chicago, IL, USA). Preliminary analyses were done to determine whether
violations of the assumptions for each statistical test occurred. Differences were
considered statistically significant at p < 0.05.
In order to determine if there was a pre-drug difference between mood for the four
testing sessions, whether there was an effect of the treatment on mood and whether this
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interacted with VAMS Factor, a four (Treatment: placebo, citalopram, escitalopram and
sertraline) x two (Time: before and after) x three (Factor: factor 1, factor 2, factor 3)
repeated-measures ANOVA was performed.
In terms of the DSA statistical analysis, to determine if there was an effect of stimulus
loudness on DSA strength in the placebo condition, a repeated-measures linear contrast
was used where the independent variable was Stimulus Intensity (60, 70, 80, 90 and 100
dB), and the dependent variable was “Tangential strength” (i.e. mean for the tangential
right dipole (TR) strength and the tangential left dipole (TL) strength) in the placebo
condition.
In order to determine if there was an effect of the SSRIs collectively on the DSA slope,
a Wilcoxon’s Signed-rank test was performed where the independent variable was
Treatment (placebo and SSRI, where “SSRI” was created from averaging “Tangential
Slope” from the three SSRIs) and the dependent variable was Tangential Slope. The
non-parametric Wilcoxon’s Signed-rank test was used because the TL slope and the TR
slope data did not have normal distributions and could not be normalised. Furthermore,
to determine if there was a difference between the three SSRIs, a Friedman test was
performed where the independent variable was SSRI (citalopram, escitalopram and
sertraline) and the dependent variable was the Tangential slope. Following each
significant result, post hoc Wilcoxon’s Signed-rank tests were performed to test for a
difference between SSRIs.
In order to determine if there was a differential effect of the treatments on the two
hemispheres, a Wilcoxon’s Signed-rank test was performed where the independent
variable was Treatment (placebo and SSRI) and the dependent variable was average
“TangDif” across the three SSRI conditions (where “TangDif” was the difference
between the slopes of the two hemispheres). Further, to determine whether the three
SSRIs differentially affected the hemispheres, a Friedman test was performed where the
independent variable was SSRI (citalopram, escitalopram and sertraline) and the
dependent variable was TangDif. Following each significant result, post hoc
Wilcoxon’s Signed-rank tests were performed to determine where any differences lay.
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Additionally, three exploratory analyses were performed. First, to determine whether
any above effects were general or specific to A1, equivalent analyses to the second set
of DSA analyses described above were performed with the Radial dipole (Rad) slope in
place of the Tangential. Specifically, a Wilcoxon’s Signed-rank test was done where
the independent variable was Treatment (placebo and SSRI) and the dependent variable
was the Radial slope. The non-parametric Wilcoxon’s Signed-rank test was used
because the RL slope and the RR slope data did not have normal distributions and could
not be appropriately normalised.
Second, to determine whether similar results were found for the ASF slope as were
reported for the DSA slope above, the following analyses were done: (a) to determine
whether there was an effect of stimulus loudness for N1/P2 scalp-derived amplitude in
the placebo condition, a repeated-measures linear contrast was conducted, where the
independent variable Stimulus Intensity (60, 70, 80, 90 and 100 dB), and the dependent
variable was the N1/P2 complex amplitude; (b) In order to determine if there was any
effect of the SSRIs on the ASF slope a repeated-measures contrast was conducted,
comparing the placebo condition to the mean of the three SSRI conditions, where the
independent variable was Treatment (placebo, citalopram, escitalopram and sertraline)
and the dependent variable was the ASF slope. Furthermore, to investigate if there was
any difference in the ASF slope between the three SSRI conditions, a repeated-measures
ANOVA was conducted, where the independent variable was Treatment (citalopram,
sertraline and escitalopram) and the dependent variable was the ASF slope.
Finally, to determine whether there was a relation between the ASF and DSA results,
first a Pearson’s correlation was performed comparing the ASF slope and the DSA
slope. Second, in order to determine whether results derived from ASF or DSA showed
a larger drug effect, the difference between the SSRIs and the placebo (i.e.
Treatment_effect = Mean_SSRI – placebo) was computed for each method and
compared with a Wilcoxon’s Signed-rank test, where the independent variable was
Method (ASF and DSA) and the dependent variable was Treatment Effect. The
Wilcoxon’s Signed-rank test was used because the data did not have a normal
distribution and could not be normalised. Note that, since DSA slopes have a different
magnitude to ASF slopes, the DSA slope and the ASF slope values were converted into
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71
Z-scores before the Wilcoxon’s Signed-rank test was performed. The LDAEP slope
was converted to Z-scores across the combined treatment conditions (placebo,
citalopram, sertraline and escitalopram), for the DSA and ASF slope separately. The
conversion into Z-score slopes was computed by subtracting the mean from the slope
score and dividing by the standard deviation for each group separately.
3.2. Results
VAMS
The repeated-measures ANOVA showed that there was no main effect of Treatment
(F(3,42) = 0.79, p = 0.50; partial η2 = 0.21), no interaction of Treatment-by-Time
(F(3,42) = 1.56, p = 0.21; η2 = 0.38), Treatment-by-Factor (F(6,84) = 1.10, p = 0.37; partial
η2 = 0.07), nor Treatment-by-Time-by-Factor (F(6,84) = 0.74, p = 0.62; partial η2 = 0.28).
These results suggest that there was no effect of any treatment on mood, there were no
pre-existing differences between the sessions in the participant’s mood before treatment,
and that treatment and time did not interact with VAMS factors.
DSA slope
There was a linear increase in the tangential strength across the five stimulus intensities
(repeated-measures linear contrast, F(1,14) = 123.28, p < 0.01; partial η2 = 0.90). There
was no effect of the SSRIs collectively on the Tang-slope (Wilcoxon’s Signed-rank test,
z = -0.96, p = 0.33), nor was there a difference in Tangential slope between the three
SSRIs (Friedman test χ2(15) = 0.13, p = 0.94). Furthermore, there was no differential
effect of the collective treatment on the two hemispheres (Wilcoxon’s Signed-rank test,
z = -0.97, p = 0.34), nor was there a differential effect of the three SSRIs on the two
hemispheres (Friedman test, χ2(15) = 2.80, p = 0.257), indicating that the SSRIs did not
differentially modify the tangential dipole slope (Figure 3-4). Finally, there was also no
effect of the SSRIs on the radial dipole slope (Wilcoxon’s Signed-rank, z = -0.45,
p = 0.65, Figure 3-4).
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Figure 3-4: (a) DSA of LDAEP data in the placebo (PLAC) and citalopram (CIT) conditions, shown for the left and right tangential (top panels) and radial (bottom panels) dipoles. A: Scatter graph of individual data. B: Box-and-whiskers plot of LDAEP percentiles, N = 15.
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Figure 3-4 (Cont.): (b) DSA of LDAEP data in the placebo (PLAC) and escitalopram (ESCIT) conditions, shown for the left and right tangential (top panels) and radial (bottom panels) dipoles. A: Scatter graph of individual data. B: Box-and-whiskers plot of LDAEP
percentiles, N = 15.
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Figure 3-4 (Cont.): (c) DSA of LDAEP data in the placebo (PLAC) and sertraline (SERT) conditions, shown for the left and right tangential (top panels) and radial (bottom panels) dipoles. A: Scatter graph of individual data. B: Box-and-whiskers plot of LDAEP percentiles, N = 15.
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ASF slope
The increasing loudness of the auditory stimuli led to increasing amplitudes of N1/P2
complex (Figures 3-5 and 3-6). There was a linear increase in the N1/P2 complex
amplitude across the five stimulus intensities (repeated-measures linear contrast,
F(1,14) = 111.9, p < 0.01; partial η2 = 0.75) (Figure 3-5). However, this analysis failed to
find a significant difference between the placebo and the combined SSRIs (F(1,14) = 0.32,
p = 0.59; partial η2 = 0.022) (Figure 3-7). This suggests that there was no effect of the
combined SSRIs on the ASF slope. There was also no main effect of the SSRIs
(repeated-measures ANOVA, F(1,14) = 0.16, p = 0.70; partial η2 = 0.012), indicating that
there was no difference between the three SSRIs (Figure 3-7).
0
4
8
12
16
PLAC
ESCIT (10 mg)SERT (50 mg)
CIT (20 mg)
60 70 80 90 100
Stimulus intensity (dB SPL)
N1/
P2 a
mpl
itude
( µV
)
Figure 3-5: Mean N1/P2 amplitude plotted against stimulus intensity for the four treatments conditions: placebo (PLAC), citalopram (CIT), escitalopram (ESCIT) and
sertraline (SERT), N = 15.
The exploratory analysis revealed two further findings. First, there was no significant
correlation between the ASF and DSA analysis methods (Pearson correlation analysis,
r = 0.11, p = 0.34) and only 11 % of the variance in the DSA values could be explained
by the variance in the ASF values. Second, there was no difference between the drug
effects derived from the ASF and DSA methods (Wilcoxon’s Signed-rank test,
z = -0.85; p = 0.40).
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Figure 3-6: Grand mean ERPs at Cz of three intensities of auditory stimulus (i.e. 60, 80 and 100 dB), following treatment with citalopram, escitalopram, sertraline and
placebo, N = 15.
60 dB SPL
0
-5
-10
5
10
80 dB SPL
100 dB SPL
ms-100 0 100 200 300 400
Stimulus
Am
plitu
de µ
V
0
-5
-10
5
10
0
-5
-10
5
10
escitalopram (10 mg)citalopram (20 mg)placebo
sertraline (50 mg)
60 dB SPL
0
-5
-10
5
10
80 dB SPL
100 dB SPL
ms-100 0 100 200 300 400
Stimulus
Am
plitu
de µ
V
0
-5
-10
5
10
0
-5
-10
5
10
escitalopram (10 mg)citalopram (20 mg)placebo
sertraline (50 mg)
Chapter 3
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Figure 3-7: ASF of LDAEP data in the placebo (PLAC), citalopram (CIT), escitalopram (ESCIT) and sertraline (SERT) conditions. A: Scatter graph of individual data. B: Box-and-whiskers plot of ASF slope percentiles, N = 15.
Chapter 3
78
3.3. Discussion
The present study aimed to replicate the previous results of Nathan and colleagues
(2006), where acute treatment with 20 mg of citalopram led to a shallower LDAEP
slope, presumably by increasing serotonin availability, and to extend this finding by
investigating three different SSRIs. The current study also compared the effects of
5-HT modulation using both the DSA and ASF methods to estimate the LDAEP slope.
The present study failed to replicate the previous results, in that no modulation of
LDAEP by SSRIs was found. This lack of replication was not related to the particular
SSRIs used (and their respective selectivity) as the same lack of significant effect was
found for citalopram, escitalopram and sertraline. Furthermore, no differences were
found between the DSA-derived and ASF-derived LDAEP analysis methods.
The discrepancies between the results of the present study and those of Nathan and
colleagues (2006) may be related to methodological differences. For instance, the
different results may relate to the time window during which the EEG was recorded. In
the study by Nathan and colleagues (2006), the EEG was recorded two hours after
treatment with citalopram, whilst in the present study it was recorded three and half
hours after treatment. Three and half hours was chosen to best coincide with the
published peak plasma concentrations of citalopram, escitalopram and sertraline. Even
though electrophysiological recording took place within the peak plasma concentration
range of each of the SSRIs, it is possible that the effect of the SSRIs on serotonergic
transmission may occur earlier than this. However, a study comparing the effect of
10 mg of escitalopram and 20 mg of citalopram in healthy participants has reported
marked and similar increases in the salivary and plasma cortisol levels at two and three
hours post-treatment when compared to placebo (Nadeem et al. 2004). Based on these
findings, in the present study, escitalopram and citalopram were active within the EEG
recording window. The recording time chosen therefore appears not to be responsible
for the discrepancy between the results of Nathan and Colleague (2006) and those of the
present study. It should be noted that the finding of peak plasma levels for the SSRIs
around three hours after dosing does not mean it is also the peak time point of effects on
central 5-HT neurotransmission.
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It could be that, the discrepancy between the present findings and those of previous
research may be due to methodological differences regarding recording and analysis
methods. However, recording parameters and ASF-derived analysis were strictly
consistent with those of Nathan and colleagues (2006) and those of other studies in the
literature (Croft et al. 2001, Senkowski et al. 2003). Therefore, it can be assumed that
the methodology used here was not responsible for the discrepancies between the two
studies. Instead, the discrepancy could be due to the sample, where Nathan and
colleagues (2006) tested both men and women but, the present study used only men. As
was discussed in section 1.3.5.a, there is evidence of gender differences in 5-HT
neurotransmission. For instance, 5-HT function has been shown to be influenced by the
5-HT releasing agent, fenfluramine (Goodwin et al. 1994) and by diet (Anderson et al.
1990) in women, but not in men. In addition, the pattern of antidepressant response has
been found to vary between men and women. For example, women treated with
citalopram showed a significantly greater response to the treatment when compared to
men (Berlanga and Flores-Ramos 2006; Khan et al. 2005). It has been suggested that
women respond better to antidepressant treatment because of the modulatory effect of
oestrogen and its interaction with 5-HT (Rubinow et al. 1998). This may explain why
Nathan and colleagues (2006) found a significant effect on the LDAEP slope after an
acute dose of citalopram using a sample comprised of both men and women. Therefore,
gender differences should be considered when investigating the relationship between the
LDAEP and 5-HT function using SSRIs.
In addition to gender differences, divergence of individual responses was found in the
tangential and radial slope. Two individuals seemed to be off the scale (Figure 3-4),
raising the question: are they true outliers or do they reflect inter-individual variability
in the LDAEP response? After careful exploration of the raw data, these participants
did not appear to be outliers for any reasons clear to the author and therefore seem to
reflect variability between participants in the LDAEP response. Further inspection of
the individual responses suggested that participants can be classified as augmenters or
reducers. One limitation of the present experiment is therefore the lack of classification
of participants in term of their LDAEP response. These observations emphasize the
need for more attention to intra-individual responses in future LDAEP research.
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80
Finally, it may be argued that the discrepancy in results can be explained by
polymorphism of the 5-HTT gene. Although the present study did not address this
variable, this possibility should be considered in light of recent literature (Chen et al.
2002; Gallinat et al. 2003; Strobel et al. 2003; see section 2.4. for more details). For
instance, a shallower LDAEP slope was reported in l/l genotype carriers (associated
with high central 5-HT activity) compared to the l/s and s/s carriers (associated with low
central 5-HT activity) (Gallinat et al. 2003). Therefore, it is possible that the
discrepancies between Nathan and colleagues (2006) and the present study may be in
part due to genetic variations across participants.
Although inconsistent with Nathan and colleagues (2006), the present findings are
consistent with other studies that found no change in the LDAEP after treatment with
citalopram (Uhl et al. 2006). Also, after decreasing 5-HT function by ATD, there were
no significant changes in the LDAEP slope (Debener et al. 2002; Dierks et al. 1999;
Massey et al. 2004). Therefore, it would appear that both acute increases or decreases
of serotonergic function in healthy participants do not modify the LDAEP, questioning
the relationship between the LDAEP and 5-HT function. The present investigation also
supports clinical studies that found no significant effect on the LDAEP slope after
treatment with identical SSRIs (i.e. sertraline or citalopram) as those used in the present
investigation (Gallinat et al. 2000). A comparable finding has been reported for the
LDAEP of the auditory P2-slope (Paige et al. 1994) where no effects were found after
four-weeks of treatment with SSRIs. These results suggest that increasing serotonergic
function in patients using SSRIs does not modify the LDAEP slope. The similarity of
the results found in patients and healthy participants using identical SSRIs, further
questions the relationship between the LDAEP and central 5-HT function.
Another purpose of this study was to determine whether there were any differences
between the two analysis methods used (ASF- and DSA slope). Contrary to what has
been argued in the literature (Hegerl et al. 2001; Mulert et al. 2002; Scherg and Picton
1991), the present investigation failed to find any evidence for a greater sensitivity of
the DSA-derived LDAEP to a change in 5-HT function, when compared to the
ASF-derived LDAEP. It should be noted that this was despite using similar
methodology and finding similar DSA sources to those reported in the literature (Hegerl
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81
and Juckel 1993; Hegerl et al. 1994; Scherg and Picton 1991). For example, we found
two dipoles per hemisphere, situated in the A1 and A2 regions that together explained
97.4 % of the variance of the N1/P2 complex (Hegerl and Juckel 1993; Hegerl et al.
1994; 1995; Juckel et al. 1995). This percentage did not differ appreciably between
treatments (placebo: 93.5 %, citalopram: 93.4 %, escitalopram: 93.9 % and sertraline:
94.4 % of the variance). The percentage of variance found in the present study suggests
a good accuracy of the DSA method.
In conclusion, the present investigation failed to replicate previous research in that it did
not find shallower LDAEP slopes after an acute increase of 5-HT function using SSRIs.
This suggests that there is not a relationship between LDAEP and acute enhancement of
5-HT function, at least after acute SSRI administration. In addition, no differences were
found between effects of SSRIs using the ASF- and DSA-derived LDAEP methods.
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Chapter 4
Experiment 2: The Effect of Acute Tryptophan Depletion on
the LDAEP
Chapter 4
83
Introduction
The most convincing evidence of a relationship between the LDAEP and 5-HT function
comes from animal studies (Juckel et al. 1997; 1999), as in healthy humans evidence
supporting the hypothesis of a relationship between the LDAEP and 5-HT function is
less certain. For instance, although Nathan and colleagues (2006) showed a shallower
LDAEP slope in healthy participants after augmenting 5-HT function using acute SSRI
administration, the results presented in chapter 3 failed to replicate these findings. More
work is thus needed to determine the validity of the LDAEP hypothesis. The present
chapter will describe the results of experiments aimed at reducing central 5-HT function
rather than increasing it.
5-HT function can be reduced using a popular non-invasive tool called “acute
tryptophan depletion” (ATD). ATD is a method based on a dietary intervention that
rapidly lowers tryptophan and consequently acutely depletes 5-HT levels and its
metabolites in humans (Carpenter et al. 1998; Nishizawa et al. 1997; Williams et al.
1999) and in animals (Moja et al. 1989). ATD has been reported to be a reliable
non-invasive method to investigate neurophysiological effects following the reduction
of 5-HT (Fusar-Poli et al. 2006). In the ATD methodology, participants ingest an amino
acid (AA) mixture with (balance condition: BAL) or without tryptophan (ATD
condition). Tryptophan depletion is achieved: (1) by increased competition with other
large neutral amino acids (LNAA) for transport into the brain via the blood brain
barrier; (2) by stimulation of protein synthesis requiring tryptophan uptake into the liver
resulting in a further decrease of free plasma tryptophan (Reilly et al. 1997). In humans,
plasma tryptophan levels have been found to decrease as much as 90 % over five to six
hours after ATD (Reilly et al. 1997; Rubia et al. 2005). In another study, the
administration of the ATD mixture reduced 5-HT and 5-HIAA concentrations in the
brain by 27 % and 40 %, respectively, and free and total tryptophan in serum by 67 %
and 75 %, respectively (Gessa et al. 1974). Using brain imaging, this reduction was
found in a variety of brain regions such as temporal, frontal, occipital and parietal
cortex, caudate nucleus, putamen, thalamus, amygdala and hippocampus (Nishizawa et
al. 1997). ATD therefore seems to be a valid method to acutely reduce 5-HT levels in
Chapter 4
84
the human brain (Moore et al 2000; Nathan et al. 2004; Neumeister 2003; Reilly et al.
1997).
Only a few studies have been carried out to investigate LDAEP after ATD, and these
have shown inconsistent results. For instance, while a MEG study reported a shallower
N1m/P2m-slope after ATD (Kahkonen et al. 2002), other studies found no effects on
the LDAEP slope (Debener et al. 2002; Dierks et al. 1999; Massey et al. 2004; Norra et
al. 2004). These conflicting findings may be due to factors such as different amino acid
composition of the ATD drink across studies; while some used a 100 g amino acid
mixture, others used a 50 g amino acid mixture (see section 2.2.1. for details). Animal
studies have reported a correlation between the amount of amino acid administered and
indices of 5-HT function (Moja et al. 1989). Furthermore, a greater reduction of plasma
free tryptophan than the one seen with 50 g mixtures (i.e. 70-75 % decrease; Dierk et al.
1999 and Hughes et al. 2004) has been suggested to be necessary for the effect of ATD
to be observed in humans (Reilly et al. 1997). Therefore, the amount of amino acid
administered may need to be higher than 50 g in order to observe effects on the LDAEP.
The negative findings may also be due to variability between men and women
(Neumeister 2003; Nishizawa et al. 1997) with greater ATD modulation of s5-HT
function reported in women when compared to men (Nishizawa et al. 1997; McBride et
al. 1990), with similar findings in animals (Fischette et al. 1983; Zhang et al. 1999; see
section 2.2.1 for details). It should be noted that women were also reported to have a
higher risk of developing depressive symptoms during ATD relative to men
(Neumeister, 2003). However, no significant change in the LDAEP slope has been
reported in women after ATD (Debener et al. 2002). Despite these negative findings in
women, because of the difference in serotonergic neurotransmission between men and
women, it would seem important to investigate effects of ATD in a homogenous sample
of men or women instead of a mixed sample.
Another criticism of the above-mentioned studies is that the percentage of 5-HT
function decrease (i.e. percentage of ATD) occurring in the brain could not be verified
because the plasma free Trp/LNAA ratio was not included (see section 2.1.1 for details).
The plasma free Trp/LNAA ratio is recognised as a more accurate measure of the
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85
central effect of ATD than the plasma amino acid concentration (Reilly et al. 1997).
Studies investigating the relationship between the LDAEP and 5-HT function should
therefore also include the Trp/LNAA ratio to confirm central tryptophan depletion.
Because of the discrepancies in methodology in the literature, the present study will
further investigate the relationship between the LDAEP and 5-HT function by
decreasing central 5-HT levels via administration of a 100 g amino acid mixture to men
and reporting the Trp/LNAA ratio to confirm the extent of central tryptophan depletion.
Men were used because of the reported risk for women to develop depressive symptoms
during ATD (Neumeister 2003). As per chapter 3, this study will also address any
differences in the LDAEP slope outcomes between the two LDAEP analysis methods
(ASF and DSA). Both methods have been employed in studies on the effect of ATD on
LDAEP (ASF: e.g. Massey et al. 2004; Debener et al. 2002; DSA: e.g. Dierk et al.
1999). As discussed previously (section 1.3.4), the DSA-derived LDAEP method has
been reported to be an important methodological advance over the ASF-derived LDAEP
method (Mulert et al. 2002; Scherg and Picton 1991) because of the separation of the
primary and secondary (represented by the tangential and radial dipole, respectively)
auditory cortices (Hegerl and Juckel 1993; Hegerl et al. 1994; Scherg and Picton 1991).
In conclusion, the aim of the present study is to investigate the effect of ATD on
LDAEP in healthy men using both LDAEP analysis methodologies (DSA and ASF).
Measurement of the plasma free Trp/LNAA ratio will also be reported to confirm
central tryptophan depletion. It was hypothesised that a decrease of central 5-HT
function (using ATD) will result in a steeper LDAEP slope.
