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Basic Principles of tRNS: Theory and
Application
Roi Cohen KadoshPLEASE D
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OPY
Declaration of competing interests
• Scientific Advisory Board, Neuroelectrics Inc.
• Scientific Advisory Board, InnoSphere Inc.
• Consultancy, InnoSphere Inc.
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Noise
If everything else is ideal, then noise is the enemy
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Noise
Can we consider our brain as an ideal system?
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NoiseBenefits have been reported in diverse systems, including:• Climate models• Electronic circuits
• Differential equations
• Lasers• Neural models
• Physiological neural populations and networks• Chemical reactions
• Ion channels
• SQUIDs (superconducting quantum interference devices)• Ecological models• Cell biology
• Financial models• Psychophysics• Nanomechanical oscillators
• Organic semiconductor chemistry• Social systems
McDonnell & Abbott, 2009, PLoS Comp BiolPLEASE D
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Noise
Nonlinearity: presence of noise in a nonlinear system
is better for output signal quality than its absence.
Noise cannot be beneficial in a linear system
Performance (noise + nonlinearity) > Performance (nonlinearity)
Stochastic facilitation: Random
noise enhances the detection of
weak stimuli and/or the
information content of a signal (Moss et al., 2004, Clin Neurophysiol;
McDonnell & Ward, 2011, Nat Rev Neurosci)
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Noise
Nonlinearity: presence of noise in a nonlinear system
is better for output signal quality than its absence.
Noise cannot be beneficial in a linear system
Performance (noise + nonlinearity) > Performance (nonlinearity)
McDonnell & Abbott, 2009,
PLoS Comp BiolPLEASE D
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OPY
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Random Noise Stimulation
2005, Ann Neurol
• Used noisy galvanic vestibular stimulation (GVS) to influence
neuronal circuits including the basal ganglia and the limbic system
• 19 Patients with multi system atrophy and/or Parkinson’s disease.
• Noisy GVS boosted the neurodegenerative brains of patients,
including those unresponsive to standard levodopa therapy
• It is also effective in improving autonomic and motor responsiveness
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Transcranial Random Noise Stimulation (tRNS)
Alternating current at random frequencies (Terney et al.,
2008, J Neurosci)
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Terney et al.,
2008, J
Neurosci
10 min tRNS on MEP
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Advantages over tDCS
• Polarity-independent
• Less sensitive to cortex folding
• Compared to tDCS, it is more comfortable,
which make it potentially advantageous for
setting and blinding studies (Ambrus et al., 2010;
Moliadze et al., 2010)
• The 50% perception threshold for both tDCS
conditions was at 0.4mA while this threshold
was at 1.2mA in the case of tRNS.PLEASE D
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Chaieb et
al., 2015,
Front
Neurosci
The effect of carbamazepine (CBZ):
A sodium channel blocker
A more pronounced effect of voltage-gated sodium channels on tRNS
aftereffects
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Perceptual learning
Fertonani et al. 2011, J NeurosciPLEASE D
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Perceptual task
Van der Groen and Wenderoth 2016, J NeurosciPLEASE D
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Snowball et al., 2013, Curr Biol
tRNS over the dlPFC improves
cognitive training
D a y
Me
an
Ca
lcu
lati
on
RT
s (
ms
)1 0 0 0
2 0 0 0
3 0 0 0
4 0 0 0
5 0 0 0
tR N S
S h a m
D a y
Me
an
Dril
l R
Ts
(m
s)
4 0 0
6 0 0
8 0 0
1 0 0 0
S h a m
tR N S
Calculation TrainingDrill Training
1 2 3 4 5 1 2 3 4 5
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Near Infrared Spectroscopy (NIRS)
An optical imaging technique used to observe:
▪ HbO2 (oxygenated haemoglobin)
▪ HHb (deoxygenated haemoglobin)
▪ HbT (total haemoglobin)
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4 0
5 0
6 0
7 0
8 0
Pe
ak
t
im
e
(s
ec
on
ds
)
H b O2
S h a m
t R N S
H H b H b T
F(1, 20)=6.67, p=.018
tRNS improves brain efficiency
Faster
Slower
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Snowball et al., 2013, Curr Biol
Long-lasting effect
Me
di
an
R
T
(m
s)
2 5 0 0
3 0 0 0
3 5 0 0
4 0 0 0
4 5 0 0
5 0 0 0
5 5 0 0
6 0 0 0
O l d P r o b l e m s N e w P r o b l e m s
S h a m
t R N S
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No lasting improvement for drill
Me
di
an
R
T
(m
s)
1 5 0 0
2 0 0 0
2 5 0 0
3 0 0 0
3 5 0 0
4 0 0 0
4 5 0 0
S h a m t R N S
p=0.78
Faster
Slower
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C a l c u l a t i o n D r i l l
4 0
6 0
8 0
1 0 0
1 2 0
Pe
ak
t
im
e
(s
ec
on
ds
)
S h a m
t R N S
F(1,10)=.49, p=.5F(1,10)=11.58, p=.007
Long-lasting effect at the physiological
level
Faster
Slower
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Results
Cappelletti et al. 2013, J NeurosciPLEASE D
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Atypical development
tRNS cap
Looi et al., 2017, Sci RepPLEASE D
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S e s s io n
Le
ve
l c
om
ple
ted
1 2 3 4 5 6 7 8 9
6
8
1 0
1 2
1 4
1 6
1 8
2 0 S h a m tR N S
tRNS affects the learning slopes
F(1,10)=5.9, p<.01
Better
Snowball et al., 2013, Curr Biol; Cappelletti et al., 2013, J Neurosci; Popescu et al., 2016,
Neuropsychologia; Fertonani et al., 2011, J Neurosci; Terney et al., 2008, J Neurosci
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Online effect: temporary fluctuations in behaviour
or knowledge that can be observed and measured
during the acquisition process
The Subcomponents of Cognitive
Training
Soderstrom & Bjork (2015, Perspect Psychol Sci)
Performance
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Offline effect: relatively permanent changes in
behaviour/knowledge
The Subcomponents of Cognitive
Training
Soderstrom & Bjork (2015, Perspect Psychol Sci)
Learning
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Experiment 1
d l P F C P P C
- 1 0 0 0
- 5 0 0
0
5 0 0
1 0 0 0
On
li
ne
(
B)
n=72
Better
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Experiment 1
d l P F C P P C
- 1 0 0 0
- 5 0 0
0
5 0 0
1 0 0 0
Of
fl
in
e
(B
)
*
n=72
Better
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Experiment 2
d l P F C P P C
- 1 0 0 0
- 5 0 0
0
5 0 0
1 0 0 0
On
li
ne
(
B)
n=51
Better
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Experiment 2
d l P F C P P C
- 1 0 0 0
- 5 0 0
0
5 0 0
1 0 0 0
Of
fl
in
e
(B
)
*
* *
n=51
Better
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The effect is offline-related!
