Mechanisms of auditory attention in normal and hearing impaired listeners

Christofer W. Bester, BSc (Hons)

Supervised by: Emeritus Professor Don Robertson1

Emeritus Professor Geoff Hammond2

This thesis is presented for the degree of Doctor of Philosophy of the University of Western Australia

1 School of Anatomy, Physiology and Human Biology 2 School of Psychology

2015

Mechanisms of auditory attention in normal and hearing impaired listeners

i

Abstract.

Near-threshold tones presented in background noise are detected at a

relatively higher rate if presented more frequently than other tones,

and/or if preceded by a clearly audible cue tone of the same or similar

frequency. A potential candidate that has been suggested to underlie the

formation of this so-called attentional filter is the medial olivocochlear

system (MOCS). This thesis addresses the extent and nature of the

potential MOCS role in forming the attentional filter.

Three sets of experiments are included in the present work. The first set

of experiments correlated the depth of the attentional filter with the

strength of a single MOCS process, the MOCS acoustic reflex, using the

suppression of otoacoustic emissions in normal -hearing participants. The

second set of experiments explored the depth of the attentional filter

using the difference in detection rate of the more frequently presented

tones and the infrequently presented tones, in participants with a loss of

the MOCS efferent t argets due to sensorineural hearing loss (SNHL).

Sensorineural hearing loss participants were recruited with a range of

severities of hearing loss, from mild to moderately -severe, so that fi lter

depth could be correlated with the level of hearing loss. The final set of

experiments measured the attentional filter in cochlear implant

recipients, as a group presumed to have no remaining MOCS action on

the cochlea, but who had undergone a period of auditory relearning. The

findings of the thesis are:

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1. In normal-hearing participants there was no evidence for increasing

depth of the attentional fil ter with increasing strength of the MOCS

acoustic reflex, as assessed by the contralateral suppression of

otoacoustic emissions.

2. The depth of the attentional filter was found to decrease slightly

with increasing MOCS acoustic reflex strength, although this was a

weak effect which was observed primarily on the low -frequency

side of the attentional filter.

3. In these clinically normal hearing participants, there was a range of

auditory thresholds from -5 to 10 dB HL. A negative correlation

was found between the depth of the low -frequency side of the

attentional filter and hearing level. The depth of the low -frequency

side of the attentional filter decreased to zero over this sm all range

of subclinical hearing levels.

4. Individuals with SNHL and a loss of otoacoustic emissions had

decreased depth of the attentional fil ter. At the lowest level of

SNHL, the low-frequency side of the attentional filter was no

longer suppressed in comparison with the more-frequently

presented centre frequency. The depth of the high -frequency side of

the fil ter decreased progressively with increasing SNHL, and was

near zero at 60 dB HL.

5. Two participants with conductive hearing loss, who were assumed

to have a hearing loss without an associated loss of MOCS targets

in the cochlea, showed a similar decrease in filter depth as the

SNHL group.

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6. Five of the six cochlear implant recipients, who were presumed to

have no remaining MOCS targets in the cochlea, show ed no

evidence of an attentional filter when the stimuli were presented

with free-field acoustics. However, one implant recipient showed a

normal attentional fi lter.

7. Four implant recipients were re -tested with a programmed, direct

stimulation that had no acoustic stimulus, to eliminate the

potentially unwanted effects of the commercial speech processor

used previously. Two of the cochlear implant recipients tested with

programmed, direct stimulation showed an attentional filter.

The decreased depth of the attentional filter with increasing MOCS

acoustic reflex strength in normal -hearing participants is not consistent

with a role for the MOCS in forming the attentional filter. In participants

with SNHL, the decreased depth of the high -frequency side of the f ilter

occurred at levels of hearing loss physiologically relevant to the

impairment of the MOCS efferent targets. In contrast, the loss of the

low-frequency side of the attentional fil ter occurred before clinical

SNHL is classified, and at a hearing level that is not typically associated

with appreciable impairment to the MOCS efferent targets, the outer hair

cells. The subclinical changes in hearing level may be associated with

recent research into so-called “hidden” hearing losses, which have been

identif ied in individuals with normal auditory thresholds. These hidden

hearing losses have been associated with auditory neuropathy, and this

neuropathy may be selective for the fibres that form the afferent input to

the MOCS. The loss of the low-frequency side of the filter may then be

due to reduced input to the MOCS with auditory neuropathy, or it may be

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due an alternative, non-MOCS mechanism whose impairment is

associated with the low-level elevation in auditory thresholds. These

results are consistent with a t least a partial role for the MOCS in

forming the filter. However, the loss of the attentional fil ter in two

participants with conductive hearing loss may suggest that the hearing

loss alone can result in the loss of the attentional filter. Finally, the

finding that at least one cochlear implant recipient who had profound

SNHL prior to implantation was able to form the attentional filter

suggests that there must be an alternative mechanism that is able to form

the fil ter in some cochlear implant recipients .