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86
4.1. Methods
4.1.1. Participants
Fifty-one non-smoking, adult male participants were recruited for this study using the
same advertising methods as described in section 3.1.1. Of these, only 19 completed
the study, and three were further excluded from the analysis due to poor EEG
recordings. The remaining 16 participants were aged between 20 and 42 years
(Mean = 26.5, SD = 7 years). Participants received $200 for their time, which was paid
upon completion of the study. The exclusion criteria were identical to the ones referred
in section 3.1.1. The study measures and procedure were thoroughly explained to all
participants prior to the beginning of the study and written informed consent was
obtained (Appendix A-2).
4.1.2. Study design
The study was approved by the Swinburne University of Technology Human Research
Ethics Committee. We used a double-blind, placebo-controlled, repeated-measures
design. Each participant underwent the same testing procedures in each testing session.
All participants attended four full-day testing sessions, separated by a minimum 1-week
washout period. The treatment conditions were: (i) 104.4 g nutritionally balanced
control mixture (BAL); (ii) an equivalent mixture deficient in tryptophan (ATD); (iii) an
equivalent mixture deficient in tyrosine and phenylalanine (TPD); and (iv) an equivalent
mixture deficient in tyrosine, tryptophan and phenylalanine (CMD). Only the results
with the BAL and ATD will be reported here (see preface for details).
The timing of the drink administration, 5.5 hrs before EEG recording, was chosen to be
within the timing of maximal tryptophan depletion determined in human plasma (Moja
et al. 1996) and cerebrospinal fluid (Carpenter et al. 1998; Williams et al. 1999). The
treatment administration was randomised and was counterbalanced using a latin square
design (Appendix B-1), to ensure that an equal number of participants were tested under
each drink condition. Participants were tested at the same time of day, for each of the
four testing sessions.
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87
4.1.3. Experimental procedure
Participant screening and pre-experimental procedure
Study applicants were given the study information sheet (Appendix C-2) and if they
agreed to participate in the study, they were pre-screened by telephone by the
experimenter using the same screening procedure as described in section 3.1.3.
Participants then underwent a medical interview (refer to section 3.1.3 for more detail;
Appendix D) and given a numerical identifier, which was used throughout the study to
ensure confidentiality.
Testing day
Two days before the testing session, participants were contacted by telephone to
encourage compliance with the experimental conditions and were requested to adhere to
a low-protein diet for 24 hours (content < 23 g, Young et al. 1985; Appendix G), not to
consume alcohol or caffeinated products and to fast from 7:00 pm the night before the
testing day. Table 4-1 summarises the procedure for each testing session. On each
testing day, participants arrived at 10:00 am at the Brain Sciences Institute, Swinburne
University of Technology, and were asked to complete the Visual Analogue Mood
Scales (VAMS, Appendix E, see section 3.1.3 for more details). Upon completion, a
blood sample was drawn for baseline plasma amino acid concentrations from seven of
the participants. Blood was drawn via venipuncture with a 21-gauge needle directly
into 12 ml Lithium-Heparin tubes. Samples were immediately centrifuged at 3000 rpm
for 10 mins and plasma was separated and stored at -20 °C until analysis. Following the
VAMS and blood sampling, the amino acid mixture (see below) was administered. The
participant was then asked to wait in a quiet room and was offered a standard selection
of magazines of neutral content and allowed to do personal study. The participant was
regularly visited by the experimenter to check whether he was suffering from any side
effects of the treatment. At two hours post-ingestion, the participant was given a low
protein snack (carrot or apple) to minimise any hunger discomfort. Five hours post-
ingestion, a second blood sample was taken, VAMS completed again, and the EEG
recording session commenced. Each EEG recording session lasted for approximately
one hour, with breaks in-between tasks to give instructions to the participant and also
for rest. Upon completion of the testing session, the participant was given high protein
Chapter 4
88
food (chocolate or protein bars) to replete their amino acid balance and to reverse any
effects of ATD. Electrode locations were digitised after the EEG recording. Upon
completion, the EEG cap and the face electrodes were removed, and the participant’s
hair was washed. All participants followed a normal diet between sessions.
Table 4-1: Timeline of experimental procedure for the ATD experiment
Time Protocol
10:00 am Participant arrives, completion of baseline mood rating questionnaire (VAMS 1) + 1st blood sample (if applicable)
T0 (10:30 am) ATD or BAL mixture administration
T+4 ½ hrs (2:30-3 pm) Completion of mood rating questionnaires (VAMS 2) + 2nd blood sample (if applicable)
T+5 hrs (3:00-3:30 pm) EEG set-up
T+5 ½ hrs (3:30 pm) EEG recording starts
T+6 ½ hrs (4:30-5 pm) EEG recording completed, 3Dmap recording, hair washing
Amino acid mixture
The composition of the amino acid mixture was based on the original 100 g balanced
(BAL) suspension developed by Young and colleagues (1985): L-Alanine, 5.5 g;
L-Arginine, 4.9 g; L-Cysteine, 2.7 g; Glycine, 3.2 g ; L-Histidine, 3.2 g ; L-Isoleucine,
8.0 g; L-Leucine, 13.5 g ; L-Lysine monohydrochloride, 11.0 g ; L- Methionine,
3.0 g; L-Phenylalanine, 5.7 g; L-Proline, 12.2 g; L-Serine, 6.9 g; L-Threonine, 6.5 g;
L-Tryptophan, 2.3 g; L-Tyrosine, 6.9 g and L-Valine, 8.9 g. The ATD mixtures was
identical in composition to the BAL mixture, except that it was deficient of
L-Tryptophan. Drinks were prepared just before oral administration by mixing the
amino acid (in powder form) with 180 ml of orange juice. L-Arginine, L-Cysteine,
Chapter 4
89
L-Methionine were administered separately in capsule form due to their unpalatability.
Participants were instructed to swallow the suspension rapidly due to its bitter taste.
4.1.4. Data acquisition
As described in section 3.1.4.
4.1.5. Stimuli
As described in section 3.1.5.
4.1.6. Data analysis
VAMS
As described in section 3.1.6.
ERP Analysis
As described in section 3.1.6.
Dipole Source Analysis (DSA)
The DSA analysis was performed as described in section 3.1.6. Three participants were
excluded from the DSA due to corrupted 3Dmap files. The two dipoles per hemisphere
explained 98.8 % of the variance of the grand average scalp data in the time window of
the N1/P2 complex (68-296 ms).
Scalp topography (ASF) method
As described in section 3.1.6.
DSA and ASF slope estimation
As described in section 3.1.6.
Biochemical Analysis
Plasma samples were thawed at room temperature. One hundred µL of plasma was
diluted 1:1 with internal standard solution and deproteinised by ultrafiltration through a
Chapter 4
90
membrane with a 10 kDa nominal molecular weight cut-off (Ultrafree MC with PL-10
membrane, Millipore, MA, USA). One hundred µL of the resulting filtrate was used to
determine the concentrations of the free amino acids, Trp, Tyr, Phe, Val, Leu, and Ile.
The free amino acid concentration was determined in the filtrates using precolumn
derivatisation with 6-aminoquinolyl-N-hydroxysuccinimidyl carbamate and quantified
by reversed phase high performance liquid chromatography using the Waters AccTag
amino acid analysis system (Waters Corporation, MA, USA) (Cohen 2000). Amino
acids were detected by fluorescence, except for Trp, which required UV detection. Val,
Leu and Ile levels were analysed to calculate the ratio of plasma Trp, Tyr, or Phe, to
other large neutral amino acids (LNAAs).
4.1.7. Statistical analysis
All statistical analyses were performed using SPSS 14 software package for Windows
(SPSS Inc., Chicago, USA). Preliminary analyses were done to determine whether
violations of the assumptions for each statistical test occurred. Differences were
considered statistically significant at p < 0.05.
In order to determine if there was a pre-drug difference between mood for the two
testing sessions, whether there was an effect of the treatment on mood and whether this
interacted with VAMS Factor, a two (Treatment: BAL and ATD) x two (Time: before
and after) x three (Factor: factor 1, factor 2, factor 3) repeated-measures ANOVA was
done.
To determine if there was an effect of stimulus loudness on DSA strength in the placebo
condition, a repeated-measures linear contrast was used where the independent variable
was Stimulus Intensity (60, 70, 80, 90 and 100 dB), and the dependent variable was
‘Tangential strength’ in the placebo condition. In order to determine whether there was
an effect of treatment on the tangential DSA slope and whether any treatment effect
differed between the two hemispheres, a two (Treatment: BAL and ATD) x two
(Hemispheres: left and right) repeated-measures ANOVA was used. As the DSA slopes
were not normally distributed, for all treatment conditions the tangential left slope (TL)
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91
and the tangential right slope (TR) were normalised using t-variable = Log10 (old
variable).
Additionally, four exploratory analyses were performed. Firstly, to determine whether
any of the above effects were general or specific to A1, equivalent analyses to the DSA
analyses described above were done with the radial dipole instead of the tangential.
Since the radial left (RL) and the radial right slope (RR) data did not have normal
distributions, they were normalised using t-variable = Log10 (old variable).
Secondly, to determine whether similar results were found for the ASF slope as were
reported for the DSA slope of the above, the following analyses were done: (a) to
determine whether there was an effect of stimulus loudness on the N1/P2 scalp-derived
amplitude in the placebo condition, a repeated-measures linear contrast was conducted,
where the independent variable was Stimulus Intensity (60, 70, 80, 90 and 100 dB) and
the dependent variable was the N1/P2 complex amplitude; (b) to determine if there was
any effect of the treatment on the ASF slope, a paired-samples t-test was conducted,
where the dependent variable was the ASF slope and the independent variable was
Treatment (BAL and ATD).
Thirdly, to determine how similar the two LDAEP analysis methods were, the following
statistical analyses were done. To determine whether there was a relation between the
ASF and DSA results, a Pearson’s correlation was used comparing the ASF slope and
the DSA slope. Furthermore, to determine whether results derived from ASF or DSA
showed a larger drug effect, a repeated-measures contrast was used, where the
independent variables were Treatment (BAL and ATD) and Methods (TL, TR and
ASF), and the dependent variable was the LDAEP slope. Note that, since DSA slopes
have a different magnitude to ASF slopes, the DSA slope and the ASF slope values
were converted into Z-scores before the repeated-measures contrast was done. The
LDAEP slope was converted to Z-scores across the combined treatment conditions
(BAL and ATD), for the DSA and ASF slopes separately (see section 3.1.7 for details).
Fourthly, to determine whether there was a difference in the amino acid plasma levels in
response to the ATD, a Wilcoxon’s Signed-rank test was done where the independent
variable was the Treatment (BAL and ATD) and the dependent variable was the amino
Chapter 4
92
acid plasma level. Furthermore, to determine whether there was a difference in the
amino acid ratio in response to the ATD, a Wilcoxon’s Signed-rank test was used for
each of the amino acid ratios (i.e. Trp/ΣLNAAs, Tyr/ΣLNAAs, Phe/ΣLNAAs).
Non-parametric tests were used because the amino acid data did not have normal
distributions and could not be normalised.
Chapter 4
93
4.2. Results
VAMS
There was no main effect of Treatment (repeated-measures ANOVA, F(1,15) = 1.41,
p = 0.25, partial η2 = 0.09), no interaction of Treatment-by-Time (F(1,15) = 0.21,
p = 0.654, partial η2 = 0.014), Treatment-by-Factor (F(2,30) = 0.40, p = 0.68, partial
η2 = 0.04), nor Treatment-by-Time-by-Factor (F(2,30) = 0.43, p = 0.66, partial η2 = 0.10).
These results suggest that there was no effect of the treatment on mood, that there were
no pre-existing differences between the sessions in the participant’s mood before
treatment and that treatment and time did not interact with the VAMS factors.
DSA slope
There was a linear increase in the tangential strength across the five stimulus intensities
(repeated-measures linear contrast, F(1,12) = 37.57, p < 0.01, partial η2 = 0.76). There
was no main effect of Treatment (repeated-measures ANOVA, F(1,11) = 0.01, p = 0.93,
partial η2 = 0.03), nor a Treatment-by-Hemisphere interaction (F(1,11) = 0.04, p = 0.95,
partial η2 = 0.35). These results suggest that there was no effect of treatment on the
tangential slope, and that the difference between the two hemispheres did not vary
between BAL and ATD (Figure 4-1). There was no effect of the ATD on the rad-slope
(repeated-measures ANOVA, F(1,11) = 0.75, p = 0.41, partial η2 = 0.06; Figure 4-1), nor
was there a Treatment-by-Hemisphere interaction (F(1,11) = 6.63, p = 0.29, partial
η2 = 0.036).
Chapter 4
94
Figure 4-1: DSA of LDAEP data in the balance (BAL) and acute tryptophan depletion (ATD) conditions, shown for the left and right tangential (top
panels) and radial (bottom panels) dipoles. A Scatter graph of individual data. B Box-and-whiskers plot of the LDAEP percentiles, N = 13.
A B
Chapter 4
95
ASF slope
The increasing loudness of the auditory stimuli led to increasing amplitudes of the
N1/P2 complex (Figures 4-2 and 4-3). There was a linear increase in the N1/P2
complex amplitude across the five stimulus intensities (repeated-measures linear
contrast, F(1,15) = 68.18, p < 0.01, partial η2 = 0.82, Figure 4-2). No significant
difference in the ASF slope between BAL and ATD was found (t-test, t(15) = - 1.12,
p = 0.28, η2 = 0.24).
The exploratory analysis revealed two further findings. First, there was no significant
correlation between the ASF and DSA analysis methods (Pearson correlation analysis,
r = 0.15, p = 0.49); only 15 % of the variance in the DSA values could be explained by
the variance in the ASF values. Second, there was no difference between the
drug-effects derived from the DSA and ASF methods (repeated-measures ANOVA,
F(1,11) = 0.68, p = 0.43).
0
4
8
12
16
20
24
BALATD
60 70 80 90 100
Stimulus intensity (dB SPL)
N1/
P2 a
mpl
itude
( µV
)
Figure 4-2: Mean N1/P2 amplitude plotted against stimulus intensity for the balance (BAL) and acute tryptophan depletion (ATD) conditions, N = 16.
Chapter 4
96
Figure 4-3: Grand mean ERPs at Cz of three intensities of auditory stimulus (i.e. 60, 80 and 100 dB), following the balance (BAL) and acute tryptophan depletion (ATD)
conditions, N = 16.
BAL conditionATD condition
0
-5
-10
5
10
0
-5
-10
5
10
ms-100 0 100 200 300 400
0
-5
-10
5
10
Am
plitu
de (µ
V)
60 dB
80 dB
100 dB
Stimulus
BAL conditionATD condition
0
-5
-10
5
10
0
-5
-10
5
10
0
-5
-10
5
10
0
-5
-10
5
10
ms-100 0 100 200 300 400
0
-5
-10
5
10
0
-5
-10
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10
Am
plitu
de (µ
V)
60 dB
80 dB
100 dB
Stimulus
Chapter 4
97
Figure 4-4: ASF of LDAEP data in the balance (BAL) and acute tryptophan depletion (ATD) conditions. A: Scatter graph of individual data. B: Box-and-whiskers plot of ASF slope
percentiles, N = 16.
Amino acid plasma measures
Following the administration of the BAL drink, all concentrations of the six amino acids
(Trp, Tyr, Phe, Leu, Ile and Val) increased significantly compared to baseline. After
administration of the ATD drink, there was a significant decrease in the concentration of
Trp, a significant increase in the concentration of Phe and no significant change in the
concentration of the other amino acid (for percentage see Table 4-3). There was a
significant effect of the BAL drink on the plasma levels of the amino acids (Wilcoxon’s
Signed-rank tests, z = - 2.37; p = 0.02 for Trp, Tyr, Phe, Leu, Ile and Val respectively).
There was a significant effect of the ATD drink on the tryptophan plasma levels
(Wilcoxon’s Signed-rank, z = - 2.37; p = 0.02) and on the Phe plasma levels (z = - 2.20;
p = 0.03). Finally, there was no significant effect of the ATD drink on the other plasma
levels (z = - 1.18; p = 0.24 for Tyr and Val respectively and z = - 1.35; p = 0.18 for Ile
and Leu respectively).
As expected, after ATD the greatest change in the ratio of amino acid vs the combined
LNAAs was seen for tryptophan (93%), even though statistically this decrease only
reached trend level (ratio of Trp: ∑LNAAs, z = - 1.73, p = 0.08). There was a
significant decrease in the ratio of Tyr: ∑LNAAs (Wilcoxon’s Signed-rank tests,
z = - 2.37; p = 0.02), but no significant change in Phe: ∑LNAAs (z = - 0.32; p = 0.07),
when compared to baseline amino acid ratios (for percentage see Table 4-3).
Chapter 4
98
Baseline and 4.5hrs post-treatment values indicate: mean (SEM). BAL = balance condition, ATD = acute tryptophan depletion condition. N = 7. * p < 0.05 indicates significant change from baseline to 4.5 hrs post-treatment for both BAL and ATD conditions.
Table 4-2: Results for plasma concentrations of amino acids (µmol/L) for baseline and 4.5 hrs following ATD treatment
-0.318 (0.750)-1.40.140 (0.036)0.142 (0.034)ATD
-1.951 (0.051)-25.50.110 (0.035)0.148 (0.021)BALPhe/∑LNAAs
-1.342 (0.180)-93.30.011 (0.004)0.016 (0.005)ATD
-1.732 (0.083)-20.00.015 (0.004)0.016 (0.008)BALTrp/∑LNAAs
-1.581 (0.114)-19.10.129 (0.057)0.16 (0.030)ATD
-2.371 (0.018)*-32.70.109 (0.024)0.16 (0.031)BALTry/∑LNAAs
-2.366 (0.018)*-84.30.8 (0.23)5.1 (1.6)ATD
-2.371 (0.018)*141.610.9 (3.4)4.5 (1.9)BALPlasma Trp
-2.197 (0.028)*127.3114.4 (52.3)50.3 (14.5)ATD
-2.366 (0.018)*126.3101.7 (43.9)45.0 (9.3)BALPlasma Phe
-1.352 (0.176)147.7234.0 (101.3)94.5 (84.7)ATD
-2.366 (0.018)*273.8241.8 (46.5)64.7 (6.0)BALPlasma Leu
-1.352 (0.176)130.5133.0 (60.3)57.7 (52.0)ATD
-2.366 (0.018)*267.3139.6 (26.6)38.0 (4.1)BALPlasma Ile
-1.183 (0.237)88.6251.9 (140.8)133.5 (100.4)ATD
-2.366 (0.018)*203.2300.8 (28.3)99.2 (9.5)BALPlasma Val
-1.183 (0.237)47.796.7 (36.6)65.5 (46.8)ATD
-2.366 (0.018)*98.697.4 (27.3)49.1 (11.4)BALPlasma Tyr
Wilcoxon Signed rank testZ (p)
Per Cent Change4.5hrs Post TreatmentBaselineTreatment
ConditionAmino Acid
-0.318 (0.750)-1.40.140 (0.036)0.142 (0.034)ATD
-1.951 (0.051)-25.50.110 (0.035)0.148 (0.021)BALPhe/∑LNAAs
-1.342 (0.180)-93.30.011 (0.004)0.016 (0.005)ATD
-1.732 (0.083)-20.00.015 (0.004)0.016 (0.008)BALTrp/∑LNAAs
-1.581 (0.114)-19.10.129 (0.057)0.16 (0.030)ATD
-2.371 (0.018)*-32.70.109 (0.024)0.16 (0.031)BALTry/∑LNAAs
-2.366 (0.018)*-84.30.8 (0.23)5.1 (1.6)ATD
-2.371 (0.018)*141.610.9 (3.4)4.5 (1.9)BALPlasma Trp
-2.197 (0.028)*127.3114.4 (52.3)50.3 (14.5)ATD
-2.366 (0.018)*126.3101.7 (43.9)45.0 (9.3)BALPlasma Phe
-1.352 (0.176)147.7234.0 (101.3)94.5 (84.7)ATD
-2.366 (0.018)*273.8241.8 (46.5)64.7 (6.0)BALPlasma Leu
-1.352 (0.176)130.5133.0 (60.3)57.7 (52.0)ATD
-2.366 (0.018)*267.3139.6 (26.6)38.0 (4.1)BALPlasma Ile
-1.183 (0.237)88.6251.9 (140.8)133.5 (100.4)ATD
-2.366 (0.018)*203.2300.8 (28.3)99.2 (9.5)BALPlasma Val
-1.183 (0.237)47.796.7 (36.6)65.5 (46.8)ATD
-2.366 (0.018)*98.697.4 (27.3)49.1 (11.4)BALPlasma Tyr
Wilcoxon Signed rank testZ (p)
Per Cent Change4.5hrs Post TreatmentBaselineTreatment
ConditionAmino Acid
Chapter 5
99
4.3. Discussion
The present study aimed to examine the effects of acute serotonin depletion using ATD
on the LDAEP slope in healthy participants, and to compare the DSA and ASF methods
of estimating the LDAEP. In line with the most of the literature, the present results
failed to find an effect of ATD on the LDAEP. Furthermore, no differences were found
between the DSA and ASF methods of calculating the LDAEP.
In the present study acute tryptophan depletion resulted in an 84 % decrease in the
plasma tryptophan concentration and a 93 % decrease in the ratio of tryptophan to other
LNAAs, a decrease which is considered to affect central 5-HT function (Carpenter et al.
1998; Nishizawa et al. 1997; Williams et al. 1999). In spite of this decrease, no effects
on LDAEP slope were observed. These findings are consistent with a number of other
studies which have found no significant difference in the LDAEP slope after ATD
(Debener et al. 2002; Dierks et al. 1999; Massey et al. 2004; Norra et al. 2004).
Interestingly, in a recent MEG study, the effect of tryptophan depletion decreased the
N1m/P2m slope in healthy participants (Kahkonen et al. 2002). As was suggested in
the introduction of the present chapter, it is possible that these discrepant results may be
explained by genders differences. Indeed, some studies used only male participants
(Massey et al. 2004), including the present study, while other studies used only women
(Debener et al. 2002, Norra et al. 2004) or men and women (Dierk et al. 1999;
Kahkonen et al. 2002). Recent ATD studies in healthy participants have found a high
variability between men and women (for review see Neumeister 2003), with women
generally showing a greater effect of ATD (Nishizawa et al. 1997), however the ASF
slope was not altered in women (Debener et al. 2002; Norra et al. 2004).
Furthermore, as discussed in chapter 3, divergence of individual responses was found in
the tangential and radial slope. One individual seemed to be off the scale (Figure 4-1).
After investigation of the raw data, this participant did not appear to be an outlier and
therefore seems to reflect variability between participants in the LDAEP response.
Inspection of the individual responses again suggested that participants can be classified
as augmenters or reducers confirming the need for more attention to intra-individual
responses in LDAEP research.
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Another possible explanation for the lack of effect of ATD on LDAEP slope in the
present study and in the literature may be from a potential problem of the ATD
technique. Tyrosine competes for the same amino acid transporter as tryptophan,
therefore, decreasing tryptophan may increase tyrosine transport through the blood brain
barrier and potentially increase dopamine levels (Cooper et al. 1996). Consistent with
this, early studies reported a correlation of steeper LDAEP slopes with low levels of
dopamine metabolites (Bruneau et al. 1986; Bruneau et al. 1987). A single photon
emission computed tomography study found a correlation between LDAEP and both
5-HTT binding and striatal dopamine transporter binding (Pogarell et al. 2004).