d l P F C P P C
- 1 0 0 0
- 5 0 0
0
5 0 0
1 0 0 0
Of
fl
in
e
(B
)
*
d l P F C P P C
- 1 0 0 0
- 5 0 0
0
5 0 0
1 0 0 0
On
li
ne
(
B)
d l P F C P P C
- 1 0 0 0
- 5 0 0
0
5 0 0
1 0 0 0
On
li
ne
(
B)
d l P F C P P C
- 1 0 0 0
- 5 0 0
0
5 0 0
1 0 0 0
Of
fl
in
e
(B
)
*
* *
Exp. 1
Exp. 2
n=123, Stimulation x Area: p=.00004, dlPFC: p=0.0008, PPC: p=0.01
Better
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Dose effect and potential mediators
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We aimed to target the top-down cortical attention system; a
predominantly right lateralised frontoparietal network
The neural basis of sustained attention
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Sustained attention
1270
1280
1290
1300
1310
1320
1330
1340
0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 6.5 7 7.5 8 8.5 9 9.5
65
35
-1000-40004008001200160020002400
TargetOnsetContrastofthes mulusbeginstodecreasefromthebaselinelevel(65%)
Max.decreaseContrastofthes mulus
reachesthelowestlevel(35%)
ReturntoBaselineContrastofthes mulusreturnstothebaseline
level(65%)
Time(ms)
ContrastofS
mulus(%
)
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Experiment design
Within-subjects design (n=72)
Each subject received 3 different stimulation conditions over 3 consecutive days
Order of stimulation fully randomized
tRNS electrodes placed over F4 and P4 to target right DLPFC and right IPL
Harty & Cohen Kadosh (Submitted)PLEASE D
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F(4,284) = 3.08, p = .017PLEASE D
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Variability in the response 1mA tRNS
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1mA tRNS reduced TBR
F(2,136) = 5.93, p = .003PLEASE D
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The benefit from tRNS depended on TBR
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Short Quiz
What are the advantages of tRNS over tDCS?
• Polarity-independent
• Less sensitive to cortex folding
• It is more comfortable, which make it potentially
advantageous for setting and blinding studies
• The 50% perception threshold for both tDCS
conditions was at 0.4mA while this threshold
was at 1.2mA in the case of tRNS.
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Short Quiz
tRNS seems to interact with:
1) The GABAergic system
2) The dopaminergic system
3) The glutamatergic system
4) 1 and 3 are correct
5) All the answers are correct
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Short Quiz
Based on the material covered here, who would
you think be most likely to benefit from tRNS
1) The average person
2) Those who are cognitive below the average
3) Those who are cognitively above the average
4) 1 and 2
5) 1 and 3 as the effect is non-linear
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Short Quiz
The effect of tRNS is:
1) Online-base
2) Offline-base
3) Can be both
4) Neither (you should use tDCS)
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What have we learned
• Noise can be beneficial in nonlinear systems
• Applying noise to the brain improves performance
• The effect can be long-lasting
• tRNS has some advantages over tDCS
• tRNS interacts with voltage-gated sodium channels,
the gultamateric system, and hemodynamic
response.
• The effect can be moderated by neurophysiological
trait
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Thanks to
Current and previous lab
members
Dr Siobhan Harty
Dr Beatrix Krause
Dr Chung Yen Looi
Thomas Page
Dr Tudor Popescu
Gal Raz
Albert Snowball
Dr Devin Terhune
Olivia Towse
Dr George Zacharopoulos
Collaborators
Dr Jessamy Almquist (Honeywell)
Dr Mihaela Duta (Oxford)
Prof Margarete Delazer (Innsbruck)
Prof. Glyn Humphreys (Oxford)
Jenny Lim (Fairely House School)
Dr Simon Lolliot (McGill)
Dr Ilias Tachtsidis (UCL)
Dr Laura Zamarian (Innsbruck)
Dr Tingting Zhu (UCL)
Prof Glyn Humphreys (Oxford)
Staff, parents and children, Fairely House
School
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Thank you for your attention
E-mail: [email protected]
Web: www.psy.ox.ac.uk/research/cohen-kadosh-laboratory
“It is not science fiction, it is already real
and it will be a critical part of our future.” Stephen Hawking, discussing our research
TEDx Talk: https://www.youtube.com/watch?v=QoHZ5b-aaX4
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