The attentional filter is thought to improve the detectability of signals of

interest in noisy environments. The impaired formation of the filter with

SNHL may then contribute to the poor speech -in-noise perception

associated with this hearing impairment . In addition, the filter decreased

in depth at subclinical hearing levels, which may indicate an important

“hidden” detriment to auditory ability before clinical hearing loss is

classified. Finally, most of the cochlear implant recipients did not show

a typical attentional filter, which may contribute to the difficulties with

speech in noise perception associated with the implants. However, the

apparent presence of the attentional filter in at least one cochlear

implant recipient indicates that the filter can be formed in some

individuals with no remaining MOCS action on the cochlea. Variations

in the ability to form an attentional filter may be a contributing factor to

the wide range in cochlear implant outcomes, in particular when

discriminating signals in competing background noise.

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Table of contents

Abstract. ............................................................................................................................. i Table of contents .............................................................................................................. vi List of figures ................................................................................................................. viii Abbreviations .................................................................................................................... x Acknowledgements .......................................................................................................... xi Candidate Contributions ................................................................................................. xii Chapter 1. General Introduction ................................................................................... 1

1.1 The attentional filter: History ............................................................................. 3 1.2 The attentional filter: Cues ................................................................................. 5 1.3 The medial olivocochlear system: Proposed role ............................................... 7 1.4 The medial olivocochlear system: Anatomy ...................................................... 8 1.5 The medial olivocochlear system: Physiology ................................................. 10 1.6 The medial olivocochlear system: Effects on hearing...................................... 11 1.7 The medial olivocochlear system: In humans .................................................. 15 1.8 The medial olivocochlear system: Forming the attentional filter..................... 19 1.9 The medial olivocochlear system: Related structures ...................................... 25 1.10 Central mechanisms ......................................................................................... 27 1.11 Structure and aims of the thesis ........................................................................ 28

Chapter 2. General Methods ....................................................................................... 31 2.1 Acoustic Stimuli ............................................................................................... 32 2.2 Psychophysical procedures............................................................................... 33 2.3 Auditory thresholds .......................................................................................... 34 2.4 Cued probe-target procedure to measure the attentional filter ......................... 34

Chapter 3. Formation of the attentional filter in normal-hearing participants ............ 37 3.1 Introduction ...................................................................................................... 38 3.2 Methods ............................................................................................................ 40

3.2.1 Participants ................................................................................................ 40 3.2.2 MOCS acoustic reflex strength measurement ........................................... 40 3.2.3 Preliminary study ...................................................................................... 44 3.2.4 Primary experiment: Attentional filters and the suppression of OAEs ..... 45

3.3 Results .............................................................................................................. 46 3.3.1 Activation of the middle-ear muscle reflex............................................... 46 3.3.2 Preliminary study: TEOAEs ..................................................................... 46 3.3.3 Preliminary study: DPOAEs ..................................................................... 48 3.3.4 Preliminary study: OAE relationships and the selective attention task .... 49 3.3.5 Primary experiment: Attentional filters and the suppression of OAEs ..... 52 3.3.6 Primary experiment: Detection rates measurement .................................. 55 3.3.7 Primary experiment: TEOAE suppression ................................................ 55 3.3.8 Primary experiment: DPOAE suppression ............................................... 60

3.4 Discussion ........................................................................................................ 66 Chapter 4. Formation of the attentional filter in hearing-impaired participants ......... 74

4.1 Introduction ...................................................................................................... 75 4.2 Methods ............................................................................................................ 77

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4.2.1 Participants ................................................................................................ 77 4.2.2 Measuring the attentional filter. ................................................................ 78

4.3 Results .............................................................................................................. 79 4.3.1 Normal-hearing & SNHL groups: Audiometric results ............................ 79 4.3.2 Normal hearing & SNHL groups: Attentional filters ................................ 82 4.3.3 Conductive hearing loss participants: Audiometric results ....................... 87 4.3.4 Conductive hearing loss participants: Attentional filters .......................... 89

4.4 Discussion ........................................................................................................ 90 Chapter 5. Formation of the attentional filter in cochlear implant recipients using acoustic presentation ..................................................................................................... 101

5.1 Introduction .................................................................................................... 102 5.2 Methods .......................................................................................................... 104

5.2.1 Participants .............................................................................................. 104 5.2.2 Stimulus Presentation .............................................................................. 105 5.2.3 Preliminary study: Simulation ................................................................ 106 5.2.4 Preliminary study: Threshold & attentional filter procedures................. 108 5.2.5 Primary Experiment: Measuring the attentional filter ............................ 108 5.2.6 Statistics .................................................................................................. 109