Previously, a shallow LDAEP slope was reported after administration of the D1/D2
receptor agonist, apomorphine, in animals (Juckel et al. 1997). Therefore, it may be
possible that ATD in the current study resulted in an indirect activation of dopamine
function, leading to a counterbalanced effect on the LDAEP slope. On the other hand,
administration of the dopamine receptor agonists, pergolide or bromocriptine, to healthy
participants had no effect on LDAEP (O’Neill et al. 2006a). Moreover, while in the
present study a large decrease in the ratio of tryptophan to other LNAAs was found, the
decrease in the tyrosine ratio to other LNAAs was small, suggesting that the ATD
technique affected mostly the 5-HT system. Finally, as an extension to the present
experiment and in the same group of participants, we failed to observe an effect of the
tyrosine/phenylalanine depletion and combined tryptophan/tyrosine/phenylalanine
depletion on the ASF-derived LDAEP slope (O'Neill et al. 2006b; Appendix H).
Therefore, it seems unlikely that the results of the present study are linked to a possible
action of dopamine on the LDAEP.
Further, one may wonder about the power of the relevant statistical test to detect a
difference in the DSA-derived LDAEP analysis method, if there truly was one. In the
present chapter, post-hoc power analysis of our design found a power of 0.05
(calculated using G*Power 3.0.3, Concept and design, Universität Kiel, Germany; Faul
and al. 2007) to detect a small effect size (η2 = 0.03) in the DSA-derived analysis.
Therefore, the probability is 0.05 that there is no effect or that if there is an effect it is
small. This is suggesting that the present study has no power to detect a difference after
acute tryptophan depletion in the DSA. Such a result is not surprising considering that
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the ANOVA in the DSA-derived analysis in the present chapter resulted in a p value of
0.9 and an effect size of 0.03.
This study also determined whether there was a difference in DSA and ASF. Contrary
to the literature, (Hegerl et al. 2001; Mulert et al. 2002; Scherg and Picton 1991), any
greater sensitivity of the DSA-derived LDAEP to changes in serotonergic function
when compared to the ASF-derived LDAEP could not be found in the present
investigation. The negative findings of the present investigation support the findings of
chapter 3 that showed no difference between the DSA-derived and the ASF-derived
analyses. In line with chapter 3, 98.8 % of the variance of the N1/P2 complex was
explained in the basic dipole model, which did not differ appreciably between treatment
conditions (BAL: 93.4 %, ATD: 93.5 % of the variance).
In conclusion, the present study results support previous research (Debener et al. 2002;
Dierks et al. 1999; Massey et al. 2004; Norra et al. 2004), in that it did not find a steeper
LDAEP slope after acute decrease of 5-HT function using ATD. This finding does not
support a relationship between LDAEP and an acute decrease of 5-HT function. In
addition, no differences were found between the effects of ATD on the ASF-derived and
DSA-derived LDAEP methods.
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Chapter 5
Experiment 3: The Effect of the 5-HT1A Receptor Agonist
Buspirone on the LDAEP
Chapter 5
103
Introduction
In the previous chapters, no change in the LDAEP slope was found after acute increases
of 5-HT function induced by treatment with SSRIs (Chaper 3) or a decrease of 5-HT
function induced by acute tryptophan depletion (Chapter 4) using either the DSA or
ASF analysis methods. Therefore, neither augmentation nor reduction of 5-HT function
was found to affect LDAEP, suggesting that LDAEP is not a good marker of central
5-HT function as previously suggested in the literature (Hegerl and Juckel 1993).
However, this conclusion appears to be inconsistent with the clinical literature which
has demonstrated a relationship between the LDAEP and psychiatric disorders known to
be related to 5-HT dysfunction, such as depression (Buchsbaum et al., 1971; Stahl
1994), generalized anxiety disorder (Senkowski et al., 2003; Waugh and Goa 2003) and
schizophrenia (Burnet et al. 1997; see section 2.3.1 for more details).
Depression is associated with reduced expression of 5-HT1A receptors and increased
expression of 5-HT2A receptors (see Mann 1999 for review), and a corresponding
decrease in 5-HT1A receptor-mediated effects (Blier et al. 1990). Specifically, PET
studies in depressed patients have revealed a decrease in 5-HT1A receptor binding in the
raphe nuclei (Drevets et al. 2000; Meltzer et al. 2004; Sargent et al. 2000). 5-HT1A
receptors may also contribute to the therapeutic effects of antidepressants (Blier and de
Montigny 1994; McAllister-Williams and Young 1998). Chronic SSRI treatment
resulted in functional desensitisation and down-regulation of 5-HT1A autoreceptors
leading to an increase in 5-HT transmission at the postsynaptic level (Chaput et al.
1986, Hensler 2003). Schizophrenia has also been related to a dysfunction of 5-HT1A
receptors, where post-mortem studies have reported a 60-70 % increase in 5-HT1A
receptor density in the hippocampus, raphe nuclei and cortical regions (Burnet et al.
1997).
Based on these findings of impaired 5-HT1A receptor function in psychiatric illnesses, it
is possible that the relationship between LDAEP and 5-HT function may be related
more specifically to the 5-HT1A receptor than to a global change of central 5-HT
function as suggested by Hegerl and colleagues (1993). Little is known about the
relationship between the LDAEP and 5-HT1A receptors. Such a relationship is possible
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based on the thesis that EEG generators are produced by ionic currents generated by
pyramidal cells (see section 1.2.2.b for more details). In vivo and in vitro studies have
suggested that 5-HT1A and 5-HT2A receptors are key players, that exert opposite effects
on the excitability and firing activity of pyramidal neurons, where 5-HT1A receptors
hyperpolarise pyramidal neurons and 5-HT2A receptors depolarise pyramidal neurons.
This hyperpolarisation or depolarisation of a group of pyramidal cells is believed to
contribute to ERP, including LDAEP (see section 1.2.2.b).
It is possible that the discrepancy between the present SSRI results and the clinical
LDAEP literature may be due to the differential action of acute and chronic SSRI
treatment on 5-HT1A receptor function. The negative results in chapter 3 could be due
to the normally delayed onset of antidepressants efficacy (between two to four weeks),
which corresponds to the time it takes for down-regulation of 5-HT1A receptors to occur.
Acute increases of 5-HT function by SSRI treatment, as in the study in chapter 3, may
affect multiple 5-HT receptor subtypes. In view of the opposite role of 5-HT1A and
5-HT2A receptors in cortical excitation, the net effect of such a generalized increase may
therefore be zero. Only down-regulation of 5-HT1A receptors by chronic SSRI treatment
unmasks 5-HT modulation of LDAEP. Similarly, it is possible that the lack of effects
of ATD on the LDAEP slope reported in chapter 4 and in the ATD/LDAEP literature
(see section 2.2.1 and chapter 4 for more details), may be related to a lack of a specific
effect on postsynaptic 5-HT1A receptor function.
5-HT1A receptor modulation has been reported to modify the LDAEP slope in animals
(Juckel et al. 1997, 1999; Manjarrez et al. 2005). Specifically, systemic or intra-raphe
administration of the 5-HT1A receptor agonist, 8-OH-DPAT, resulted in a shallower
LDAEP slope (Juckel et al. 1997, 1999). However, similar studies have not been done
in humans. The present chapter therefore aims to further investigate the relationship
between LDAEP and 5-HT1A receptors by testing the effect of the 5-HT1A receptor
partial agonist, buspirone. Buspirone is an azapirone derivative anxiolytic (Figure 5-1),
which displays a high affinity for 5-HT1A receptors (IC50 = 24 nM; Peroutka 1985).
Buspirone inhibits firing of 5-HT cells in the DRN via activation of 5-HT1A
autoreceptors (Van der Maelen et al. 1986) and decreases extracellular concentrations of
5-HT in the DRN. Therefore, it is hypothesised that buspirone, through its specific
Chapter 5
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5-HT1A autoreceptor action, will decrease 5-HT function sufficiently to produce a
steeper LDAEP slope.
Further, as in chapters 3 and 4, this study will compare the different LDAEP analysis
methods, ASF and DSA.
Figure 5-1: Structure of buspirone
Chapter 5
106
5.1. Methods
5.1.1. Participants
Fifty-six non-smoking adult female participants were recruited for this study using the
same advertising methods as described in section 3.1.1. In contrast to the studies
described in chapters 3 and 4, only women were used in this study because oestrogen
was given to participants (see preface) and could not be given to men to limit any
possible side effects. Of the female participants, only 16 participants completed the
study, and these were aged between 20 to 38 years (Mean = 25.3, SD = 6 years).
Participants received $200 for their time, which was paid upon completion of the study.
The exclusion criteria were identical to the ones described in section 3.1.1. In addition,
participants were excluded from the study if they reported taking any hormone
replacement medication, such as the oral contraceptive pill, if they reported an irregular
menstrual cycle, or if they were pregnant or lactating. The study measures and
procedure were well explained to all participants prior to the beginning of the study and
written informed consent was obtained (Appendix A-3).
5.1.2. Study design
The present study was approved by the Swinburne University of Technology Human
Research Ethics Committee. This study used a double-blind, placebo-controlled,
repeated-measures design. Each participant underwent the same testing procedures in
each recording session. All participants attended four full-day testing sessions and each
was tested within ten days of the onset of menstruation (Mean = 5.0, SD = 2.82,
range = 0-14 days) i.e. during the follicular phase of their menstrual cycle when
oestrogen levels are low (Figure 5-2). Participants were tested at this stage of the
menstrual cycle, because oestrogen levels have been found to alter the central
processing of auditory information (Yadav et al. 2002, 2003).
Chapter 5
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Testing period
Figure 5-2: Schematic representation of ovulatory menstrual cycles of the reproductive hormones and testing period (modified from Papanicolaou et al. 1948).
Testing sessions were separated by a washout period of at least 1-week. The treatment
conditions were: (i) placebo/placebo (flour and gelatine) and (ii) placebo/buspirone
(Buspar®, 5 mg; Bristol Myers Squibb Company, Noble Park, Vic, Australia); (iii)
oestradiol/placebo, and (iv) oestradiol/buspirone. The treatment conditions (iii) and (iv)
are not reported in this thesis (see preface for details). For blinding purposes, all tablets
were enclosed within a gelatine capsule, filled with plain flour, giving equivalent
appearance for each condition.
The dose for buspirone was selected based on previous studies in humans. For instance,
5 mg of buspirone significantly reduced skin conductance response in women
(Hellewell et al. 1999) and induced a decrease in plasma 5-HT and 5-HIAA
concentrations and anxiety scores (Mizuki et al. 1994). The 5 mg dose in the present
study was lower than the clinical recommended dose (i.e. 15 mg; MIMS 2004) to
prevent side effects (Lechin et al. 1998).
The timing of the drug administration, one hour before recording, was chosen to be
within the range of the peak plasma level for buspirone (tmax = 0.7 hr ± 0.15, Dalhoff et
E2 = oestrogen; LH = luteinizing hormone; FSH = Follicle stimulating hormone
Chapter 5
108
al. 1987). Treatment administration was counterbalanced and randomised using a latin
square design (Appendix B), to ensure that an equal number of participants were tested
under each treatment conditions. Participants were tested at the same time of day, for
each of the four testing sessions.
5.1.3. Experimental procedure
Participant screening and pre-experimental procedure
Study applicants were given the information sheet (Appendix C-3) and if they agreed to
participate in the study, they were pre-screened by telephone by the experimenter using
the same screening procedure described in section 3.1.3. Participants then underwent a
medical interview (Appendix D; refer to section 3.1.3 for more details) and were given a
numerical identifier, which was used throughout the study to ensure confidentiality. In
addition, menstrual cycle dates were noted to determine the length of the participant’s
cycle and schedule the dates of future recording sessions.
The day before the testing session, participants were contacted by phone to encourage
compliance with the experimental conditions, were requested not to consume alcohol or
caffeinated products for 24 hours prior to testing, and were asked to consume a light
breakfast (e.g. toast and fruit) the following morning (testing day).
Testing day
Table 5-1 summarises the procedure for each testing session. One or two participants
were tested per day and the time of the testing session was kept the same for the four
sessions for each participant. On each testing day, participants arrived at 9:30 am (or
11:30 am) at the Brain Sciences Institute, Swinburne University of Technology. At
10 am (or 12 pm) they were administered the first treatment (placebo or oestradiol).
The participant was then asked to wait in a quiet room and was offered a standard
selection of magazines of neutral content and allowed to do personal study for three
hours. The participant was regularly visited by the experimenter to check whether she
was suffering from any side effects. One and a half hours after the first treatment, the
participant was given a tryptophan-free lunch (rice crackers and jam, orange juice and
an apple). At 1 pm (or 3 pm), i.e. 3 hours after the first treatment, the participant was
Chapter 5
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administered the second treatment (placebo or buspirone). The participant was then
set-up for the EEG recording. Participants were asked to complete the VAMS (Bond
and Lader 1974; see section 3.1.3 and Appendix E) and then EEG recording started (one
hour after the second treatment administration). Each EEG recording session lasted for
approximately one hour, with breaks in between tasks to give instructions to the
participant and also for rest. Electrode locations were digitised after the EEG recording
(as described in Chapter 3). Upon completion of the testing session, the EEG cap and
the face electrodes were removed and the participant’s hair was washed.
Table 5-1: Timeline for experimental procedure for the buspirone experiment
TIME ACTIVITY
9:30 am 11:30 am Participant arrives at BSI
T0 (10 am) T0 (12 pm) First treatment administration (placebo or oestradiol)
T+1 ½ h (11:30 am) T+1 ½ h (1:30 pm) Lunch
T+3 hrs (1-1:45 pm) T+3 hrs (3-3:45 pm) Second treatment administration (placebo or buspirone) and EEG set-up
T+3 ¾ hrs (1:45-2 pm) T+4 ¾ hrs (3:45-4 pm) Completion of mood rating questionnaires (VAMS)
T+4 hrs (2 pm) T+4 hrs (4 pm) EEG recording starting
T+5 hrs (3 pm) T+5 hrs (5 pm) EEG recording completed, 3Dmap recording, hair washing
5.1.4. Data acquisition
The equipment used and the recording conditions were the same as described in the
chapters 3 and 4 (see section 3.1.4 for details), with an exception being that the cap used
in the present study had 61 EEG scalp sites at locations based on the International 10/20
recording system (Quik-Caps, NeuroScan Inc, Sterling, VA, USA). All channels were
recorded relative to the left mastoid. As part of prepulse inhibition experiments (data
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not shown here) and EOG correction, four additional electrodes were employed: a
bipolar montage (EMG1 and EMG2) below the right eye to record electro-myographic
activity, and monopolar recordings from electrodes below (E3) the left eye to record eye
movement activity (electro-oculogram, EOG), and on the nose. EEG was continuously
recorded, digitised at 2000 Hz and filtered using a 0.05-500 Hz band-pass filter.
5.1.5. Stimuli
The stimulus order presentation was the same as described previously (see section 3.1.5
for details; Appendix F). The ‘distractor’ task in this study was different from the
previous studies and involved participants being instructed to look at the screen and
press a keypad when a complete, 4-sided square flashed up onto the screen (as opposed
to a 3-sided, incomplete square). These appeared on average every 10.5 s, with a range
of 1-21 s.
5.1.6. Data analysis
VAMS
As described in section 3.1.6.
ERP Analysis
In this study, N1 and P2 amplitudes were calculated as the minimum (N1) and
maximum (P2) amplitude (relative to baseline) in the 80-140 ms and 110-240 ms time
windows, respectively.
Dipole source analysis (DSA)
The DSA analysis was performed as described in section 3.1.6. One participant was
excluded due to a corrupted 3Dmap file. The two dipoles per hemisphere explained
95.83 % of the variance of the grand average scalp data in the time window of the
N1/P2 complex (27-244 ms).
Scalp topography (ASF) method
As described in section 3.1.6.
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DSA and ASF slope estimation
As described in section 3.1.6.
5.1.7. Statistical analysis
All statistical analyses were performed using the SPSS 14 software package for
Windows (SPSS Inc., Chicago, USA). Preliminary analyses were done to determine
whether violations of the assumptions for each statistical test occurred. Differences
were considered statistically significant at p < 0.05.
To determine if there was an effect of the drug on mood and to determine whether this
interacted with VAMS Factor, a two (Treatment: placebo and buspirone) x three
(Factor: factor 1, factor 2 and factor 3) repeated-measures ANOVA was performed.
To determine if there was an effect of stimulus loudness on DSA strength in the placebo
condition, a repeated-measures linear contrast was used where the independent variable
was Stimulus Intensity (60, 70, 80, 90 and 100 dB) and the dependent variable was
‘Tangential strength’ (i.e. mean for the tangential right dipole (TR) strength and the
tangential left dipole (TL) strength) in the placebo condition.
In order to determine whether there was an effect of treatment on the tangential DSA
slope and whether any treatment effect differed between the two hemispheres, a two
(Treatment: placebo and buspirone) x two (Hemispheres: left and right)
repeated-measures ANOVA was used. As the DSA slope values were not normally
distributed, for each treatment condition the tangential left slope (TL) and the tangential
right slope (TR) were transformed using t-variable = [square root (old variable + 0.70)].
Following each significant result, post hoc t-tests were conducted with Bonferroni
corrections.
Additionally, three exploratory analyses were performed. Firstly, to determine whether
any of the above effects were general or specific to A1, equivalent analysis to the DSA
analyses described above were done with the radial dipole (Rad) slope instead of the
tangential. Since, the radial left (RL) and the radial right slope (RR) data did not have
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normal distributions, they were transformed using t-variable = [square root
(old variable + 0.70)].
Secondly, in order to determine whether similar results were found for the ASF slope as
were reported for the DSA slope above, the following analyses were done: (a) to
determine whether there was an effect of stimulus loudness on the N1/P2 scalp-derived
amplitude in the placebo condition, a repeated-measures linear contrast was conducted,
where the independent variable was Stimulus Intensity (60, 70, 80, 90 and 100 dB) and
the dependent variable was the N1/P2 complex amplitude; (b) in order to determine if
there was any effect of the treatment on the ASF slope, a paired-samples t-test was
conducted, where the dependent variable was the ASF slope and the independent
variable was Treatment (placebo and buspirone).
Thirdly, in order to determine how similar the two LDAEP analysis methods were, the
following statistical analyses were performed: (a) to determine whether there was a
relation between the ASF and DSA results, a Pearson’s correlation was performed
comparing the ASF slope and the DSA slope; (b) to determine whether results derived
from ASF or DSA showed a larger drug effect, a repeated-measures ANOVA was
performed, where the independent variables were Treatment (placebo and buspirone)
and Method (TL, TR and ASF), and the dependent variable was the LDAEP slope.
When significant, contrasts were performed comparing ASF to the mean of TR and TL
strength, as well as comparing TL to TR strength. Note that since DSA slopes have a
different magnitude to ASF slopes, the DSA slope and the ASF slope values were
converted into Z-scores before the repeated-measures contrast was performed. The
LDAEP slopes were converted to Z-scores across the combined treatment conditions
(placebo and buspirone), for the DSA and ASF slope separately (see section 3.1.7. for
details).
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5.2. Results
VAMS
There was no main effect of Treatment (repeated-measures ANOVA, F(1,15) = 0.02;
p = 0.88; partial η2 = 0.001), nor Treatment x Factor interaction (F(2,14) = 1.17; p = 0.34;
partial η2 = 0.14). These results suggest that there was no effect of the treatment on
mood and that treatment did not interact with the VAMS factors.
DSA slope
There was a linear increase in the tangential strength across the five stimulus intensities
(repeated-measures linear contrast, F(1,14) = 66.21, p < 0.01, partial η2 = 0.83). There
was a significant main effect of Treatment (repeated-measures ANOVA, F(1,14) = 8.24;
p = 0.012, partial η2 = 0.37). However, there was no significant
Treatment-by-Hemisphere interaction (F(1,14) = 0.69, p = 0.42, partial η2 = 0.05). These
results suggest that buspirone increased the tang-slope, and that the effect of buspirone
on tang-slope was not different between the two hemispheres (Figure 5-3, Table 5.2).
There was no effect of treatment on the rad-slope (repeated-measures ANOVA,
F(1,14) = 1.40, p = 0.267, partial η2 = 0.09) and there was no significant
Treatment-by-Hemisphere interaction (F(1,14) = 0.08; p = 0.78, partial η2 = 0.01,
Figure 5-3).
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Figure 5-3: DSA of LDAEP data in the placebo (PLAC) and buspirone (BUSP) condition, shown for the left and right tangential (top panels) and radial (bottom panels) dipoles. A Scatter graph of individual data. B Box-and-whiskers plot of the LDAEP percentiles, N = 15.
t-tests # p < 0.01 and * p < 0.05, compared to the placebo condition.
A B
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ASF slope
The increasing loudness of the auditory stimuli led to increasing amplitudes of N1/P2
complex (Figure 5-5). There was a linear increase in the N1/P2 complex amplitude
across the five stimulus intensities (repeated-measures linear contrast, F(1,15) = 66.50;
p < 0.01; partial η2 = 0.82) (Figure 5-4).
0
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60 70 80 90 100
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Figure 5-4: Mean N1/P2 amplitude plotted against stimulus intensity for the placebo (PLAC) and buspirone (BUSP) conditions, N = 16.
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Figure 5-5: Grand Mean ERPs at Cz of three intensities of auditory stimulus (i.e. 60, 80 and 100 dB), following treatment with placebo and buspirone, N = 16.
100 dB
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There was no significant difference in the ASF slope between placebo and buspirone
(t-test, t(15) = - 0.71; p = 0.500; η2 = 0.17). ASF slope means (SEM) for placebo and
buspirone were 0.41 (0.046) and 0.44 (0.047), and ranges were 0.07-0.76 and 0.14-0.82,
respectively (Figure 5-6).
Figure 5-6: ASF of LDAEP data in the placebo (PLAC) and buspirone (BUSP)
conditions. A: Scatter graph of individual ASF slope. B: Box-and-whiskers plot of LDAEP percentiles, N = 16.
The exploratory analysis revealed two further findings. First, there was no significant
correlation between the ASF and DSA methods (Pearson correlation analysis, r = - 0.16,
p = 0.39); only 16 % of the variance in the DSA values could be explained by the
variance in the ASF values. Second, there was a significant difference between the drug
effects derived from the DSA and ASF methods (repeated-measures ANOVA,
F(2,28) = 4.93; p = 0.02; partial η2 = 0.27). Repeated-measures contrasts found a
significant difference between the ASF slope and the averaged TL and TR slopes
(F(1,14) = 8.70; p = 0.01; partial η2 = 0.21), whereas there was no significant difference
between TL and TR slopes (F(1,14) = 0.72; p = 0.41; partial η2 = 0.05). This indicates a
difference between the DSA and ASF methods, but no difference between the two
hemispheres in the DSA method.
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5.3. Discussion
The present study aimed to examine the effects of 5-HT1A receptor modulation using the
5-HT1A receptor agonist buspirone, on the LDAEP slope, and to compare the DSA and
ASF methods for estimating the LDAEP slope. The present study found that acute
administration 5 mg of buspirone significantly decreased the LDAEP slope from the
primary auditory cortex but not from the secondary auditory cortex. Furthermore, this
effect was found with the DSA but not with the ASF method of calculating the LDAEP
slope. These results are consistent with the animal literature (Juckel et al. 1999), which
also reports a change of LDAEP after activation of 5-HT1A receptors. For example, a
steeper LDAEP slope was reported following local application of 8-OH-DPAT into the
DRN of freely-moving cats (Juckel et al. 1999) while a shallower LDAEP slope was
reported following systemic administration of 8-OH-DPAT (Juckel et al. 1997).
The steeper LDAEP slope found in the present chapter after acute administration of
buspirone is likely to represent reduced central serotonergic function caused by
activation of 5-HT1A receptors. An acute dose of buspirone in rats reduces
5-HT synthesis throughout the brain (Okazawa et al. 1999) and completely inhibits
DRN firing (Van der Maelen et al. 1986), likely by its action on 5-HT1A autoreceptors.
In the same healthy participants as used for the measurement of LDAEP in the present
chapter, buspirone treatment resulted in a disruption of prepulse inhibition of the
acoustic startle response, a measure of sensory processing (Gogos et al. 2006). This
would suggest that activation of 5-HT1A autoreceptors using this relative low dose of
buspirone is potent enough to reduce 5-HT neuronal firing and modulate cortical
activity and the LDAEP slope.
Buspirone is clinically used as an anxiolytic drug with its anxiolytic effects suggested to
be mediated by hippocampal postsynaptic 5-HT1A receptors (Stefanski et al. 1993).
Therefore, the present study results could be influenced by an anxiolytic effect of
buspirone; however, this is unlikely as VAMS results suggest that there was no effect of
the treatment on mood. It should be noted that while buspirone is known as a partial
5-HT1A receptor agonist, at higher doses it has also been reported to have dopamine D2
receptor antagonistic properties (Tunnicliff 1991). Buspirone also increases firing in
the locus ceruleus via indirect agonist activity at noradrenergic neurons (Lechin et al.
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1998). Therefore, one limitation of the present study is the lack of selectivity of
buspirone for 5-HT1A receptors. However, the low dose of buspirone used in the
present study likely favours a preferential activation of 5-HT1A autoreceptors.
The results of the present study appear inconsistent with those of chapters 3 and 4.
Chapter 3 found no significant change in the LDAEP slope after acute administration of
SSRIs. Chapter 4 found no significant change in the LDAEP slope after ATD.
Differences in results of the present chapter and those from chapter 3 may relate to the
differential action of antidepressants on 5-HT1A receptors. The increase of 5-HT
function by antidepressants when administered chronically is thought to result from a
desensitisation of 5-HT1A autoreceptors, leading to an increase in 5-HT activity, with no
corresponding desensitisation of postsynaptic 5-HT1A receptors (Blier et al. 1990;
Hensler 2003). In addition, evoked potentials, including LDAEP, reflect modulation of
activity of cortical pyramidal cells (Mitzdorf 1985; Barth and Di 1990), including
hyperpolarisation via activation of 5-HT1A receptors and depolarisation via activation of
5-HT2A receptors (see section 1.2.2.b). Thus, the combined effect of generalized
serotonergic activation or inhibition could be nil if opposing 5-HT1A and 5-HT2A
receptor mechanisms are involved, as in after acute SSRI treatment. The same
explanation could be used for the lack of effect of ATD. Differences in results of the
present chapter and those from chapter 4, may relate to the lack of specific effect of
ATD on 5-HT1A receptors. In contrast, in the present study, 5-HT1A receptors were
more selectively targeted with buspirone treatment.
Another possibility for the apparently conflicting results of the present chapter and
those from chapters 3 and 4 are gender differences, with men tested in chapters 3 and 4,
but women tested in the present study. Indeed, gender differences have been reported in
LDAEP studies, affecting both latency and amplitude of the AEP. For instance, women
have shorter latencies and higher amplitudes when compared to men (Michalewski et al.
1980), while a significantly weaker P2 latency was reported for women when compared
to men (Chen et al. 2002), and larger N1/P2 complex amplitudes have been found in
women when compared to men (Camposano and Lolas 1992). Consistent with this,
gender has been reported as a significant predictor in the ASF slope in MDMA users
(Croft et al. 2001). These differences may relate to the finding that 5-HT synthesis is
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52 % lower in women when compared to men (Nishizawa et al. 1997). Putting together
these results, it seems reasonable to suggest that any manipulation of the 5-HT system
in women will induce a larger effect on the LDAEP slope when compared to men and
should be further investigated.
In addition to gender differences related to 5-HT and LDAEP, differential buspirone
effects between men and women have also been reported. For example, buspirone has
been shown to decrease skin conductance responses in an aversive conditioning
paradigm (used to investigate the mechanism of action of 5-HT and anxiety treatment),
and the effects were more marked in women when compared to men (Hellewell et al.
1999). Therefore, the combination of the marked effect of buspirone and the larger
N1/P2 complex amplitude in women, may explain the inconsistent results between the
present study and chapters 3 and 4. However, because gender was not included as an
experimental factor within any of the experiments in this thesis, further conclusions
about its role must await further investigation.
In accordance with results found in chapters 3 and 4, divergence of individual responses
was found in the tangential and radial slope in the present experiment. One individual
seemed to be off the scale (Figure 5-3). After cautious exploration of the raw data, this
participant did not appear to be an outlier and therefore seems to reflect variability
between participants in the LDAEP response. Similarly to the previous experiments in
this thesis, examination of individual responses suggested that participants can be
classified as augmenters or reducers confirming the need for more attention to intra-
individual responses in future LDAEP research. These ‘atypical’ individuals could be
indicative of the occurrence of a phenomenon that is qualitatively different from the
typical pattern observed or expected in the majority of LDAEP responses. Although the
sample size of the experiment makes it impossible to say whether or not this is the case,
future studies with larger sample size may be able to answer this question.
The present study also compared two methods used for analysing the LDAEP: ASF and
DSA. It has been suggested that the DSA is a more sensitive method to detect a
modulation of the 5-HT system on the LDAEP than the ASF (Hegerl et al. 1994; Lewis
et al. 1986; Scherg and Von Cramon 1986). Contrary to the results of chapters 3 and 4,
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the present study found differential effects for the two methods, with the DSA but not
ASF showing buspirone effects. This may be viewed as support for the advantage of
DSA over ASF and as a demonstration of the reported sensitivity of DSA. However, it
is also possible that the DSA result is an error, with one or more of the required
methodological assumptions underlying it not met. It is not possible to determine this
issue at present, as there is no evidence to show superiority of either method, nor any
evidence suggesting that similar results are obtained using the two methods. For
instance, an augmentation of the LDAEP was reported in long-term ecstasy users using
the DSA (Tuchtenhagen et al. 2000) and the ASF analyses (Croft et al. 2001). In line
with chapters 3 and 4, 95.8 % of the variance of the N1/P2 complex was explained in
the basic dipole model, which did not differ appreciably between treatment conditions
(placebo: 95.7 % and buspirone: 96.0 % of the variance). This suggests that the DSA
method is producing relatively stable results.
There are other reasons that may underly the different LDAEP slope outcome in the
present investigation between the ASF- and DSA-derived LDAEP analysis methods.
First, DSA analysis may be more likely to detect pyramidal cell activity modulation in
the primary auditory cortex than ASF-derived LDAEP analysis that predominantly
reflects the summed activity of many cortical neurons in the area under the EEG
electrode (Cz). Therefore, the A1 pyramidal cell changes in activity induced by
activation of 5-HT1A receptors using buspirone may have been sufficient to be detected
by the DSA-derived analysis, but there may not have been sufficient changes in cortical
neuron activity in the area under the EEG electrode to be detected by the ASF-derived
analysis.
Second, one may wonder about the power of the relevant statistical test to detect a
difference in the ASF-derived LDAEP analysis method, if there truly was one. In the
present chapter, post-hoc power analysis of our design found a power of 0.14
(calculated using G*Power 3.0.3, Concept and design, Universität Kiel, Germany; Faul
and al. 2007) to detect a small effect size (η2 = 0.17) in the ASF-derived analysis.
Therefore, the probability is 0.14 that there is no effect or that if there is an effect it is
small. This is suggesting that the present study has virtually no power to detect a
difference after acute buspirone administration in the ASF slope. Such a result is not
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surprising considering that the t-test in the ASF-derived analysis in the present chapter
resulted in a p value of 0.5 and an effect size of 0.17. If we were to repeat the present
study with a statistical power of 80% (Cohen 1977), a priori power analysis found that
216 participants are needed to achieve such power. Such a sample size raises
practicality and ethical issues and would strains economical resources. Alternatively, a
priori power analysis using the concept of a compromise power analysis developed by
Erdfelder (1984) found a power of 0.67 with a sample size of 30 participants. This is
perhaps more reasonable than the previous alternative.
There is one limitation in the present investigation with regards to DSA, namely that it
was done using only a rough estimation of the primary auditory cortex (using A1
coordinates from the literature), as we lacked a high spatial resolution map of the
primary cortex for each participant. This limitation can be overcome by using
co-registration of EEG and fMRI to improve source localisation. This has been shown
to be feasible in a study that has successfully combined EEG recording and fMRI
(Mulert et al. 2004). However, this limitation is not likely to explain the differences in
the DSA results in the present thesis, as the lack of such co-registration is consistent
with the bulk of the LDAEP literature.
In conclusion, the present data are in line with previous animal research (Juckel et al.
1997, 1999) in that acute activation of the 5-HT1A receptor produced sufficient change
in cortical activity to induce a steeper LDAEP slope of the tangential dipole. This
suggests that although the LDAEP slope may not reflect overall 5-HT function, it may
be related to specific receptor function, namely the 5-HT1A receptor.
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Chapter 6
General Discussion-Conclusion
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Introduction
Reliable measures of serotonergic activity are required to investigate characteristics of
the central 5-HT system in humans. In the early 1990s, LDAEP was proposed as a
non-invasive measure of central serotonergic activity. However, human and animal
studies since then have provided inconsistent and often contradictory evidence of the
relationship between LDAEP and the serotonergic system. The studies in the present
thesis were designed to investigate the effect of serotonergic modulation of LDAEP in
healthy participants. Two main issues were explored: (1) a systematic investigation of
the relationship between LDAEP and the serotonergic system in healthy participants, by
increasing or decreasing 5-HT function, and (2) a comparison of the outcomes of these
modulations using two methods of analysis: DSA and ASF. Participants listened to a
series of acoustic stimuli of fives intensities (60, 70, 80, 90, 100 dB, SPL) while their
EEG was recorded across the scalp. The results reported in each of the three
experimental chapters are discussed in the context of the possible relationship between
LDAEP and the serotonergic system and are summarised below.
6.1. Summary of the key findings
The aim of the first experiment was to examine the impact of an increase in 5-HT levels
in the synaptic cleft, resulting from the administration of one of three different SSRIs.
The results failed to demonstrate any effects of the SSRIs on the LDAEP slope. The
findings of this first experiment did not replicate the findings of Nathan and colleagues
(2006), where treatment with citalopram resulted in a shallower LDAEP slope. On the
other hand, these findings are consistent with other studies that have found no change in
LDAEP after increasing 5-HT function using citalopram (Uhl et al. 2006). There was
no difference in results between the two analysis methods.
The aim of the second experiment was to examine the impact of an overall reduction in
5-HT function using ATD. Measurement of the plasma-free Trp/LNAA ratio was also
reported to confirm the extent of central tryptophan depletion. Despite a 93 % decrease
in the ratio of tryptophan to other LNAAs, no changes in LDAEP slope were found.
These findings are consistent with a number of other studies which have found no
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significant difference in LDAEP slope after ATD (Debener et al. 2002; Dierks et al.
1999; Massey et al. 2004; Norra et al. 2004). Further, similar to the first experiment,
there was no difference between the DSA- and ASF-derived LDAEP analysis.
The final experiment examined the effect of 5-HT1A receptor modulation on the LDAEP
slope using 5 mg of the 5-HT1A receptor partial agonist, buspirone. DSA, but not ASF,
showed that buspirone increased the LDAEP slope derived from the primary auditory
cortex, but not from the secondary auditory cortex. These findings are consistent with
animal studies showing a steeper LDAEP slope in the primary cortex following
administration of the 5-HT1A receptor agonist, 8-OH-DPAT (Juckel et al. 1999).
In summary, the results of this thesis suggest that LDAEP is not a good marker of
central 5-HT function. However, the last experiment of this thesis suggests that LDAEP
may be related more specifically to 5-HT1A receptor function than to 5-HT function in
general. In addition, this experiment also suggested that the DSA method is more
sensitive than the ASF method. Contrary to what was suggested in the literature
(Hegerl et al. 1994; Lewis et al. 1986; Scherg and Von Cramon 1986), there was no
clear evidence from the other experiments of a difference between the two analysis
methods.
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6.2. Discussion
A number of studies have provided support for a relationship between the LDAEP and
5-HT function. Animal studies have shown a steeper LDAEP slope following local
application of the 5-HT1A receptor agonist, 8-OH-DPAT, in the DRN (which decreases
5-HT release) (Juckel et al. 1999) and following postsynaptic 5-HT2A receptor
antagonism with ketanserin (Juckel et al. 1997) or 5-HT1A receptor antagonism with
spiperone (Manjarrez et al. 2005). A shallower LDAEP slope has been reported
following the administration of spiperone in the DRN (which increases serotonin
release) (Juckel et al. 1999), and stimulation of postsynaptic 5-HT1A receptors with
8-OH-DPAT (Juckel et al. 1997). These studies support a relationship between LDAEP
and 5-HT1A receptor activation, as also suggested by the results in chapter 5, where this
relationship was observed after treatment with buspirone.
Evidence in support of the LDAEP hypothesis i.e. of a relationship between the LDAEP
and 5-HT function in humans, are inconsistent. As outlined in the General Introduction
in more detail, clinical studies found a steeper LDAEP slope in disorders with supposed
5-HT dysfunction, such as depression (Buchsbaum et al. 1971) and generalised anxiety
disorder (Senkowski et al. 2003). Furthermore, a relationship between LDAEP and
5-HT function has been inferred from indirect findings using lithium (Hubbard et al.
1980; Hegerl et al. 1990) and ethanol (Hegerl et al. 1996b), which are non-selective
serotonergic modulators, and from correlations with plasma 5-HIAA (Von Knorring and
Perris 1981). However, studies in healthy participants have failed to provide such
evidence. The study by Nathan and colleagues (2006) which showed that acutely
increasing 5-HT function by citalopram treatment resulted in a shallower LDAEP slope,
was not confirmed either in a study using intravenous administration of this drug (Uhl et
al. 2006), or by the first investigation of this thesis (Chapter 3). Similarly, an acute
decrease of 5-HT availability using ATD was shown to have no effect (Dierks et al.
1999; Debener et al. 2002; Massey et al. 2004; Chapter 4 of the present thesis) or cause
a paradoxical decrease in the LDAEP slope (Kahkonen et al. 2002). The discrepant
findings in the literature, along with the negative findings of chapters 3 and 4, do not
support the hypothesis of a straightforward relationship between LDAEP and central
5-HT function. However, the significant findings in previous animal studies (Juckel et
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al. 1997, 1999; Manjarrez et al. 2005) and in chapter 5, suggest that LDAEP may be
more specifically related to 5-HT1A receptor function.
6.2.1. Interpretation of findings in the present thesis
6.2.1.a. Methodological issues
It must be considered whether the lack of relationship between LDAEP and central
5-HT function observed in the present thesis in general reflects a failure of LDAEP as a
marker of activity of the serotonergic system, or whether it reflects issues related to
methodology. It is unlikely that the difference in results between Nathan and colleagues
(2006) and chapter 3 may be the result of different methodology used, since the
protocols that we used were similar and, indeed, both studies were performed in the
same laboratory and used the same EEG methodology. On the other hand, while EEG
was recorded at the peak plasma level for the SSRIs (around 3 hours after dosing), it has
been reported that acute SSRI administration leads to only a mild or no increase of
5-HT neurotransmission and concomitant stimulation of postsynaptic 5-HT receptors
(Waldinger et al. 2005). Therefore, it is possible that the lack of results in chapter 3
may be due to an insufficient increase in 5-HT neurotransmission, although this does
not explain why the previous study (Nathan et al. 2006) found contrary results.
The absence of effect observed after ATD in chapter 4 was unlikely due to insufficient
tryptophan depletion. The drink used in the experiments in this thesis is identical to that
used by Scholes and colleagues (2007), who reported a significant reduction of Stroop
interference (indeed, Scholes’ participants were tested using the same experimental
procedure as in the present thesis). The findings of Scholes and colleagues (2007) are
consistent with a number of other studies which have found decreased Stroop
interference following ATD (Evers et al 2006; Schmitt et al 2000). Therefore, based on
similarities between the present findings and those in the literature, the ATD mixture
used appears to have induced sufficient tryptophan depletion. Furthermore, the amino
acid plasma analysis demonstrated a 93 % decrease in the ratio of tryptophan to other
LNAAs, which is considered to affect central 5-HT function (Carpenter et al. 1998,
Nishizawa et al. 1997; Williams et al. 1999). The lack of effect of ATD was
furthermore unlikely to be due to competition between tryptophan and tyrosine in
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crossing the blood brain barrier, because in the present work a high decrease in the ratio
of tryptophan to other LNAAs was found, while the decrease in the tyrosine ratio to
other LNAAs remained low. This suggests that the ATD technique selectively affected
the 5-HT system and it seems unlikely, therefore, that the lack of effects in the second
investigation was related to plasma tryptophan levels. Also previous studies report a
robust depletion of tryptophan levels or the more important ratio of tryptophan to other
LNAAs after ATD (Ahveninen et al. 2002; Carpenter et al. 1998; Harrison et al. 2004;
Hughes et al. 2004; Kahkonen et al. 2002; Knott et al. 1999; Mc Allister-williams et al.
2002; Nathan et al. 2004; Scholes et al. 2007; Williams et al. 1999).
Literature reports suggest that the lack of effect in ATD in LDAEP studies may due to
the use of ASF analysis methodology instead of the DSA method (Beauducel et al.
2000; O’Neill et al. 2006a; Segrave et al. 2006; Uhl et al. 2006). Therefore, the present
thesis aimed to identify whether there is a difference between these analysis methods,
and no evidence of this was found. The lack of differences between the two methods
following 5-HT modulation in both chapters 3 and 4 is unlikely due to unreliability of
the methods. Additional statistical analysis was carried out to determine if there were
differences in DSA slope and in ASF slope between each study in the placebo
conditions and it was hypothesised that if DSA and ASF methodology are reliable, then
they should produce consistent slopes from one study to the next. A one-way ANOVA
showed that there was no significant difference in the DSA slope between each
experiment (F(2,38) = 1.34, p = 0.27; partial η2 = 0.07)2 (Table 6-1). Further, a high
percentage of variance in the N1/P2 complex (from 95.8 % to 98.8 %) was explained by
the basic dipole model, which did not differ appreciably between the placebo conditions
(Table 6-1). More importantly, the percentage of variance of the N1/P2 complex
reported in the three experiments in the present work is very similar to those reported in
the literature (Hegerl and Juckel 1993; Hegerl et al. 1994; Juckel et al. 1995).
Therefore, these results suggest good reliability of the DSA between each experiment.
2 To determine if there was a difference in method between studies, a two (Method: ASF and DSA) x three (Study: SSRI, ATD and buspirone) ANOVA was performed. Further analysis was then done with one-way ANOVAs for each method separately, followed by multiple comparison LSD post-hoc tests.
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However, significant difference in the ASF slope between each placebo condition was
found between the studies (One-way ANOVA: F(2,39) = 7.57, p = 0.002; partial
η2 = 0.29) (Table 6-1). Pairwise comparison using the least significant difference
(LSD) procedure revealed significant differences between ASF slopes in the SSRI
experiment in chapter 3 and those in the ATD experiment in chapter 4 (d = -0.12;
p = 0.024); as well as significant differences between chapter 3 and the buspirone
experiment in chapter 5 (d = -0.21; p < 0.01) and between chapter 4 and chapter 5
(d = -0.10; p = 0.048). Therefore, there was little consistency in the ASF-derived
LDAEP slopes between studies and the reliability and reproducibility of this method is
therefore questionable. The difference in reliability between the ASF and DSA methods
found in the present thesis is in accordance with the results obtained by Beauducel and
colleagues (2000), in that the DSA method appears to be more reliable than the
ASF-derived analysis.
Table 6-1: Summary of the present thesis results for the placebo condition
SSRI Study ATD Study Buspirone study
ASF slope 0.22 (0.03)* 0.32 (0.04)* 0.41 (0.05)*
TL 1.98 (0.25) 3.41 (0.80) 2.23 (0.30)
TR 2.05 (0.26) 4.13 (0.70) 2.32 (0.21)
RL 1.49 (0.18) 1.38 (0.63) 1.85 (0.21) DSA slope
RR 2.05 (0.26) 2.34 (0.55) 1.99 (0.24)
Mean (SEM). *p < 0.05: LSD Pairwise comparison of LDAEP slopes in the placebo condition in each study (i.e. SSRI, ATD and buspirone) in this thesis. DSA slope in µAmm/dB and ASF slope in µV/dB.
6.2.1.b. Possible individual differences in LDAEP
a- Gender differences
Gender differences have been suggested throughout this thesis as a possible explanation
for the discrepancies between the present results and the literature. As outlined in more
detail in the General Introduction, differences in 5-HT neurotransmission between men
Chapter 6
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and women have been reported in the literature (Anderson et al. 1990; Goodwin et al.
1994). For instance, 5-HT synthesis has been found to be 52 % lower in normal women
when compared to normal men (Nishizawa et al. 1997) and women had a significantly
greater response to SSRIs when compared to men (Berlanga and Flores-Ramos 2006;
Khan et al. 2005). We have furthermore shown that the ASF slope is correlated with
depression scores in women (r = 0.42; p = 0.07) and inversely correlated with
depression scores in men (r = -0.70; p = 0.007) (Appendix I, Guille et al. 2004). Gender
differences also affect both latency and amplitude of the AEP (Chen et al. 2002;
Michalewski et al. 1980). Women have shorter latencies and higher amplitudes than
men (Michalewski et al. 1980). A significantly weaker P2 latency was reported for
women with the s/s genotype for the 5-HTT gene than for the two other genotypes; l/s
and l/l (Chen et al. 2002). This is suggesting that gender may also affect the LDAEP
slope. Indeed, gender has been reported as a significant predictor in the ASF slope in
MDMA users (Croft et al. 2001).
As discussed in section 3.3., Nathan and colleagues (2006) used a mixed-gender
sample, while in chapter 3 we used men only. If women have a significant greater
response to SSRIs, it is therefore possible that the positive results found by Nathan and
colleagues (2006) are due to the presence of women in their participant sample. Gender
differences have also been suggested as a possible explanation for negative results in
ATD studies (Neumeister et al. 2002; Neumeister 2003). However, it should be noted
that ATD did not influence ASF slope either in studies using only women (Debener et
al. 2002; Norra et al. 2004) or in the present investigation using only men (Chapter 4).