5.3 Results ............................................................................................................ 111 5.3.1 Preliminary study: Simulation results ..................................................... 111 5.3.2 Preliminary study: Threshold & attentional filter procedures................. 113 5.3.3 Primary experiment: Measuring the attentional filter ............................. 115

5.4 Discussion ...................................................................................................... 120 Chapter 6. Formation of the attentional filter in cochlear implant recipients using programmed, direct stimulation .................................................................................... 127

6.1 Introduction .................................................................................................... 128 6.2 Methods .......................................................................................................... 130

6.2.1 Participants .............................................................................................. 130 6.2.2 Constructing the stimuli .......................................................................... 130 6.2.3 Measuring the attentional filter ............................................................... 132 6.2.4 Shifted target experiments....................................................................... 134 6.2.5 Statistics .................................................................................................. 134

6.3 Results ............................................................................................................ 135 6.3.1 Stimulation details ................................................................................... 135 6.3.2 Attentional Filter measurements ............................................................. 136

6.4 Discussion ...................................................................................................... 141 Chapter 7. General Discussion.................................................................................. 148

7.1 Implications & Future Directions ................................................................... 159 7.1.1 Formation of the filter in normal hearing individuals ............................. 160 7.1.2 Formation of the attentional filter with conductive hearing loss ............ 163 7.1.3 An alternative mechanism able to form the attentional filter .................. 164

7.2 Conclusions .................................................................................................... 165 References ..................................................................................................................... 166 Chapter 8. Appendix ................................................................................................. 175

8.1 Depth of the attentional filter as a function of OAE suppression................... 175 8.1.1 TEOAE suppression ................................................................................ 175 8.1.2 DPOAE suppression ............................................................................... 177

viii

List of figures

Chapter 1

Figure 1.1: The attentional filter measured by Greenberg and Larkin (1968) .................. 4

Figure 1.2: Schematic diagram of the MOCS anatomy .................................................... 9

Figure 1.3: Auditory nerve fibre firing rate with MOCS activation in quiet .................. 12

Figure 1.4: Auditory nerve fibre firing rate with MOCS activation in noise .................. 14

Figure 1.5: Schematic of proposed MOCS role in filter formation ................................ 21

Figure 1.6: Change in filter depth after a vestibular neurectomy ................................... 22

Chapter 2

Figure 2.1: Sound spectrum of broadband background noise ......................................... 32

Figure 2.2: Structure of the two interval forced choice procedure ................................. 33

Chapter 3

Figure 3.1: Examples of OAE data, including DPOAE spectrum, DPOAE fine structure and a DPOAE I/O function, as well as the TEOAE waveform ................................. 42-43

Figure 3.2: TEOAE response with and without noise for 3 participants ........................ 47

Figure 3.3: DPOAE response with and without noise for 3 participants ........................ 49

Figure 3.4: Attentional filters for 15 normal hearing participants .................................. 52

Figure 3.5: Attentional filters for 15 normal hearing participants, for the three sessions used to measure the filter ................................................................................................ 54

Figure 3.6: Attentional filters across three sessions for two participants ....................... 55

Figure 3.7: Correlation between TEOAE suppression and depth of the attentional filter ..

......................................................................................................................................... 56

Figure 3.8: Correlation between DPOAE suppression and depth of the attentional filter ..

......................................................................................................................................... 61

Chapter 4

Figure 4.1: Audiograms for normal hearing and SNHL participants ........................ 80-81

Figure 4.2: Attentional filters for the normal hearing and SNHL groups ....................... 83

Figure 4.3: Depth of the attentional filter as a function of hearing loss for the normal hearing and SNHL groups .............................................................................................. 85

Figure 4.4: Schematics for attentional filters with normal hearing and SNHL .............. 86

Figure 4.5: OAE suppression as a function of hearing loss for the normal hearing group

......................................................................................................................................... 87

Figure 4.6: Audiograms for two conductive hearing loss participants ........................... 88

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Figure 4.7: Attentional filters for two conductive hearing loss participants ................... 89

Chapter 5

Figure 5.1: Schematic of stimuli used for cochlear implant simulation ....................... 107

Figure 5.2: Response of the cochlear implant during simulations at threshold ............ 111

Figure 5.3: Response of the cochlear implant during simulations at threshold ............ 113

Figure 5.4: Tracking threshold in two individuals with normal hearing and two cochlear implant recipients using acoustic presentation .............................................................. 114

Figure 5.5: Attentional filters for two normal hearing participants and two cochlear implant recipients in a preliminary study using acoustic presentation ......................... 115