In chapter 5, a significantly steeper tangential slope was reported after acute activation
of 5-HT1A receptors in women, while no changes in the LDAEP slope were found in
men after a decrease in central 5-HT function using ATD (Chapter 4) or an increase in
5-HT function using SSRIs (Chapter 3). However, a gender effect cannot be claimed
based on the finding of this thesis, as gender differences in LDAEP were not
investigated within each experiment. Nevertheless, it may be more difficult to detect
5-HT effects on LDAEP in men than in women, and it is possible that the discrepancies
in the 5-HT/LDAEP literature are clouded by gender differences. Therefore, future
studies should investigate further the influence of gender on the LDAEP.
Chapter 6
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b- 5-HTT polymorphism and LDAEP
The discrepant findings between the literature and the present thesis may also be
explained by the influence of 5-HTT polymorphisms. These polymorphisms have been
reported to be associated with depression and the response to SSRI treatment (Smits et
al. 2004). For instance, depressed patients with the l/l genotype responded quicker to
acute SSRI treatment (paroxetine, 20 mg) than those with l/s or s/s genotype (Pollock et
al. 2000). Polymorphisms in the 5-HTT gene were associated with the influence of
stressful life events on depression. For instance, individuals with one or two copies of
the short allele exhibited more depressive symptoms, diagnosable depression and
suicidality in response to stressful life events when compared to individuals who were
homozygous for the long allele (Smits et al. 2004). These studies underline a possible
relationship between 5-HTT genotype and 5-HT function. Therefore, it is conceivable
that LDAEP may also be influenced by 5-HTT genotype. A genetic influence on the
LDAEP has been described in several studies (Chen et al. 2002; Gallinat et al. 2003;
Strobel et al. 2003). l/l genotype carriers exhibited a shallow LDAEP slope, when
compared to l/s and s/s carriers (Gallinat et al. 2003). Given that most of the studies on
LDAEP did not investigate 5-HTT polymorphisms, it is therefore possible that the
inconsistencies may in part be explained by genetic variations between study subject
populations that influence 5-HT neurotransmission.
c- Augmenters and reducers
In early ERP studies, the concept of augmenting/reducing was postulated as a central
mechanism affecting the response to external stimuli. Participants were classified as
augmenters when showing a larger response after increasing visual stimuli and reducers
when showing the opposite response (Buchsbaum and Silverman 1968). Since 1968,
the concept of augmenting/reducing has been related to neuropsychiatric disorders such
as schizophrenia (Landau et al. 1975) and depression (Buschman et al. 1971). Although
the augmenters/reducers concept was mainly studied in the visual modality, many
investigations have attempted to relate it to AEP in healthy participants (see
Carrillo-de-la-Peña 1992 for review, Kaskey et al. 1980; Lolas et al. 1987). The
augmenters/reducers concept in AEP studies has been criticised because of variability in
its characteristics, such as inter-stimulus interval or recording sites (Connolly 1987;
Chapter 6
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Carrillo-de-la-Peña 1992; Hegerl and Juckel 1993; see section 1.3.5.a for details).
Taking into account the above criticisms and in an attempt to propose an alternative
measure of the augmenting/reducing concept, the more neutral LDAEP was proposed
(Hegerl and Juckel 1993). Since then, inter-individual difference in response to
increasing stimulus loudness in LDAEP studies have not received widespread attention
in the literature.
The present thesis found inter-individual differences in the ASF slope and DSA slope of
LDAEP. Inspection of the individual responses suggests that participants can be
classified as augmenters or reducers in both ASF- and DSA-derived methods (see
scatter graphs in Figures 3.4, 3.7, 4.1, 4.4, 5.3 and 5.6). Although there are no clear
criteria in the early AEP literature for classifying participants as augmenters or reducers,
the present findings suggest that the outcome of the analysis would have been different
if these subgroups could be separated in the statistical analysis. Therefore, one
limitation of the present study is the lack of pre-classification of the participants in
terms of their response to auditory stimulation. Although such selection could have
been done after the testing sessions, it would have necessitated bigger sample groups in
order to reach significance. These considerations emphasize that more attention is
needed on variability in individual responses to avoid it being a confounding factor in
future LDAEP research.
6.2.1.c. 5-HT1A receptor vs central 5-HT function in LDAEP
As discussed above and in chapter 5, animal studies found direct evidence supporting
LDAEP modulation by 5-HT1A receptor activation (Juckel et al. 1997, 1999; Manjarrez
et al. 2005). Clinical studies have provided indirect support for these findings, with
demonstration of a steeper LDAEP slope in disorders with supposed 5-HT1A receptor
dysfunction, such as depression (Buchsbaum et al. 1971) and generalised anxiety
disorder (Senkowski et al. 2003), and a shallower LDAEP slope in schizophrenia
(Burnet et al. 1997). Therefore, it is possible that 5-HT1A receptors modulate LDAEP
slope in these disorders. In support of this, chronic SSRI administration has been found
to lead to a desensitisation of 5-HT1A autoreceptors (Hensler 2003), while acute SSRI
administration results in an increase of synaptic 5-HT concentrations. Putting together
these evidences with the results in chapter 5 support a possible relationship between
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LDAEP and 5-HT1A receptor function, rather than the generalised central 5-HT
influence suggested by Hegerl and Juckel (1993). Thus, it is possible that stimulation of
5-HT1A receptors induces sufficient modulation of 5-HT neuronal firing to modify the
LDAEP slope, as opposed to changes in 5-HT firing resulting from more global 5-HT
modulation. Future investigation should examine this matter in both human and animal
studies to fully understand the relationship between LDAEP and 5-HT/5-HT1A function.
6.2.1.d. Towards a neurophysiological model for an explanation of the differential
results found between DSA and ASF slope after serotonin modulation
While the exact mechanisms responsible for the relationship between LDAEP and 5-HT
function in clinical studies are unknown, most evoked potentials, including LDAEP,
reflect activity of cortical pyramidal cells (Mitzdorf 1985; Barth and Di 1990; see
section 1.2.2.a. for more details). In the present thesis, results were expressed as DSA-
and ASF-derived LDAEP. The DSA method is based on physical law describing scalp
potential. DSA separates the auditory evoked N1/P2 complex into subcomponents
generated by A1 and A2 modelled by two separate dipoles in each temporal lobe, one
dipole for A1 and one dipole for A2. ASF reflects overlapping subcomponents in the
area under the EEG electrode generated by A1 and A2 (see section 1.3. for more
details).
The primary auditory cortex has a high density of serotonergic innervation (Lewis et al.
1986; Wilson and Molliver 1991), which enables LDAEP slope to be modulated by the
serotonergic system and more specifically by 5-HT1A receptors (Juckel et al. 1997).
Thus, low 5-HT function within the auditory cortex is represented by a steep LDAEP
slope and high 5-HT function within the auditory cortex is represented by a shallow
LDAEP slope. The exact mechanism underlying modulation of electrophysiological
responses in LDAEP by neurotransmitters is unknown. Hyperpolarisation or
depolarisation via 5-HT1A and 5-HT2A receptors, respectively, of a group of pyramidal
cells contributes to the LDAEP slope (Mitzdorf 1985; Barth and Di 1990; see section
1.2.2.b for more details). Therefore modulation of 5-HT1A and 5-HT2A receptors, using
receptor agonists or antagonists, will induce sufficient electrophysiological changes to
modify the LDAEP slope. Accordingly, local administration of the 5-HT1A receptor
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agonist, 8-OH-DPAT (Juckel et al. 1999) and administration of the 5-HT1A receptor
partial agonist, buspirone (Chapter 5), led to a steeper LDAEP slope in A1.
A tentative model describing the differential effects of buspirone between ASF-derived
and DSA-derived LDAEP slope is described here. LDAEP slope changes associated
with modulation of the 5-HT1A autoreceptors may be the result of direct activation of
these autoreceptors in the DRN, which leads to a decrease in 5-HT neuronal firing and
reduced 5-HT release and receptor stimulation at the postsynaptic level (i.e. layer 4).
Changes in 5-HT firing thus alter the excitatory or inhibitory nature of the pyramidal
cells that can be recorded using the DSA method. DSA uses a mathematical model,
called the inverse problems that incorporates biophysical properties to estimate the
location of sources that generate a set of electrical potentials measured at the surface of
the scalp (Scherg 1990). In the inverse problem, when a section of the cortex becomes
activated by hyperpolarisation or depolarisation of a group of pyramidal cells,
intraneuronal current flows can be approximated by tangential dipoles. Considering
these properties of the inverse model, modification of intraneuronal current flows
following a decrease in 5-HT firing via modulation of 5-HT1A autoreceptors seems to be
sufficient to be approximated by tangential dipoles (Chapter 5). However, this
modification of intraneuronal current flows may not have been sufficient to be recorded
at the scalp using EEG (i.e. ASF slope analysis). This is possible because EEG records
electrical potential changes which occur between two electrodes located on the scalp.
Therefore, current flows recorded using EEG electrodes and analysed using the
ASF-derived method need to be sufficient enough to go through the brain tissue, cranial
bone and skin, to induce a change in the ASF slope. Because of the estimation of dipole
using the inverse problem, these current flows, even if they are small, may be sufficient
to be approximated by the DSA-derived method.
6.2.1.e. Summary
In summary, this thesis demonstrated that an increase and a decrease in central 5-HT
function failed to modulate the LDAEP slope. There are no clear methodological issues
to explain the lack of effects on the LDAEP slope. In addition, the findings of this
thesis suggested no significant differences between the DSA and ASF analysis method
of the LDAEP. Taken together, these results weaken the hypothesis of LDAEP as a
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135
valid marker for the central 5-HT function in healthy humans. However, the final
experiment of this thesis suggests that LDAEP slope is influenced by modulation of the
5-HT1A receptors, instead of the modulation of the central 5-HT function.
6.2.2. Future research
Together with previous evidence in animal studies (Juckel et al. 1997, 1999; Manjarrez
et al. 2005), the current findings suggest that LDAEP, as analysed with the DSA
method, may be a valid marker for 5-HT1A receptor function. Therefore, further studies
should investigate this possible relationship bearing in mind some of the factors that
may influence the LDAEP response.
As indicated in chapter 2 and above, the 5-HTT genotype has been found to be
correlated with the LDAEP slope, although the literature has been inconsistent. While
some reports suggest shallow LDAEP slopes in l/l carriers in comparison to l/s and s/s
carriers (Gallinat et al. 2003), some other reports show steep LDAEP slope for l/l
carriers when compared to the other genotypes (Hensch et al. 2006; Strobel et al. 2003;
see section 2.4 for details). This influence of genotype in LDAEP needs further
consideration, particularly because a relationship between major depression and 5-HTT
genotype has been suggested (Owens and Nemeroff 1994).
Also with respect to 5-HT1A receptor function, individual differences related to
genotype, gender and initial LDAEP slope may influence whether subsequent
modulation of this receptor will have an effect. Limitations of the work in the present
thesis, therefore, are that there was no investigation of modulation of central 5-HT
function, and specifically 5-HT1A receptors, in both men and women and no analysis for
genotype in either gender. Future research, which attempts to incorporate these factors,
may be more successful in elucidating the effect of central 5-HT function and 5-HT1A
receptors on LDAEP.
Future studies should also use imaging technology in order to help to elucidate the
central mechanisms associated with LDAEP. For instance, associating LDAEP and
PET scanning using specific serotonergic radiotracer such as 11C-DASB, can be used in
order to define possible covariates modulating LDAEP. Because of variability in the
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morphology of the A1 region in the human brain, Mulert and colleagues (2002)
underlined the importance of a clear separation of the primary auditory cortex from the
secondary auditory cortex, to further improve the validity of DSA methodology
(Pentune et al. 1996). Therefore, another limitation of the present thesis is that there
was no fMRI recording for each individual, and hence there was no accurate way to
record the location of A1. However, this limitation is not likely to explain the
differences between the present thesis’ results and that from past research, as the lack of
such co-registration is consistent with the bulk of the LDAEP literature. In a recent
review on ERPs and neuropharmacology, Pogarell and colleagues (2006) suggested
co-registration of fMRI and EEG in future investigations (Mulert et al. 2004, 2005;
Nunez and Silberstein 2000) to provide useful information about activated brain regions
in LDAEP. However, this co-registration remains applicable mainly in research, due to
the practical and technical difficulties of the techniques and the cost of fMRI.
Like most research endeavours, findings reported in this thesis appear to raise more
questions than answers. Some of the questions are: (1) Do gender differences affect the
LDAEP slope? (2) What is the exact 5-HTT genotype influence on the LDAEP?
(3) To what extent does 5-HT1A receptor function influence the LDAEP slope? By
answering these questions in animals and in humans, the relationship between LDAEP
and 5-HT function will be better understood and it may be possible that LDAEP could
be a valid marker in clinical research.
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137
6.3. Conclusion
This thesis has investigated the relationship between LDAEP and the serotonergic
system in healthy participants, by increasing or decreasing central 5-HT function. Two
analysis methods for the LDAEP slope, ASF and DSA, were compared. The present
results question the thesis that there is a clear relationship between LDAEP and global
5-HT function, however there may be a relationship between LDAEP and 5-HT1A
receptor function instead. The present thesis also suggests considering gender
differences when investigating the relationship between LDAEP and 5-HT function.
Further, results also suggest that there is no difference between DSA- and ASF-derived
methods with respect to the effect of SSRIs and ATD. It is clearly not suggested that
research on the LDAEP should discontinue, as there remains some degree of
consistency across various studies. Further investigations should be carried out to
address methodological concerns such as characteristics of selected samples,
involvement of 5-HT1A receptors, and the analysis methodology used (ASF vs DSA).
Future research should employ consistent procedures, to ensure comparability between
studies.
References
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Appendices
Appendix A: Consent Forms
A-1. Version used in experiment presented in Chapter 3: The Sensitivity of the LDAEP
to Changes in Central Serotonergic Neurotransmission: Effects of Three Selective
Serotonin reuptake Inhibitors
A-2. Version used in experiment presented in Chapter 4: The Sensitivity of the LDAEP
to Changes in Central Serotonergic Neurotransmission: Effects of Acute Tryptophan
Depletion
A-3. Version used in experiment presented in Chapter 5: The Sensitivity of the LDAEP
to Changes in Central Serotonergic Neurotransmission: Effects of the 5-HT1A Receptor
Agonist Buspirone
Appendix A.1
SWINBURNE UNIVERSITY OF TECHNOLOGY
BRAIN SCIENCES INSTITUTE
FORM OF DISCLOSURE AND
INFORMED CONSENT
Project Title:
An Examination of the Central Serotonergic Effects of Escitalopram in
Comparison to RS-Citalopram and Sertraline Using a Novel
Electrophysiological Marker of Brain Serotonin Function
Investigators:
Primary Investigators: Valérie Guille
A/Prof. Pradeep Nathan
A/Prof. Rodney Croft
Participant’s Name: ___________________________________Participant ID Code:_____________
Only the Primary Investigators will have knowledge of the names and code numbers used. It is the responsibility of the Primary Investigators to destroy this information at the end of the study. If confidentiality is required to be broken, this may only be done by the Primary Investigators after consultation with the Participant in writing.
Appendix A.1
I,……………………………………………………………………………………………………
(Name of participant)
agree to participate in a research project entitled “An Examination of the Central Serotonergic
Effects of Escitalopram in Comparison to RS-Citalopram and Sertraline Using a Novel
Electrophysiological Marker of Brain Serotonin Function”, conducted by Ms. Valérie Guille,
A/Prof. Pradeep Nathan and A/Prof. Rodney Croft.
My agreement is based on the understanding that:
• I agree to participate in this study, realizing that my identity will remain confidential, and that I
may withdraw at any time.
• I have been given a full explanation and a copy of the information sheet outlining the purpose of
this study, the procedures involved, and what I will be expected to do.
• I have been given an explanation of how the drugs Zoloft® (Sertraline), Lexapro®
(Escitalopram) and Cipramil® (Citalopram) work and have been informed about the possible
side effects.
• My consent to participate in this project is given freely.
• I understand the time involved in each of the four recording sessions (5h x 4 sessions).
• I understand that I cannot drink alcohol or coffee 20h prior to each of the recording days.
• I am currently not taking any medication, vitamins, diet complement or illegal drugs, and I am a
non-smoker.
• I have no previous head injuries or epilepsy.
SIGNED…………………………………………………………DATE……………………………
(Participant)
SIGNED…………………………………………………………DATE……………………………
(Researcher)
Appendix A.2
SWINBURNE UNIVERSITY OF TECHNOLOGY
BRAIN SCIENCES INSTITUTE
FORM OF DISCLOSURE AND INFORMED CONSENT
Project Title:
The Effects of Dopamine Depletion and Serotonin Depletion on Emotional
Processing and Cognition
Principal Investigators: Ms Valérie Guille Ms Sumie Leung Mr Alan Dunne Senior and Associated Investigators: A/Prof Pradeep Nathan A/Prof Rodney Croft Dr. Susan Ilic Ms Kirsty Scholes Ms Hayley Lawrence Ms Clementine Thurgood Participant’s Name:_____________________________________Participant IDCode:____________ Only the Primary Investigators will have knowledge of the names and code numbers used. It is the responsibility of the Primary Investigators to destroy this information at the end of the study. If confidentiality is required to be broken, this may only be done by the Primary Investigators after consultation with the Participant in writing.
Appendix A.2
I, ……………………………………………………………………………………………
(Name of participant)
agree to participate in a research project entitled: The Effects of Dopamine Depletion and Serotonin
Depletion on Emotional Processing and Cognition conducted by Ms Valérie Guille, Ms Sumie Leung,
Mr Alan Dunne, A/Prof. Pradeep Nathan, A/Prof Rodney Croft, Ms Kirsty Scholes, Ms Hayley
Lawrence and Ms Clementine Thurgood. I have read and understood the information given to me
regarding this project and any questions I have asked have been answered to my satisfaction.
My agreement is based on the understanding that: • I agree to participate in this activity, realising that my identity will remain confidential, and that I
may withdraw at any time.
• I do not have epilepsy, or a personal history of epilepsy
• I do not have any physical or psychiatric disorders
• I have been given a full explanation and a copy of the information sheet outlining the purpose of this study, the procedures involved, and what I will be expected to do.
• I am not on any medication
• I do not smoke
• I have been given an explanation of how the amino acid depletion procedure work and have been informed about the possible side effects.
• I understand that participation in this study involves the donation of 10 ml of blood, twice during each testing session
• My consent to participate in this project is given freely.
• I understand the time involved in the medical screening session and each of the four recording sessions.
• I agree that research data collected for the study may be published or provided to other researchers on the condition that anonymity is preserved and that I cannot be identified.
• I agree to follow the diet recommended by the investigators on the day prior to testing.
SIGNED…………………………………………………………DATE……………………………
(Participant) SIGNED…………………………………………………………DATE……………………………
(Researcher)
Personal privacy protection in health care information systems, Australian Standard AS 4400-1995. Privacy Act,1988 Commonwealth of Australia The December 1991 Guidelines for Good Clinical Research Practice in Australia, published by the Therapeutic Goods Administration of the Commonwealth Department of Health and Family Services, recommends retention of data for at least 15 years. Uniform Requirement for Manuscripts Submitted to Biomedical Journals as presented in JAMA 1993: 269:2282-
Appendix A.3
SWINBURNE UNIVERSITY OF TECHNOLOGY
BRAIN SCIENCES INSTITUTE
FORM OF DISCLOSURE AND INFORMED CONSENT
Project Title:
Examining the interaction between oestrogen and the serotonin-
1A receptor, in models of schizophrenia.
Investigators:
Primary Investigators: Andrea Gogos, Valérie Guille
Senior and Associated Investigators: A/Prof. Pradeep Nathan
Dr. Maarten Van Den Buuse
Dr. Rodney Croft
Participant’s Name:____________________________________Participant IDCode:____________
Only the Primary Investigators will have knowledge of the names and code numbers used. It is the responsibility of the Primary Investigators to destroy this information at the end of the study. If confidentiality is required to be broken, this may only be done by the Primary Investigators after consultation with the Participant in writing.
Appendix A.3
I, ……………………………………………………………………………………………
(Name of participant)
agree to participate in a research project entitled ‘Examining the interaction between oestrogen and
the serotonin-1A receptor, in models of schizophrenia’, conducted by A/Prof. Pradeep Nathan, Ms.
Andrea Gogos, Ms. Valérie Guille, Dr. Maarten Van Den Buuse and Dr. Rodney Croft.
My agreement is based on the understanding that: • I agree to participate in this study, realising that my identity will remain confidential, and that I
may withdraw at any time. • I have been given a full explanation and a copy of the information sheet outlining the purpose of
this study, the procedures involved, and what I will be expected to do.
• I have been given an explanation of how the drugs Oestradiol (Estrofem) and Buspirone (Buspar) work and have been informed about the possible side effects.
• My consent to participate in this project is given freely. • I understand the time involved in each of the four recording sessions. • I understand that I cannot drink alcohol on each of the recording days. • I am currently not taking any medication and I am a non-smoker. SIGNED…………………………………………………………DATE……………………………
(Participant)
SIGNED…………………………………………………………DATE……………………………
(Researcher)
Appendix B
Appendix B: Treatment randomisation
B-1. Version used in experiment presented in Chapter 3 and Chapter 4:
B-2. Version used in experiment presented in Chapter 5:
Appendix B.1
Randomisation table for treatment administration for the SSRI study (Chapter 3) and for the Tryptophan depletion study (Chapter 4)
Subject # Test 1 Test 2 Test 3 Test 41 A B C D2 D A B C3 C D A B4 B C D A5 A B C D6 D A B C7 C D A B8 B C D A9 A B C D10 D A B C11 C D A B12 B C D A13 A B C D14 D A B C15 C D A B16 B C D A17 A B C D18 D A B C19 C D A B20 B C D A
Drug Identification:
Treatment SSRI study (Chapter 3)
Tryptophan depletion (Chapter 4)
A Citalopram (20 mg) Placebo
B Placebo Combine3
C Sertraline (50 mg) Tryptophan depletion
D Escitalopram (10 mg) Tyrosine/Phenylalanine depletion3
3 Data not reported in the present thesis. See preface for details.
Appendix B.2
Randomisation table for treatment administration for the buspirone study (Chapter 5) 4
Subject # Test 1 Test 2 Test 3 Test 41 B D A C2 A C B D3 C A D B4 D B C A5 B D A C6 A C B D7 C A D B8 D B C A9 B D A C
10 A C B D11 C A D B12 D B C A13 B D A C14 A C B D15 C A D B16 D B C A17 B D A C18 A C B D19 C A D B20 D B C A
Drug Identification:
Treatment buspirone study (Chapter 5)
A Oestrogen5
B Placebo
C Oestrogen + Buspirone (5 mg)5
D Buspirone (5 mg)
4 Latence square randomisation done using randomisation tables from: Lellouch and Lazar 1999. 5 Data not reported in the present work. See preface for details.
Appendix C
Appendix C: Participant information sheet
C-1. Version used in experiment presented in Chapter 3: The Sensitivity of the LDAEP to Changes
in Central Serotonergic Neurotransmission: Effects of Three Selective Serotonin reuptake Inhibitors
C-2. Version used in experiment presented in Chapter 4: The Sensitivity of the LDAEP to Changes
in Central Serotonergic Neurotransmission: Effects of Acute Tryptophan Depletion
C-3. Version used in experiment presented in Chapter 5: The Sensitivity of the LDAEP to Changes
in Central Serotonergic Neurotransmission: Effects of the 5-HT1A Receptor Agonist Buspirone
Appendix C.1
SWINBURNE UNIVERSITY OF TECHNOLOGY
BRAIN SCIENCES INSTITUTE
PARTICIPANT INFORMATION SHEET
An Examination of the Central Serotonergic Effects of Escitalopram
in Comparison to RS-Citalopram and Sertraline Using a Novel
Electrophysiological Marker of Brain Serotonin Function
Investigators: Primary Investigators: Miss Valérie Guille A/Prof. Pradeep Nathan A/Prof. Rodney Croft Participant’s Name: ___________________________________________________________________________
Only the Primary Investigator should have knowledge of the names and code numbers (if any) used. It is the responsibility of the Primary Investigators to destroy this information at the end of the study. If confidentiality is required to be broken, this may only be done by the Primary Investigators after consultation with the Participant in writing.
Appendix C.1
EXPLANATION OF PROJECT – PARTICIPANT INFORMATION
Purpose of the study Serotonin is one of the principal brain chemicals in the brain. A low level of this chemical has been linked to depression and anxiety, with the treatment for these disorders typically involving some form of serotonin enhancement (e.g. the antidepressant such as ‘Prozac’). Recently, a new non-invasive method has been suggested as a possible test of serotonin function. It is a method whereby patterns of brain wave activity generated in the brain in response to tones of varying loudness indicate amount of serotonin. The brain‘s electrical responses to these stimuli are recorded externally using an electroencephalogram (EEG). Escitalopram, Sertraline and RS-citalopram are antidepressant used to treat depression. While it has been established from animal studies that Escitalopram has a stronger effect on serotonin than RS-Citalopram this has not been demonstrated in the brain of humans. In the current study, we aim to compare the effects of Escitalopram in comparison to RS-Citalopram and Sertraline on the Brain electrical activity (brain wave) in healthy subjects. We hypothesize that Escitalopram will have stronger effects on the serotonin system in comparison to RS-Citalopram and the well know antidepressant Sertraline. Requirements of the study We need healthy, non-smoking males aged 18 to 40 years, who are not on any medication, to be participants in this research. Participants will undergo a medical examination by a physician to ensure they are in good health, have no psychiatric disorders and medication free. Participants will need to come to the Brain Sciences Institute (BSI, Swinburne University of Technology, 400 Burwood Road, Hawthorn) four times (at least one week apart) and will be reimbursed $200 for time and travel expenses incurred by your involvement in the study. You will have your electrical brain activity (EEG) recorded while you complete a number of simple tasks on a computer. The EEG cap contains 70 electrodes, which record the natural activity of your brain. Nothing in the cap will hurt you. A small amount of water-based gel will be used to help link each electrode to the scalp. This gel will be washed out after the recording is completed. Some electrodes will also be placed around the eyes to record eye-blink responses. You will need to wear headphones so that sounds can be heard. None of this equipment causes any harm. You will complete eight simple computer tasks while EEG is recorded. A description of these tasks can be found below. Procedure Before taking part in the study, the researcher will explain the study and the tasks to you. You will then be asked to read about the drug treatments that you are to receive, and if you find everything satisfactory, you will be asked to fill in a consent form to participate in the study. A medical examination will then be arranged with a doctor at Swinburne University. Following the medical, you may begin the study. You will be required to attend tests on four days. You will have your brain activity recorded a total of 4 times, across four different testing days (see timetable below). It is very important that you have not consumed alcohol or caffeinated products for 20 hours before arriving at the Brain Sciences Institute (BSI). You will first be given some questionnaires and one tablet (either a medication or the placebo). You will then have a 3 hours break, from 10:00am to 1:00pm (you may choose to watch a video during this time or do personal work or reading). The EEG recording equipment will then be set up. The EEG recording begins at 1:30pm and runs for 1 hour and 15mins. After or before this, a 3D map of the emplacement of the electrodes will de recorded. Then, the cap and the electrodes will be removed and your hair washed.
Appendix C.1
Timetable 9.30am: Arrive at Brain Sciences Institute, Swinburne Uni, Hawthorn 9.30am – 10.00am Questionnaire 10.00am Drug/placebo administration 12.15am – 12.45am 3D map recording 1.00pm - 1.30pm: Preparation for EEG recording 1.30pm – 2.45pm: EEG recording 2.45pm – 3.00pm: Removal of equipment, hair washing and debriefing Please Note Please be at the BSI by 9.30am AT THE LATEST on all of your test days. The recordings run to a time schedule, it is important for this study, and others run at the BSI that this schedule is adhered to. Experimental Tasks 1/ Baseline EEG. You will have 3 minutes of EEG (brain activity) recorded while you are relaxing with your eyes closed and then relaxing with eyes open. 2/ Pattern Reversal (3 mins) – You will have to look at a small disk on a computer screen, and press a button whenever it changes from yellow to blue. Whilst this occurs, the screen, which is made up like a ‘checkerboard’, flashes from black to white, and white to black (condition 1), and red to green, and green to red (condition 2). 3-7/ These tasks (total 38 mins) are similar and involve briefs sounds (tones or clicks) being presented every few seconds via headphones, while you are required to press a button when you hear certain sounds, or when a square change on the screen or simply read a magazine. 8/ The last task lasts for 9 minutes and measures your eye-blink startle response to briefs sounds. While you sit comfortably and relax, you will be presented with a random order of 24 briefs sounds through the headphones. The loudest sound pulse presented is 105 dB, however, this will only be presented for 40 msec. 9/ Emotional Detection Task (8 mins) – You will be presented with positive, neutral and negative visual stimuli, with your task being to press a button to the positive and another button to the negative stimuli (i.e. no strongly positive pictures such as naked bodies, or strongly negative pictures such as serious injuries, the pictures have been approved by the ethics committee). 10/ Emotional Face Recognition Task (6 mins) – You will be presented with emotional or neutral faces, and will be asked to say what emotion the face is portraying. At the end of the tasks, a 3-dimensional map of the participant’s precise electrode placement is created using a polyhemus 3-D digitizer. It will take approximately 20 minutes. After the recording is completed, the EEG cap and electrodes are removed and the participant’s hair is washed. Care will be taken to ensure that participants are not distressed, and naturally, participants are free to withdraw from the study at any time.
Appendix C.1
Medications Each time you attend a testing session, you will be given one of the following medications; Zoloft® (Sertraline, 50 mg), Lexapro® (Escitalopram, 10 mg), Cipramil® (Citalopram, 20 mg), or a Placebo (a pill containing flour and gelatine). Neither you, nor the primary investigator will know which of these compounds you receive. Sertraline, Escitalopram and Cipramil are medications used to treat people with depression in Australia. It is suggested that you read the drug information summary sheets provided so that you understand what these medications are, how they work and any side effects that may result. We do not expect participants to suffer any significant side effects as a result of taking these medications; however you should be aware that there is always some chance of an adverse reaction. Confidentiality It is normal in studies like this for participant’s identity to be kept confidential. No one apart from the researchers who collect the data will know who the participants are, or be told any personal information about the participants. The data from this study will be stored in a secure place within the BSI, and will only be available to people directly involved with the study. The results from this study may be published or provided to other researchers but your identity will be kept confidential. Please note that your participation in this study is entirely voluntary. You are free to withdraw your consent and participation at any time during the study. If you have any questions about the study, or don’t understand something properly please feel free to ask me to explain. My contact details are: Valérie Guille Ph: 9214 5543 Email: [email protected] If you would prefer, you can contact the project supervisors at any time. A/Prof. Pradeep Nathan Ph: 9214 5216. A/Prof. Rodney Croft Ph: 9214 5149. If you have any complaints about the way that you have been treated during this study, or a question that the investigators have been unable to answer, you may write to either of the addresses below: The Chair The Director Human Experimentation Ethics Committee Brain Sciences Institute Swinburne University of Technology Swinburne University of Technology P O Box 218 400 Burwood Road
HAWTHORN. VIC. 3122 HAWTHORN. VIC. 3122 Phone: (03) 9214 5223 Phone: (03) 9214 8273
Appendix C.1
SWINBURNE UNIVERSITY OF TECHNOLOGY BRAIN
SCIENCES INSTITUTE
Drug Summary Sheet
Project Title: An Examination of the Central Serotonergic Effects of Escitalopram in Comparison to RS-Citalopram and Sertraline Using a Novel Electrophysiological Marker of Brain Serotonin Function
-Zoloft® (Sertraline hydrochloride) is a selective serotonin reuptake inhibitor (SSRI). Zoloft is used for the treatment of major depressive disorder. Some adverse effects that have been reported include headache, diarrhoea, insomnia, nausea, somnolence, malaise and dry-mouth. However, these adverse effects have been reported on chronic treatment, as we will be administering only acute doses the risk of participants incurring any adverse reactions is greatly reduced, and those that may be experienced are likely to be very mild. In addition, in our previous research Sertraline has been used safely without any side effects. -Lexapro® (Escitalopram): Lexapro is used to treat depression. It belongs to a group of medicines called selective serotonin reuptake inhibitor (SSRI) has reported some adverse effects such as insomnia, diarrhoea, dry-mouth, somnolence, dizziness, fatigue, indigestion and constipation. The overall incidence rate of adverse events in 10 mg escitalopram-treated patients (66%) was similar to that of the placebo-treated patients (61%). However, these adverse effects have been reported on chronic treatment, as we will be administering only acute doses the risk of participants incurring any adverse reactions is greatly reduced, and those that may be experienced are likely to be very mild. -Cipramil® (citalopram): is a selective serotonin reuptake inhibitor (SSRI) indicated for the treatment of depression. The most frequent adverse events associated with citalopram are nausea, vomiting, increased sweating, dry-mouth and headache. These adverse events have been reported after chronic administration, in the present study we will be administering only an acute dose. Accordingly, side effects are less likely to occur. Please note, the use of an acute dose of citalopram, 20mg, in healthy participants has previously been used in research conducted at the Brain Science Institute and participants reported no adverse effects. Research conducted elsewhere, administering a single oral dose of 20mg citalopram to healthy participants, has also found this dose to be well tolerated with no reported side effects
Appendix C.2
SWINBURNE UNIVERSITY OF TECHNOLOGY
BRAIN SCIENCES INSTITUTE
PARTICIPANT INFORMATION SHEET
Effects of Dopamine Depletion and Serotonin Depletion on Emotional Processing and Cognition Processing
Investigators:
Primary investigators: Ms Valérie Guille Ms Sumie Leung
Mr Alan Dunne
Senior and Associated Investigators: A/Prof. Pradeep Nathan A/Prof. Rodney Croft Ms Kirsty Scholes
Ms Hayley Lawrence Ms Clementine Thurgood
Dr. Susan Ilic Participant’s Name:
_______________________________________________________________________
Only the Primary Investigator should have knowledge of the names and code numbers (if any) used. It is the responsibility of the Primary Investigators to destroy this information at the end of the study. If confidentiality is required to be broken, this may only be done by the Primary Investigators after consultation with the Participant in writing.
Appendix C.2
EXPLANATION OF PROJECT – PARTICIPANT INFORMATION Purpose of the study The purpose of this study is to compare the effects of Acute Tryptophan Depletion (ATD), Acute Tyrosine/Phenylalanine Depletion (ATPD) and combined Acute Tryptophan/Tyrosine/Phenylalanine Depletion (ATTPD) on mood and emotional processing. ATD and ATPD have been popular tools to investigate the role of the specific brain chemicals, serotonin, noradrenalin and dopamine, in emotion, mood and cognitive function. These specific brain chemicals have been widely implicated in the regulation of emotion in humans and dysfunction in one or more of these chemical systems is a major feature of many mood disorders such as depression. ATD is thought to lower the amount of serotonin in the brain and is achieved by the dietary restriction of the serotonin precursor Tryptophan.). Similarly, ATPD has been proposed to lower levels of dopamine and noradrenalin by the dietary restriction of their precursors, Tyrosine and Phenylalanine. Previous studies have looked at how ATD and ATPD affects a person’s self-rated mood, but not specifically how these procedures affect their emotional processing, that is, how their brain processes emotionally relevant stimuli (i.e., a picture of a baby smiling – positive stimuli) This study will examine how the brain processes pictures which are negative, positive or neutral in nature and this will be tested by using electrophysiological (brain) techniques that measure patterns of activity associated with the presentation of pictures. Measures will be taken following ATD and ATPD and the combined ATTPD conditions. By participating in this study, you are improving the scientific investigation of the roles of serotonin, dopamine and noradrenalin in emotion in healthy humans. This is important as it can advance the understanding of how these chemicals relate to emotional deficits in disorders such as depression. Requirements of the study We need healthy, non-smoking participants aged between 18 to 45 years, who are not on any medication to be participants in this research study. You will need to come to the Brain Sciences Institute (BSI), Swinburne University of Technology, 400 Burwood Road, Hawthorn on five occasions (a brief medical examination, and four testing sessions with at least one week separating the testing sessions) and will be reimbursed $200 for your time and travel expenses incurred by your involvement in the study. The medical examination will take approximately 25 minutes. On the same day the study will be fully explained and you may ask the researchers any questions or raise any concerns that you may have. Testing will be conducted at the Brain Sciences Institute. You will have your electrical brain activity (EEG) recorded while you complete a simple emotional processing task on a computer. The EEG cap contains 64 electrodes, which record the natural activity of your brain. Nothing in the cap will hurt you. A small amount of water-based gel will be used to help attach each electrode to the scalp. This gel will be washed out after the recording is completed. None of the electrical equipment causes any harm or discomfort. You will also be required to complete some simple computer tests on memory and reaction time that will be explained to you thoroughly by the researcher. You will also be required to have a sample of your blood taken at two time periods during the day. This will be done by a registered nurse or doctor at the institute and you will be free to request a local anaesthetic to avoid any discomfort you may experience while the nurse takes the blood sample. You will also be asked not to consume any high protein food (including high protein drinks) for the 24 hours leading up to testing but will be provided with a list of appropriate food types that you are able to eat. Finally, you will be asked not to eat after 7pm on the night before testing. During this time you will be allowed to consume water and juices freely, but will be asked not to consume any drinks that contain caffeine (such as coffee, tea, or coke) or protein (i.e.,
Appendix C.2
protein shakes). This procedure has been conducted in previous research with no adverse effects to the participants. Procedure Before taking part in the study, the researcher will explain the study and the task to you, you will read about the amino acid depletion procedures (ATD ATPD) that you will undergo. If you find everything satisfactory, you will be asked to fill in a consent form. A medical examination will then be arranged with a doctor at Swinburne University. Following the medical examination, you may begin the study. You will have your brain activity recorded a total of four times, across four different testing days. Timetable 10:00am: Arrive at Brain Sciences Institute, 10:00am: Mood Questionnaire 10:15am: Blood Sample 10:30am: ATD, ATPD, ATTPD or placebo administration 2:30pm Cognitive tests on computer 3:15pm: Preparation for EEG recording 3:30 pm: Blood Sample 4:00 pm: EEG Recording, computer task 5:15pm Topographic map of scalp electrodes 5:30pm Finish recording, Removal of equipment, Hair washing, debriefing The total EEG recording time per session is approximately 1 hour. You will also be asked to complete some simple tests on a computer, which will test how well you remember words and pictures and also test your reaction time to stimuli on the computer screen. This will take about 40 minutes Please Note: Please be at BSI on time for all your test days. The recordings run to a time schedule and it is important for this study and others at the BSI that this schedule is adhered to. Medication Each time you attend a testing session, you will be given one of the following amino acid mixture drinks; placebo-control mixture (nutritionally balanced amino acid mixture NBM), Tryptophan depleted mixture (TDM), Tyrosine/Phenylalanine depleted mixture (TPDM), combined Tryptophan/Tyrosine/Phenylalanine depleted mixture (TTPDM). You will be required to drink the amino-acid mixture (mixed with orange juice) and take 20 standard sized capsules of amino acids. The researcher will inform you of any side effects that may occur due to the amino acid mixtures such as feeling sick. Nausea following the amino acid drink is rare and if it does occur is generally very mild. You will be free to withdraw from the study at any time if you feel in any way unwell. Additionally, there will be a medical doctor on-call during testing hours, and there are also staff members and a registered nurse trained in first aid in case of emergency. In the case that any adverse physical effects are experienced in the hours following the testing session, please initially contact any of the researchers listed at the end of this information sheet, and they will then contact a medical doctor.
Appendix C.2
Confidentiality It is normal in studies like this for your identity to be kept confidential. No one apart from the researchers who collect the data will know who the participants are, or be told any personal information about the participants. The data from this study will be stored in a secure place within the BSI and will only be available to people directly involved with the study. The results of this study may be published or provided to other researchers but your identity will be kept confidential. Please note that your participation in this study is entirely voluntary. You are free to withdraw consent and participation at any stage during the study. QUERIES If you have any questions about the study, or don’t understand something properly please feel free to ask us to explain. Contact details are: Ms Valérie Guille Ph: 9214 5543 Ms Sumie Leung Ph: 9214 5543 Mr Alan Dunne Ph: 9214 8291 Email: [email protected] You are also able to contact the project supervisors at any time A/Prof. Pradeep Nathan Ph: 9214 5216 A/Prof. Rodney Croft Ph: 9214 5149 If you have any complaints about the way that you have been treated during this study, or a question that the investigators have been unable to answer, you may write to either of the addresses below: The Chair The Director Human Research Ethics Committee Brain Sciences Institute Swinburne University of Technology Swinburne University of Technology P O Box 218 400 Burwood Road HAWTHORN. VIC. 3122 HAWTHORN. VIC. 3122 Phone: (03) 9214 5223 Phone: (03) 9214 8273
Appendix C.3
SWINBURNE UNIVERSITY OF TECHNOLOGY
BRAIN SCIENCES INSTITUTE
PARTICIPANT INFORMATION SHEET
Examining the interaction between oestrogen and
the serotonin-1A receptor, in models of
schizophrenia.
Investigators:
Primary Investigators: Miss Andrea Gogos, Miss Valérie Guille
Senior and Associated Investigators: A/Prof. Pradeep Nathan
Dr. Maarten Van Den Buuse
Dr. Rodney Croft
Participant’s Name:
_______________________________________________________________________
Only the Primary Investigator should have knowledge of the names and code numbers (if any) used. It is the responsibility of the Primary Investigators to destroy this information at the end of the study. If confidentiality is required to be broken, this may only be done by the Primary Investigators after consultation with the Participant in writing.
Appendix C.3
EXPLANATION OF PROJECT – PARTICIPANT INFORMATION Purpose of the study The purpose of this study is to investigate how oestrogen may be involved in schizophrenia. Schizophrenia is a debilitating mental illness that affects 1% of the population. There is no cure for schizophrenia, it is a life-long disorder. It is important that we learn more about the mediating factors of this disease, in order to improve the development of antipsychotic medication. There is a well-known gender difference in schizophrenia where men develop the disorder earlier than females. It has been proposed that oestrogen plays a neuroprotective role in schizophrenia. Recently, oestrogen has been used clinically to improve the symptoms in schizophrenia patients. The way oestrogen can improve schizophrenia symptoms is unknown, therefore, we are investigating the effects of oestrogen on serotonin receptors, where serotonin is a neurotransmitter implicated in schizophrenia. We will do this by testing the electrophysiological (brain) and physiological (bodily) patterns of activity associated with activation of oestrogen and serotonin receptors. By participating in this study you are improving the scientific investigation of schizophrenia, a significant area of research, where the overall aim is better treatment for people who suffer from this chronic illness. Requirements of the study We need healthy, non-smoking females aged 18 to 40 years, who are not on any medication, to be participants in this research. Participants will need to come to the Brain Sciences Institute (BSI), Swinburne University of Technology, 400 Burwood Road, Hawthorn four times (at least one week apart) and will be reimbursed $200 for your time and travel expenses incurred by your involvement in the study. Testing will be conducted at the Centre for Neuropsychology. You will have your electrical brain activity (EEG) recorded while you complete a number of simple tasks on a computer. The EEG cap contains 60 electrodes, which record the natural activity of your brain. Nothing in the cap will hurt you. A small amount of water-based gel will be used to help attach each electrode to the scalp. This gel will be washed out after the recording is completed. Some electrodes will also be placed around the eye to record eye-blink responses, and heart rate will also be recorded. You will need to wear headphones so that sound pulses can be heard. None of this equipment causes any harm or discomfort. You will complete seven simple computer tasks while EEG is recorded. A description of these tasks can be found below. Experimental Tasks 1/ Baseline EEG. You will have 4.5 minutes of EEG (brain activity) recorded while you are relaxing with your eyes closed and then relaxing with eyes open. 2-6/ These tasks (total 28 minutes) are similar and involve sound pulses (tones or clicks) being presented every few seconds via headphones, while you simply read a magazine or are required to press a button when you hear certain sounds. 7/ The last task lasts for 30 minutes and measures your eye-blink startle response to sound pulses. While you sit comfortably and relax, you will be presented with a random order of 48 sound pulses through the headphones. The loudest sound pulse presented is 108 dB, however, this will only be presented for 40 msec. Procedure Before taking part in the study, the researcher will explain the study and the tasks to you, you will read about the drug treatments that you are to receive, and if you find everything satisfactory, you will be asked to fill in a consent form. A medical examination will then be arranged with a doctor at Swinburne University. Following the medical, you may begin the study. You will have your brain activity recorded a total of four times, across four different testing days (see timetable below).
Appendix C.3
It is very important that you eat a light breakfast before arriving at the Brain Sciences Institute (BSI) at 11:30am on Monday. And it is also important that you have not consumed alcohol, chocolate or caffeinated products for 24 hours before testing (ie by 4pm Sunday). You will be taken over to the Centre for Neuropsychology (CNP), where the EEG laboratories are located. You will be given one tablet (either a medication or the placebo) and then have a three hours break, from 12pm to 3:30pm. During this break, you may choose to watch a video (from our selection, or bring your own), or bring a book to read. You will also be provided with a light lunch of fruit, toast, juice, or herbal tea. Food slows the rate at which some medications are absorbed into the body and certain foods effect neurotransmitter levels in the brain. Because of this it is vital that you only eat the light lunch provided, and that this lunch is the same for each testing session. You will be given the second tablet (either a medication or the placebo) at 3pm. The EEG recording equipment including the EEG cap and reference electrodes are then set up while you complete a mood/anxiety scale questionnaire. Testing will take approximately 1 hour. After this, a 3Dmap of your scalp will be done for approximately 30mins. Then, the equipment is removed and your hair can be towel dried or washed. Timetable 11.30am: Arrive at Brain Sciences Institute, Swinburne Uni, Hawthorn 12.00pm: Drug/placebo administration 12.00pm - 3.30pm: 3 hour break (includes light lunch) 3.00pm: Drug/placebo administration 3.30pm: Cap, gelling and other preparation for EEG recording 4.00pm - 5.00pm: EEG recording/testing 5.00pm - 5.30pm: 3Dmap recording 5.30pm – 5.45pm: Finish recording, removal of equipment, hair washing Please Note Please be at the BSI by 11.30am AT THE LATEST on all of your test days. The recordings run to a time schedule and it is important for this study and others run at the CNP that this schedule is adhered to. Medications Each time you attend a testing session, you will be given one of the following medications; Oestradiol (Estrofem, 2 mg), Buspirone (Buspar, 5 mg), Oestradiol + Buspirone, or a Placebo (a pill containing flour and gelatine). Neither you, nor the primary investigator will know which of these compounds you receive. Buspirone is a medication used to treat people who feel anxious, and oestradiol is used to treat symptoms occurring due to a lack of oestrogen. It is suggested that you read the drug summary sheets provided so that you understand what these medications are, how they work and any side effects that may result. We do not expect participants to suffer any significant side effects as a result of taking these medications, however you should be aware that there is always some chance of an adverse reaction. We recommend that you do not drive, but arrange for other transportation. Confidentiality It is normal in studies like this for participant’s identity to be kept confidential. No one apart from the researchers who collect the data will know who the participants are, or be told any personal information about the participants. The data from this study will be stored in a secure place within the BSI and CNP, and will only be available to people directly involved with the study. The results from this study may be published or provided to other researchers but your identity will be kept
Appendix C.3
confidential. Please note that your participation in this study is entirely voluntary. You are free to withdraw your consent and participation at any time during the study. If you have any questions about the study, or don’t understand something properly please feel free to ask me to explain. My contact details are: Andrea Gogos Ph: 9389 2993, (M) 0416 199 364 Valérie Guille Ph: 9214 5543, (M) 0404 240 435 Email: [email protected] If you would prefer, you can contact the project supervisor at any time. A/Prof. Pradeep Nathan Ph: 9214 5216 If you have any complaints about the way that you have been treated during this study, or a question that the investigators have been unable to answer, you may write to either of the addresses below: The Chair The Director Human Experimentation Ethics Committee Brain Sciences Institute Swinburne University of Technology Swinburne University of Technology P O Box 218 400 Burwood Road
HAWTHORN. VIC. 3122 HAWTHORN. VIC. 3122 Phone: (03) 9214 5223 Phone: (03) 9214 8273
Appendix D
Appendix D: Medical forms
D-1. Patient questionnaire (Female/Male) sheet
D-2. Medical history sheet
D-3. Medical exam sheet
Appendix D.1
Participant Questionnaire
Female participant
Trial Name and Number: Participant number: Name: D.O.B.: Address: Phone: Date:
Instructions: These questions are designed to help us understand any medical problems that you may have. All information given will be treated in the strictest confidence. Please tick all relevant boxes. Please ask for assistance if you are unsure about any of the questions.
Medical History: Are you allergic to anything that you know of? Medications? Yes No Foods? Yes No Surgical Tapes? Yes No Any other substances? Yes No If yes, please give details Do you take any medications (prescription or over-the counter)? Yes No
If you answered yes, please fill in the details in the table below.
Name of medication Dose Number of times taken each day
Date of commencement
Do you have any of the following medical problems?
Heart problems? Yes No High or low blood pressure? Yes No Respiratory problems? Yes No Stomach or intestinal problems? Yes No Liver problems? Yes No Kidney or urinary problems? Yes No Diabetes? Yes No Anaemia or blood disorders? Yes No Epilepsy or fitting? Yes No Eyesight problems or colour blindness? Yes No Cancer? Yes No Skin disorders? Yes No Anxiety or depression? Yes No Any other psychological problem? Yes No
Appendix D.1
If you answered yes to any of the questions above, please give details Have you ever had any operations? Yes No If yes, please give details When did you last consult a doctor? And for what reason?
Are you, or could you be pregnant? Yes No Are you breastfeeding? Yes No
Are your periods regular? Yes No Last period ended on (date) Period usually lasts for days, every days. Do you take the contraceptive pill Yes No Brand name
Do you follow any special diet? Yes No If yes, what type?
How many glasses of alcohol do you drink? ______ glasses / day / week Type_____________
Do you smoke? Yes No Number of cigarettes / day________ Do you drink coffee? Yes No Number of cups / day ________
Do you use glasses? Yes No Contact lenses? Yes No Do you use a hearing aid? Yes No Do you use any other type of prosthesis? Yes No
Appendix D.1
Participant Questionnaire
Male Participant
Trial Name and Number: Participant number: Name: D.O.B.: Address: Phone: Date: Instructions: These questions are designed to help us understand any medical problems that you may have. All information given will be treated in the strictest confidence. Please tick all relevant boxes. Please ask for assistance if you are unsure about any of the questions. Medical History: Are you allergic to anything that you know of?
Medications? Yes No
Foods? Yes No
Surgical Tapes? Yes No
Any other substances? Yes No
If yes, please give details
Do you take any medications (prescription or over-the counter)? Yes No
If you answered yes, please fill in the details in the table below.
Name of medication Dose Number of times taken each day
Date of commencement
Do you have any of the following medical problems?
Heart problems? Yes No High or low blood pressure? Yes No Respiratory problems? Yes No Stomach or intestinal problems? Yes No Liver problems? Yes No Kidney or urinary problems? Yes No Diabetes? Yes No Anaemia or blood disorders? Yes No Epilepsy or fitting? Yes No Eyesight problems or colour blindness? Yes No Cancer? Yes No Skin disorders? Yes No Anxiety or depression? Yes No Any other psychological problem? Yes No
Appendix D.1
If you answered yes to any of the questions above, please give details Have you ever had any operations? Yes No If yes, please give details When did you last consult a doctor? And for what reason?
Do you follow any special diet? Yes No If yes, what type?
How many glasses of alcohol do you drink? ______ glasses / day / week Type_____________
Do you smoke? Yes No Number of cigarettes / day________ Do you drink coffee? Yes No Number of cups / day ________
Do you use glasses? Yes No Contact lenses? Yes No Do you use a hearing aid? Yes No Do you use any other type of prosthesis? Yes No
Appendix D.2
Medical History
Trial Name and Number:
Participant Name: Number
D.O.B Sex male female Date:
Background / concurrent disease:
Medications YES NO If yes, give details below Allergic History Cardiovascular Ophthalmologic Respiratory Gastrointestinal Hepatobiliary Renal / Genitourinary Metabolic / Endocrine Neurologic Musculoskeletal Dermatological Hematological Neoplastic Other (specify)
Signature
Appendix D.3
Physical Examination
Trial Name and Number:
Participant name and number:
Date:
Normal / abnormal comments
Chest
Heart
Abdomen
Nervous System
Lymph nodes
ENT and Eyes
Extremities
Skin
Other (specify)
Baseline Obs: BP standing BP sitting
Pulse T°
Height Weight Comments: Signature
Appendix E
Appendix E: Visual Analogue Mood Scale
Appendix E
Visual Analogue Mood Scale
Instructions:
*Please rate the way you feel in terms of the dimensions given below* *Regard the line as representing the full range of each dimension*
*Rate your feelings as they are at the moment* *Mark clearly and perpendicularly across each line*
Alert Drowsy
Calm Excited
Strong Feeble
Muzzy Clear-headed
Well-coordinated Clumsy
Lethargic Energetic
Contented Discontented
Troubled Tranquil
Mentally slow Quick-witted
Tense Relaxed
Attentive Dreamy
Incompetent Proficient
Happy Sad
Antagonistic Amicable
Interested Bored
Withdrawn Sociable
S T
Appendix F
Appendix F: Auditory stimulus presentation spreadsheet
Example of a Gentask program spreadsheet
Example of a simplified program spreadsheet for the stimulus presentation software that was used in the N1/P2 paradigm for each investigation.
Appendix F
Label Duration ITI Type IMAGE 100 1600 NOSE SND 0 2100 80SND 0 1816.67 100SND 0 1650 70SND 0 1816.67 60IMAGE 100 ASAP NOSE SND 0 1883.33 90SND 0 2050 80SND 0 1883.33 100SND 0 1983.33 60SND 0 2100 80SND 0 1933.33 70SND 0 1883.33 100SND 0 1766.67 90SND 0 1383.33 60IMAGE 100 383.33 NOSE SND 0 1650 80SND 0 1650 100SND 0 1816.67 70SND 0 500 90IMAGE 100 1600 NO NOSE SND 0 1883.33 80SND 0 1716.67 70SND 0 1800 60IMAGE 100 300 NOSE SND 0 700 100IMAGE 100 1233.33 NOSE SND 0 2050 90SND 0 1716.67 80IMAGE 100 ASAP NOSE SND 0 1933.33 90SND 0 1766.67 60SND 0 1766.67 70SND 0 1816.67 100SND 0 1933.33 90SND 0 1933.33 60SND 0 1983.33 80SND 0 1650 70SND 0 1816.67 100SND 0 2050 90SND 0 1983.33 60SND 0 233.33 70IMAGE 100 1000 NOSE SND 0 1600 100SND 0 1650 80
Label Duration ITI Type SND 0 1100 90IMAGE 100 716.67 NOSE SND 0 1766.67 60SND 0 1816.67 70SND 0 1600 100SND 0 1650 80SND 0 1650 90SND 0 1816.67 60SND 0 1766.67 70SND 0 1766.67 100SND 0 1883.33 80SND 0 550 90IMAGE 100 1383.33 NOSE SND 0 1933.33 60SND 0 2050 70SND 0 1000 100IMAGE 100 1100 NO NOSE SND 0 2100 80SND 0 1600 90SND 0 1716.67 60SND 0 1600 70SND 0 1766.67 80SND 0 1983.33 100SND 0 2100 90SND 0 666.67 60IMAGE 100 1266.67 NOSE SND 0 1600 70SND 0 1600 100SND 0 2100 80SND 0 1716.67 90SND 0 733.33 60IMAGE 100 866.67 NOSE SND 0 2050 100SND 0 1816.67 70SND 0 1716.67 80SND 0 1716.67 60SND 0 1933.33 90SND 0 2100 70SND 0 800 100IMAGE 100 1183.33 NOSE SND 0 1600 80SND 0 1933.33 60SND 0 1650 90SND 0 1816.67 70SND 0 1600 80
Appendix F
Label Duration ITI Type SND 0 1933.33 100SND 0 1983.33 60SND 0 1816.67 90SND 0 1933.33 70SND 0 2100 80SND 0 1433.33 100IMAGE 100 616.67 NOSE SND 0 1933.33 60SND 0 1600 90SND 0 1716.67 70SND 0 1816.67 80SND 0 1316.67 100IMAGE 100 500 NOSE SND 0 2100 60SND 0 1716.67 90SND 0 2100 70SND 0 1933.33 100SND 0 1816.67 80SND 0 2100 60SND 0 733.33 90IMAGE 100 933.33 NOSE SND 0 ASAP 70IMAGE 100 1500 NOSE SND 0 2050 100SND 0 1883.33 80SND 0 1600 60SND 0 766.67 90IMAGE 100 1000 NO NOSE SND 0 1650 70SND 0 1766.67 100SND 0 1766.67 80SND 0 1766.67 60SND 0 1250 90IMAGE 100 633.33 NOSE SND 0 1766.67 70SND 0 1983.33 100SND 0 616.67 80IMAGE 100 1000 NOSE IMAGE 100 483.33 NOSE SND 0 1600 70SND 0 1600 90SND 0 1316.67 60IMAGE 100 400 NOSE SND 0 2100 100SND 0 1650 80
Label Duration ITI Type SND 0 1716.67 70SND 0 1650 90SND 0 1983.33 60SND 0 1716.67 100SND 0 1766.67 80SND 0 1766.67 90SND 0 1983.33 70SND 0 1983.33 100SND 0 1883.33 60SND 0 400 80IMAGE 100 1200 NOSE SND 0 1883.33 90SND 0 1766.67 100SND 0 2100 70SND 0 1983.33 60SND 0 1983.33 80SND 0 1600 100SND 0 1600 90SND 0 2050 70SND 0 833.33 60IMAGE 100 933.33 NOSE SND 0 1816.67 80SND 0 983.33 90IMAGE 100 1000 NO NOSE SND 0 1600 70SND 0 1766.67 100SND 0 883.33 60IMAGE 100 766.67 NOSE SND 0 2050 80SND 0 1766.67 70SND 0 1983.33 90SND 0 1883.33 100SND 0 1816.67 80SND 0 1600 60SND 0 1133.33 70IMAGE 100 866.67 NOSE SND 0 133.33 90IMAGE 100 ASAP NO NOSE IMAGE 100 1783.33 NOSE SND 0 1600 100SND 0 1816.67 60SND 0 1600 80SND 0 1650 70SND 0 533.33 90IMAGE 100 1166.67 NOSE
Appendix F
Label Duration ITI Type SND 0 1883.33 60SND 0 1816.67 100SND 0 133.33 80IMAGE 100 1966.67 NOSE SND 0 1983.33 70SND 0 1883.33 90SND 0 2050 100SND 0 1650 60SND 0 1766.67 80SND 0 1700 90IMAGE 100 ASAP NOSE SND 0 2050 70SND 0 1650 100SND 0 1933.33 80SND 0 2050 60SND 0 1716.67 90SND 0 2050 70SND 0 1650 80SND 0 1766.67 60SND 0 2050 100SND 0 1883.33 70SND 0 1983.33 90SND 0 ASAP 60IMAGE 100 1900 NOSE SND 0 1933.33 80SND 0 2050 100SND 0 1766.67 70SND 0 1983.33 90SND 0 1716.67 60SND 0 1983.33 80SND 0 1816.67 100SND 0 1850 70IMAGE 100 ASAP NOSE SND 0 1983.33 90SND 0 1716.67 80SND 0 2050 60SND 0 1600 100SND 0 1983.33 90SND 0 1766.67 70SND 0 1816.67 60SND 0 1716.67 80SND 0 1883.33 100SND 0 333.33 70IMAGE 100 1316.67 NOSE SND 0 1816.67 90
Label Duration ITI Type SND 0 1933.33 60SND 0 1933.33 80SND 0 1716.67 100SND 0 1816.67 90SND 0 1883.33 70SND 0 1883.33 60SND 0 1883.33 80SND 0 1933.33 100SND 0 1650 70SND 0 1233.33 90IMAGE 100 866.67 NOSE SND 0 1716.67 60SND 0 2100 100SND 0 1716.67 80SND 0 2050 70SND 0 1883.33 60SND 0 1816.67 80SND 0 866.67 100IMAGE 100 1166.67 NOSE SND 0 883.33 90IMAGE 100 1000 NO NOSE SND 0 1950 70IMAGE 100 ASAP NOSE SND 0 850 90IMAGE 100 800 NOSE SND 0 1816.67 80SND 0 1983.33 100SND 0 1883.33 60SND 0 2100 70SND 0 400 90IMAGE 100 1300 NOSE SND 0 1716.67 80SND 0 1766.67 100SND 0 2100 60SND 0 2100 70SND 0 1883.33 80SND 0 2100 90SND 0 2100 100SND 0 2100 60SND 0 1600 70SND 0 1983.33 100SND 0 250 90IMAGE 100 1000 NOSE IMAGE 100 400 NOSE SND 0 1883.33 80
Appendix F
Label Duration ITI Type SND 0 1933.33 60SND 0 1650 70SND 0 2050 100SND 0 1083.33 90IMAGE 100 633.33 NOSE SND 0 1600 80SND 0 1983.33 60SND 0 783.33 70IMAGE 100 1266.67 NOSE
SND 0 1933.33 100SND 0 1933.33 80SND 0 400 90IMAGE 100 1700 NO NOSE SND 0 1650 60SND 0 1816.67 70
Label Duration ITI Type SND 0 1716.67 100SND 0 2050 90SND 0 1883.33 80SND 0 666.67 60IMAGE 100 1383.33 NOSE SND 0 1716.67 70SND 0 1766.67 100SND 0 2050 80SND 0 1650 90SND 0 1933.33 60SND 0 1600 100SND 0 900 70IMAGE 100 700 NOSE SND 0 1983.33 80SND 0 1716.67 60SND 0 500 90
SND = command name for sounds Duration = Determine the duration in ms that the image stay on the screen ITI = Inter Trial Interval: is the time (in ms) from the onset of the present stimulus to the onset of the next stimulus. Type = the type of stimulus. Nose is the image that represents a face with a nose as opposed to NO NOSE (a face without nose). 60 to 100 is the intensity of the stimulus presented.
Appendix G
Appendix G: Tryptophan depletion study-Low protein diet
Appendix G
Thank you for volunteering to participate in our research and we hope it will turn out to be a
learning experience for all involved. As we will be attempting to modify your amino acid
concentrations with a dietary intervention, it is essential for the success of the study that you follow
the suggested diet on the day before testing (attached). This diet has been carefully selected to be
nutritionally balanced and healthy. You do not have to eat everything on the list, nor do you have
to be strict with each category. E.g. You could have a salad for lunch with lettuce, carrot, celery,
tomato and cucumber. You may substitute/swap items on the list, but it is important that you do not
consume any foods high in protein. Also, it is very important that you do not eat after 7 pm the
day before the test. If you have any further questions feel free to contact any of the investigators
and we will be happy to assist you. Thank you again for your assistance and we look forward to
working with you.
SWINBURNE UNIVERSITY OF TECHNOLOGY
BRAIN SCIENCES INSTITUTE
The Effects of Dopamine Depletion and Serotonin Depletion on Emotional Processing
and Cognition
Appendix G
Low Protein Diet
Weight (g) Protein (g) Fat (g) Carbohydrate (g) kcal BREAKFAST Banana 2 228 2.4 2 54 210 Orange juice 1/2 cup 120 0.8 0 13 52 White toast 2 slices 42 4.0 2 24 128 Margarine 10 0 8 0 68 Jelly (package) 42 0 0 30 116 Decaf coffee or tea 0 0 0 1/2 & 1/2 cream 1 package 20 0.5 2 1 27 Sugar 2 packages 8 0 0 8 32 LUNCH Shredded lettuce 80 0.7 0 2 10 Raw carrots 55 0.6 0 5 23 Raw celery (1 stalk) 40 0.3 0 2 6 Tomato (1) 123 1.3 0 6 27 Cucumber (1/2 cup) 52 0.3 0 2 7 Oil (1 tbsp) 15 0 14 0 129 Vinegar (1 package) 20 0 0 0 1 Raisins (1 package) 45 1.5 0 36 136 Apple (1) 140 0 0 21 82 Peach (1) 90 0.6 0 10 38 Twix 48 1.0 6 16 118 Decaf coffee or tea 0 0 0 1/2 & 1/2 cream 1 package 20 0.5 2 1 27 Sugar 2 packages 8 0 0 8 32 DINNER Stir fried vegetables Onions (4 tbsp) 40 0 0 3 12 Carrots 55 0.5 0 4 17 Celery (1 stalk) 40 0.3 0 1 6 Broccoli (1/2 cup) 44 1.4 0 2 11 Cauliflower (1/2 cup) 50 1.2 0 2 11 Mushrooms (1/2 cup) 35 0.9 0 1 39 Green pepper (1/2 cup) 50 0 0 3 13 Oil (3 tbsp) 45 0 44 0 386 Applesauce (1/2 cup) 128 0.2 0 25 97 1/2 & 1/2 cream 1 package 20 0.5 2 1 27 Sugar 2 packages 8 0 0 8 32 Peach (1) 90 0.6 0 10 38 SNACK Raisins (1 package) 45 1.5 0 36 136 Twix 48 1.0 6 16 118 TOTAL 22.6 88 351 2212
Appendix H
Appendix H: Poster presentation, proceeding of the XXV CINP
Congress, Chicago (2006).
Modulation of the Loudness Dependence of the Auditory Evoked Potential
(LDAEP) by Serotonin and Dopamine depletion: Implications for its use as an in
vivo marker for central serotonin function
O’Neill Barry V., Guille Valérie, Leung Sumie, Phan, K Luan,, Croft Rodney J., Nathan Pradeep J.
Proceeding of the XXV CINP Congress, Chicago (2006), The international Journal of Neuropsychopharmacology. V9. S1. S199
Appendix H
MODULATION OF THE LOUDNESS DEPENDENCE OF THE AUDITORY EVOKED POTENTIAL (LDAEP) BY SEROTONIN & DOPAMINE DEPLETION: IMPLICATIONS
FOR ITS USE AS AN IN VIVO MARKER OF CENTRAL SEROTONIN FUNCTIONO'Neill, Barry V. 1; Guille Valérie1; Leung Sumie1; Phan, K Luan3; Croft, Rodney J1. Nathan, Pradeep J2
1.Brain Sciences Institute, Swinburne University, Australia. 2.Behavioural Neuroscience Laboratory, Department of Physiology, Monash University, Australia. 3.Clinical Neuroscience and Psychopharmacology Research Unit, Department of Psychiatry, The University of Chicago, USA
0.00
0.20
0.40
0.60
0.80
Placebo Combined Tryp Tyr/Phen
Condition
N1/P
2 slo
pe (µ
V/10
dB)
• Loudness Dependence of the Auditory Evoked Potential (LDAEP) has been suggested as a possible in vivo measure of central serotonin function in humans (Hegerl and Juckel, 1993).
• LDAEP has been used to examine purported serotonergic abnormalities in depression (Hegerl et al., 2001) and anxiety disorders (Senkowski et al. 2003) and in the prediction of antidepressant treatment response (Gallinat et al. 2000).
• It is a measure of auditory cortex activity, reflecting increase or decrease in the slope of AEP’s (N1/P2) with increasing tone loudness (Figure 1).
INTRODUCTION RESULTS
Figure 2: (a) Mean N1/P2 amplitude plotted against stimulus intensity (loudness), for the placebo, combined (p=0.104), tryp (p=0.318) and tyr/phen (p=0.061) depletion conditions. Least-squares regression lines indicate no significant difference in slope between placebo and each depletion condition.
• Data were digitally re-referenced to linked mastoids.
• Stimulus tones (1000 Hz, 100ms duration with 10ms rise and 10ms fall, SOA randomized between 1600ms and 2100ms) of five intensities (60, 70, 80, 90, 100 dB) presented binaurally using single use foam ear inserts, in a pseudorandomised form.
• Data collected with a sampling rate of 1,000 Hz, and bandpass filter of 0.15 to 200Hz.
• Magnitude of the N1 and P2 peaks were determined for each intensity at CZ.
• N1/P2 slope calculated (P2-N1) as linear regression slope with stimulus intensity (independent variable) and N1/P2 amplitude (dependant variable).
** **
DATA ANALYSIS
**
Croft RJ, Klugman A, Baldeweg T, Gruzelier JH (2001). American Journal of Psychiatry 158 (10), 1687-1692.Hegerl U. and Juckel G. (1993). Biological Psychiatry 33, 173-187.Hegerl U, Gallinat G. and Juckel J. (2001). Journal of Affective Disorders 62, 93-100.Nathan PJ, Segrave. R, Phan KL, O'Neill B and Croft RJ (2006). Human Psychopharmacology 21 (1), 47-52.Senkowski D, Linden M, Zubragel D, Bar T and Gallinat J (2003). Biological Psychiatry 53, 304-314.
REFERENCES
• Placebo-controlled, double-blind, repeated measures design.
• 14 subjects under four treatment conditions: placebo (balanced amino acid drink), tryp (serotonin), tyr/phen (dopamine) and combined tryp/tyr/phen (serotonin and dopamine) depletion.
• Testing 5h post depletion and EEG recorded from 64 scalp sites (international 10/20 system).
•Electrode below the left eye was used to record eye movement, using CZ as reference and AFZ as ground, and electromyography (EMG) recorded from two electrodes beneath the right eye field.
METHODS
Figure 1:Figure 1: Basic Concept of Serotonergic modulation of LDAEP (Adopted from Hegerl et al. 2001).
• The relationship between the LDAEP and changes in serotonin neurotransmission in humans has yielded consistent results (Nathan et al. 2006; Croft et al. 2001; Gallinat et al. 2000).
• The sensitivity of the LDAEP to changes in dopamine neurotransmission are yet to be fully characterised in humans.
• To further examine the effects of serotonin and dopamine on the LDAEP, the current study examined the effects of;
– Serotonin depletion (via tryptophan depletion)– Dopamine depletion (via tyrosine/phenylalanine depletion) – Simultaneous serotonin and dopamine depletion (via tryptophan/tyrosine/phenylalanine depletion)
Figure 3: (a) Mean Values of LDAEP (µV/10dB) at CZ (60-80dB) for placebo, combined, tryp and tyr/phen depletion.
(b) Mean Values of LDAEP (µV/10dB) at CZ (80-100dB) for placebo, combined, tryp and tyr/phen.[*p<.05, **p<.02]
(a)(a) (b)(b)6060--80dB80dB 8080--100dB100dB
• Acute serotonin or dopamine depletion and simultaneous serotonin and dopamine depletion had no effect on the LDAEP (intensity range 60-100dB).
•At higher intensities (80-100dB) compared to lower intensities (60-80dB), there was a significant suppressive effect of dopamine depletion and simultaneous serotonin and dopamine depletion on the LDAEP.
• The effects of dopamine and serotonin on the LDAEP may be dependent on the intensity modulated basal activity of pyramidal cells, such that higher levels of basal activity may be more sensitive to neuromodulation.
• These findings provide a basis for further investigation on the sensitivity of the LDAEP as a marker of monoamine function and/or disorders of monoamine dysfunction.
DISCUSSION AND CONCLUSIONS
0.00
0.04
0.08
0.12
0.16
0.20
Placebo Combined Tryp Tyr/Phen
Condition
N1/P
2 sl
ope
(µV/
10dB
)
0
6
1 2
1 8
2 4
6 0 7 0 8 0 9 0 1 0 0
S t im u lu s in te n s i ty (d B S P L )
N1
/P2
am
pli
tud
e (
µV)
P la c e b o
T r y p
C o m b in e d
T y r /P h e n
0
6
1 2
1 8
2 4
6 0 7 0 8 0 9 0 1 0 0
S t im u lu s in te n s i ty (d B S P L )
N1
/P2
am
pli
tud
e (
µV)
P la c e b o
T r y p
C o m b in e d
T y r /P h e n
Email address for reprints: [email protected]
• Tryp depletion resulted in 93% tryp depletion ( p<0.02). Tyr/Phen depletion resulted in 90% tyr and 93% phen depletion (p<0.02). Combined tryp/tyr/phen depletion resulted in 87% tryp, 91% tyr and 93% phen depletion (p<0.02).
• No effect of treatment on measures of mood (Visual Analogue Mood Scales) (all p’s>0.05).
• Linear increase in N1/P2 amplitude with increasing stimulus intensity (p<0.001), but no significant effect of treatment on N1/P2 slope (Figure 2).
• Further exploratory analysis revealed a significant effect of dopamine and combined dopamine/serotonin depletion at higher intensities (80-100dB) as compared to lower intensities (60-80dB) (Figure 3 (a) and (b)).
MODULATION OF THE LOUDNESS DEPENDENCE OF THE AUDITORY EVOKED POTENTIAL (LDAEP) BY SEROTONIN & DOPAMINE DEPLETION: IMPLICATIONS
FOR ITS USE AS AN IN VIVO MARKER OF CENTRAL SEROTONIN FUNCTIONO'Neill, Barry V. 1; Guille Valérie1; Leung Sumie1; Phan, K Luan3; Croft, Rodney J1. Nathan, Pradeep J2
1.Brain Sciences Institute, Swinburne University, Australia. 2.Behavioural Neuroscience Laboratory, Department of Physiology, Monash University, Australia. 3.Clinical Neuroscience and Psychopharmacology Research Unit, Department of Psychiatry, The University of Chicago, USA
0.00
0.20
0.40
0.60
0.80
Placebo Combined Tryp Tyr/Phen
Condition
N1/P
2 slo
pe (µ
V/10
dB)
• Loudness Dependence of the Auditory Evoked Potential (LDAEP) has been suggested as a possible in vivo measure of central serotonin function in humans (Hegerl and Juckel, 1993).
• LDAEP has been used to examine purported serotonergic abnormalities in depression (Hegerl et al., 2001) and anxiety disorders (Senkowski et al. 2003) and in the prediction of antidepressant treatment response (Gallinat et al. 2000).
• It is a measure of auditory cortex activity, reflecting increase or decrease in the slope of AEP’s (N1/P2) with increasing tone loudness (Figure 1).
INTRODUCTION RESULTS
Figure 2: (a) Mean N1/P2 amplitude plotted against stimulus intensity (loudness), for the placebo, combined (p=0.104), tryp (p=0.318) and tyr/phen (p=0.061) depletion conditions. Least-squares regression lines indicate no significant difference in slope between placebo and each depletion condition.
• Data were digitally re-referenced to linked mastoids.
• Stimulus tones (1000 Hz, 100ms duration with 10ms rise and 10ms fall, SOA randomized between 1600ms and 2100ms) of five intensities (60, 70, 80, 90, 100 dB) presented binaurally using single use foam ear inserts, in a pseudorandomised form.
• Data collected with a sampling rate of 1,000 Hz, and bandpass filter of 0.15 to 200Hz.
• Magnitude of the N1 and P2 peaks were determined for each intensity at CZ.
• N1/P2 slope calculated (P2-N1) as linear regression slope with stimulus intensity (independent variable) and N1/P2 amplitude (dependant variable).
** **
DATA ANALYSIS
**
Croft RJ, Klugman A, Baldeweg T, Gruzelier JH (2001). American Journal of Psychiatry 158 (10), 1687-1692.Hegerl U. and Juckel G. (1993). Biological Psychiatry 33, 173-187.Hegerl U, Gallinat G. and Juckel J. (2001). Journal of Affective Disorders 62, 93-100.Nathan PJ, Segrave. R, Phan KL, O'Neill B and Croft RJ (2006). Human Psychopharmacology 21 (1), 47-52.Senkowski D, Linden M, Zubragel D, Bar T and Gallinat J (2003). Biological Psychiatry 53, 304-314.
REFERENCES
• Placebo-controlled, double-blind, repeated measures design.
• 14 subjects under four treatment conditions: placebo (balanced amino acid drink), tryp (serotonin), tyr/phen (dopamine) and combined tryp/tyr/phen (serotonin and dopamine) depletion.
• Testing 5h post depletion and EEG recorded from 64 scalp sites (international 10/20 system).
•Electrode below the left eye was used to record eye movement, using CZ as reference and AFZ as ground, and electromyography (EMG) recorded from two electrodes beneath the right eye field.
METHODS
Figure 1:Figure 1: Basic Concept of Serotonergic modulation of LDAEP (Adopted from Hegerl et al. 2001).
• The relationship between the LDAEP and changes in serotonin neurotransmission in humans has yielded consistent results (Nathan et al. 2006; Croft et al. 2001; Gallinat et al. 2000).
• The sensitivity of the LDAEP to changes in dopamine neurotransmission are yet to be fully characterised in humans.
• To further examine the effects of serotonin and dopamine on the LDAEP, the current study examined the effects of;
– Serotonin depletion (via tryptophan depletion)– Dopamine depletion (via tyrosine/phenylalanine depletion) – Simultaneous serotonin and dopamine depletion (via tryptophan/tyrosine/phenylalanine depletion)
Figure 3: (a) Mean Values of LDAEP (µV/10dB) at CZ (60-80dB) for placebo, combined, tryp and tyr/phen depletion.
(b) Mean Values of LDAEP (µV/10dB) at CZ (80-100dB) for placebo, combined, tryp and tyr/phen.[*p<.05, **p<.02]
(a)(a) (b)(b)6060--80dB80dB 8080--100dB100dB
• Acute serotonin or dopamine depletion and simultaneous serotonin and dopamine depletion had no effect on the LDAEP (intensity range 60-100dB).
•At higher intensities (80-100dB) compared to lower intensities (60-80dB), there was a significant suppressive effect of dopamine depletion and simultaneous serotonin and dopamine depletion on the LDAEP.
• The effects of dopamine and serotonin on the LDAEP may be dependent on the intensity modulated basal activity of pyramidal cells, such that higher levels of basal activity may be more sensitive to neuromodulation.
• These findings provide a basis for further investigation on the sensitivity of the LDAEP as a marker of monoamine function and/or disorders of monoamine dysfunction.
DISCUSSION AND CONCLUSIONS
0.00
0.04
0.08
0.12
0.16
0.20
Placebo Combined Tryp Tyr/Phen
Condition
N1/P
2 sl
ope
(µV/
10dB
)
0
6
1 2
1 8
2 4
6 0 7 0 8 0 9 0 1 0 0
S t im u lu s in te n s i ty (d B S P L )
N1
/P2
am
pli
tud
e (
µV)
P la c e b o
T r y p
C o m b in e d
T y r /P h e n
0
6
1 2
1 8
2 4
6 0 7 0 8 0 9 0 1 0 0
S t im u lu s in te n s i ty (d B S P L )
N1
/P2
am
pli
tud
e (
µV)
P la c e b o
T r y p
C o m b in e d
T y r /P h e n
Email address for reprints: [email protected]
• Tryp depletion resulted in 93% tryp depletion ( p<0.02). Tyr/Phen depletion resulted in 90% tyr and 93% phen depletion (p<0.02). Combined tryp/tyr/phen depletion resulted in 87% tryp, 91% tyr and 93% phen depletion (p<0.02).
• No effect of treatment on measures of mood (Visual Analogue Mood Scales) (all p’s>0.05).
• Linear increase in N1/P2 amplitude with increasing stimulus intensity (p<0.001), but no significant effect of treatment on N1/P2 slope (Figure 2).
• Further exploratory analysis revealed a significant effect of dopamine and combined dopamine/serotonin depletion at higher intensities (80-100dB) as compared to lower intensities (60-80dB) (Figure 3 (a) and (b)).
Appendix I
Appendix I: Poster presentation, proceeding of the 13th ASP
Conference, Hobart, Australia (2004).
The Loudness Dependence of the Auditory Evoked Potential and Depressive
Symptoms in s Student Population
Valérie Guille, Rodney J. Croft, Craig J. Gonsalvez, Colleen Respondek, Jennifer McIntosh, Ai
Takeuchi, Pradeep J. Nathan
Proceeding of the 13th ASP Conference, Hobart, Australia (2004), Australian Journal of Psychology. V56. S2004. 43
Appendix I
THE LOUDNESS DEPENDENCE AUDITORY EVOKED POTENTIAL ANDDEPRESSIVE SYMPTOMS IN A STUDENT POPULATION
Valérie Guille1, Rodney J. Croft1,2, Craig J. Gonsalvez2, Colleen Respondek2, Jennifer McIntosh2, Ai Takeuchi2, Pradeep J. Nathan1
1. Brain Sciences Institutes, Swinburne University of Technology, Hawthorn, Melbourne2. University of Wollongong, Wollongong
3. RESULTS
4. DISCUSSION-CONCLUSION
2. METHODS
• Low serotonin (5-HT) levels have been linked to depression. • However, 46% of depressed patients have only partial or no-response to
antidepressant serotonin therapy1.• It would be useful to determine whether 5-HT levels are related to
depressive symptoms in a non-clinical sample, but there are currently nonon-invasive techniques for measuring serotonin fonction.
• The loudness dependence auditory evoked potential (LDAEP) indexes central serotonergic function. That is, strong loudness dependence of theN1/P2 complex reflects low serotonergic function and vice-versa2 (see Fig2).
Aims: Investigate whether depressive symptoms are related to serotoninfunction (LDAEP) within a non-clinical population.
Subjects:13 healthy male and 20 healthy female undergraduate volunteers.
Exclusion Criteria:Non-native English speakers, people with brain damage, on medication, on contraceptive pill or regular ecstasy user were excluded.
Procedure:• EEG was recorded from 21 scalp sites with a left ear reference. EOG was
recorded from above and below the left eye, and on the outer canthi of theeyes. AD rate was 512Hz and a band-pass filter of 0.05-120Hz was employed.
• Stimuli were 50 binaural tones (100ms, 1000Hz) at each of five intensities (60, 70, 80, 90, 100dB), presented pseudorandomly with an SOA of 1.85 seconds.
• CES-D, 20-item self-report depression symptom scale3 was completed by thesubjects before the EEG recording.
• Subjects were asked to sit comfortably and relax while the paradigm was run.
1. INTRODUCTION Data analysis:1. Removed ocular voltage from EEG using EOG correction4.2. EEG filtered using low pass analog filter of 30Hz (24dB/octave roll-off).3. Epochs defined as -100 to 300ms.4. 5 ERPs created for each subject by averaging the epochs of each intensity of
stimuli separately.5. N1 and P2 amplitudes calculated as the maximum absolute amplitude
(relative to baseline) in the 80-120msec and 120-240msec time windows, respectively.
6. For each subject, N1/P2 slope was estimated using least squares linearregression.
Statistical analysis:• N1/P2 slopes and CES D variables transformed with square root function.• 6 outliers excluded using Mahalanobis distance procedure.• N1/P2 slopes and CES D scores correlated for male and female groups
separately. • N1/P2 slopes correlated with depression scores in females (trend level), and inversely with depression scores in males (not affected by outliers).
• This suggests that depression was related to low levels of 5-HT in females, and high level of 5-HT in males. This result is consistant with the N1/P2 literature for females, but inconsistant for males2.
• These discrepent results may be due to hormones, such that testosterone isrelated to both reduced 5-HT5 and increased happiness6, which suggeststhat 5-HT in itself may not have a clinically relevant relation withdepression in males.
• This highlights the need to account for sex in 5-HT/depression research.• A possible limitation is that a topography rather than source analysis was
employed, which is insensitive to the scalp distribution change that occursas a function of intensity, as can be see in Fig 5 .
0.00
0.50
1.00
1.50
2.00
2.50
3.00
3.50
0.00 1.00 2.00 3.00 4.00 5.00 6.00
CES D (score)
Slop
e (µ
V)
0.00
0.50
1.00
1.50
2.00
2.50
3.00
3.50
0.00 1.00 2.00 3.00 4.00 5.00 6.00
CES D (score)
Slop
e (µ
V)
Figure 3: Scatterplot and linear regression for male participants
Figure 4: Scatterplot and linear regression for female participants
Figure 5: Scalp topography for N1 and P2 as a function of stimuli intensity
5. REFERENCES1. Taylor J. (2003). Prog Neuropsych Biol Psychiatry 5, 889-91.
2. Hegerl U. and Juckel G. (1993). Biology Psychiatry 33, 173-187.3. Weissman M.M., Sholomskas D., Pottenger M., Prusoff B.A. and Locke B.Z. (1977). Am J Epidemiol 106, 203-14. 4. Croft R.J. and Barry R.J. (2000). Clin Neurophysiol 111, 444-51.5. Zhang L, Ma W, Barker JL, Rubinov DR. (1999).Neurosc 94, 251-9 .6. Delhez M, Hansenne M, Legros JJ. (2003). Ann Endocrinol, 64, 162-9
Raw Transform
n
Age
(X ± s )Slope
(Med ± IQR)CES D
(Med ± IQR)
t- Slope
( X ± s )t-CES D
( X ± s )
Male 13 20.92 ± 4.40 4.12 ± 3.44 9.00 ± 11.00 1.96 ± 0.56 3.17 ± 0.94
Female 20 23.11 ± 4.71 5.10 ± 3.09 9.50 ± 10.25 2.25 ± 0.57 2.95 ± 1.07
Table 1: Mean (or Median) CES D scores and N1/P2 slopes for males and females
Table 2: Correlation coefficients for CES D scores and N1/P2 slopes
p (2-tail)Pearson's rp (2-tail)Pearson's r
0.0710.412Females0.007-0.704Males
60dB 70dB 80dB 90dB 100dB
N1
P2
Figure 2: Amplitude of N1/P2 for five levels of loudness, for low and high 5-HT function separately
0.00
5.00
10.00
15.00
20.00
25.00
30.00
50 60 70 80 90 100 110
Loudness (dB)
N1/
P2 a
mpl
itude
(µV
)
Figure 1: AEP Waveform response to auditory stimuli at five intensities.
High 5-HT functionLow 5-HT function
THE LOUDNESS DEPENDENCE AUDITORY EVOKED POTENTIAL ANDDEPRESSIVE SYMPTOMS IN A STUDENT POPULATION
Valérie Guille1, Rodney J. Croft1,2, Craig J. Gonsalvez2, Colleen Respondek2, Jennifer McIntosh2, Ai Takeuchi2, Pradeep J. Nathan1
1. Brain Sciences Institutes, Swinburne University of Technology, Hawthorn, Melbourne2. University of Wollongong, Wollongong
3. RESULTS
4. DISCUSSION-CONCLUSION
2. METHODS
• Low serotonin (5-HT) levels have been linked to depression. • However, 46% of depressed patients have only partial or no-response to
antidepressant serotonin therapy1.• It would be useful to determine whether 5-HT levels are related to
depressive symptoms in a non-clinical sample, but there are currently nonon-invasive techniques for measuring serotonin fonction.
• The loudness dependence auditory evoked potential (LDAEP) indexes central serotonergic function. That is, strong loudness dependence of theN1/P2 complex reflects low serotonergic function and vice-versa2 (see Fig2).
Aims: Investigate whether depressive symptoms are related to serotoninfunction (LDAEP) within a non-clinical population.
Subjects:13 healthy male and 20 healthy female undergraduate volunteers.
Exclusion Criteria:Non-native English speakers, people with brain damage, on medication, on contraceptive pill or regular ecstasy user were excluded.
Procedure:• EEG was recorded from 21 scalp sites with a left ear reference. EOG was
recorded from above and below the left eye, and on the outer canthi of theeyes. AD rate was 512Hz and a band-pass filter of 0.05-120Hz was employed.
• Stimuli were 50 binaural tones (100ms, 1000Hz) at each of five intensities (60, 70, 80, 90, 100dB), presented pseudorandomly with an SOA of 1.85 seconds.
• CES-D, 20-item self-report depression symptom scale3 was completed by thesubjects before the EEG recording.
• Subjects were asked to sit comfortably and relax while the paradigm was run.
1. INTRODUCTION Data analysis:1. Removed ocular voltage from EEG using EOG correction4.2. EEG filtered using low pass analog filter of 30Hz (24dB/octave roll-off).3. Epochs defined as -100 to 300ms.4. 5 ERPs created for each subject by averaging the epochs of each intensity of
stimuli separately.5. N1 and P2 amplitudes calculated as the maximum absolute amplitude
(relative to baseline) in the 80-120msec and 120-240msec time windows, respectively.
6. For each subject, N1/P2 slope was estimated using least squares linearregression.
Statistical analysis:• N1/P2 slopes and CES D variables transformed with square root function.• 6 outliers excluded using Mahalanobis distance procedure.• N1/P2 slopes and CES D scores correlated for male and female groups
separately. • N1/P2 slopes correlated with depression scores in females (trend level), and inversely with depression scores in males (not affected by outliers).
• This suggests that depression was related to low levels of 5-HT in females, and high level of 5-HT in males. This result is consistant with the N1/P2 literature for females, but inconsistant for males2.
• These discrepent results may be due to hormones, such that testosterone isrelated to both reduced 5-HT5 and increased happiness6, which suggeststhat 5-HT in itself may not have a clinically relevant relation withdepression in males.
• This highlights the need to account for sex in 5-HT/depression research.• A possible limitation is that a topography rather than source analysis was
employed, which is insensitive to the scalp distribution change that occursas a function of intensity, as can be see in Fig 5 .
0.00
0.50
1.00
1.50
2.00
2.50
3.00
3.50
0.00 1.00 2.00 3.00 4.00 5.00 6.00
CES D (score)
Slop
e (µ
V)
0.00
0.50
1.00
1.50
2.00
2.50
3.00
3.50
0.00 1.00 2.00 3.00 4.00 5.00 6.00
CES D (score)
Slop
e (µ
V)
Figure 3: Scatterplot and linear regression for male participants
Figure 4: Scatterplot and linear regression for female participants
Figure 5: Scalp topography for N1 and P2 as a function of stimuli intensity
5. REFERENCES1. Taylor J. (2003). Prog Neuropsych Biol Psychiatry 5, 889-91.
2. Hegerl U. and Juckel G. (1993). Biology Psychiatry 33, 173-187.3. Weissman M.M., Sholomskas D., Pottenger M., Prusoff B.A. and Locke B.Z. (1977). Am J Epidemiol 106, 203-14. 4. Croft R.J. and Barry R.J. (2000). Clin Neurophysiol 111, 444-51.5. Zhang L, Ma W, Barker JL, Rubinov DR. (1999).Neurosc 94, 251-9 .6. Delhez M, Hansenne M, Legros JJ. (2003). Ann Endocrinol, 64, 162-9
Raw Transform
n
Age
(X ± s )Slope
(Med ± IQR)CES D
(Med ± IQR)
t- Slope
( X ± s )t-CES D
( X ± s )
Male 13 20.92 ± 4.40 4.12 ± 3.44 9.00 ± 11.00 1.96 ± 0.56 3.17 ± 0.94
Female 20 23.11 ± 4.71 5.10 ± 3.09 9.50 ± 10.25 2.25 ± 0.57 2.95 ± 1.07
Table 1: Mean (or Median) CES D scores and N1/P2 slopes for males and females
Table 2: Correlation coefficients for CES D scores and N1/P2 slopes
p (2-tail)Pearson's rp (2-tail)Pearson's r
0.0710.412Females0.007-0.704Males
60dB 70dB 80dB 90dB 100dB
N1
P2
60dB 70dB 80dB 90dB 100dB
N1
P2
Figure 2: Amplitude of N1/P2 for five levels of loudness, for low and high 5-HT function separately
0.00
5.00
10.00
15.00
20.00
25.00
30.00
50 60 70 80 90 100 110
Loudness (dB)
N1/
P2 a
mpl
itude
(µV
)
Figure 1: AEP Waveform response to auditory stimuli at five intensities.
High 5-HT functionHigh 5-HT functionLow 5-HT function
Appendix J
Appendix J: An Examination of Acute Changes in Serotonergic
Neurotransmission Using the Loudness Dependence Measure of
Auditory Cortex Evoked Activity: Effects of Citalopram,
Escitalopram and Sertraline.
Guille,V, Croft, RJ, O’Neill, BV, Illic, S, Luan Phan, K and Nathan, PJ.
Human Psychopharmacology. [in press]
Appendix K
Appendix K: Effects of Selective and Combined Serotonin and
Dopamine Depletion on the Loudness Dependence of the Auditory
Evoked Potential (LDAEP) in Humans.
O’Neill, BV, Guille, V, Croft, RJ, Leung, S, Scholes, KE, Luan Phan, K and Nathan, PJ
Human Psychopharmacology. [in press]