Figure 5.6: Grouped attentional filters for normal hearing individuals and cochlear implant recipients using acoustic presentation .............................................................. 117

Figure 5.7: Attentional filters for individual cochlear implant recipients using acoustic presentation ................................................................................................................... 119

Chapter 6

Figure 6.1: Structure of the programmed, direct stimuli ............................................... 132

Figure 6.2: Response of cochlear implant to programmed stimulus ............................. 135

Figure 6.3: Grouped attentional filters for the cochlear implant recipients using programmed, direct stimulation ................................................................................... 137

Figure 6.4: Attentional filters for individual cochlear implant recipients using both acoustic presentation as well as programmed, direct stimulation ................................. 139

Figure 6.5: Shifted target attentional filters for cochlear implant users using programmed, direct stimulation .................................................................................... 140

Appendix

Figure 8.1: Relationship between filter depth and TEOAE suppression ..................... 176

Figure 8.2: Relationship between filter depth and DPOAE suppression ............... 177-178

Figure 8.3: Frequency allocation table (FAT) for Cochlear™ implants ....................... 179

Figure 8.4: Audiograms for the contralateral ear in the SNHL participants ................ 180

x

Abbreviations

2IFC Two interval forced choice

AC Air conduction

ANOVA Analysis of variance

BC Bone conduction

CHL Conductive hearing loss

CI Cochlear implant

DPOAE Distortion product otoacoustic emission

FFT Fast Fourier transform

HL Hearing level

I/O Input / output

IHC Inner hair cell

LOCS Lateral olivocochlear system

MOCS Medial olivocochlear system

NH Normal hearing

OAE Otoacoustic emission

OHC Outer hair cell

SFOAE Stimulus frequency otoacoustic emission

SNHL Sensorineural hearing loss

SPL Sound pressure level

TEOAE Transiently-evoked otoacoustic emission

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Acknowledgements

My first acknowledgements and thanks, must go to my supervisors. Don & Geoff have

worked with (nearly) infinite patience as I have progressed in my studies, and this

document would be a pale shadow of what it is without their careful guidance.

From the Ear Science Institute of Australia, Marcus Atlas, Dunay Taljaard, and

especially Dona Jayakody have helped tremendously with my understanding of hearing

research, and without their and the Institute‟s help I would not have had the

opportunities to work directly with the hearing impaired individuals required for the

work. Thanks for the help, both inside and outside of the soundproof booths!

The Auditory lab has been an excellent base for learning how to perform high-quality

research. The guidance provided by Don, Rob, and Helmy as well as the students I‟ve

worked with, Darryl, Nathaniel, Ahmaed, Kristin, and Kerry made the years I‟ve

worked with lab enjoyable, and informative beyond a simple scientific education. My

sincere thanks to everyone involved in this institution.

The village required to raise this particular child extends beyond the university. Without

the support of my parents this PhD would simply not exist, even though this career path

was third (at most) on their list of approved jobs. Mom, dad, thanks for the help, and the

ability to make hard decisions for all of us. To the rest, Ashleigh, Scott, and Nick,

thanks for providing a context that post-graduate studies are not my whole life.

Audrey Bester, getting married during a PhD was a mad move, and I would do it again

in a heartbeat. My thanks for you would take more than the 180 pages I‟ve written here,

so I will be brief: Every day I‟m with you is the best day I‟ve ever had.

To everyone else who has helped throughout this crazy process, you have my thanks.

To my friends, please pretend that I listed your name here first in a long line of friends,

go you! Thanks to my extended family, in Australia, South Africa, London and now

Malaysia and Singapore!

“Don't Panic.” ― Douglas Adams, The Hitchhiker's Guide to the Galaxy

xii

Candidate Contributions

This thesis does not contain work that I have published, or work that is currently under

review for publication.

All experiments were conducted by the author, Christo Bester, with some assistance.

Many of the LabVIEW programs included in the work are based on versions that were

initially programmed by Geoff Hammond. I was aided by audiologists from the Ear

Science Institute of Australia. Dunay Taljaard aided in the audiometric testing of some

hearing impaired individuals in chapter 4. Dona Jayakody aided in the same audiometric

testing, and in the setup of cochlear implant recipients in chapters 5, and 6. Dr. Peter

Busby and Kieran Reed from CochlearTM provided advice and a proofread of the Python

programming included in chapter 6.

Otherwise, the content of this thesis is of my own composition, and all relevant sources

are acknowledged. This thesis has never been submitted for any other degree in this, or

another institution.

Geoff Hammond

Co-ordinating supervisor

in psychology

6th September 2015

Don Robertson

Co-ordinating supervisor

in physiology

6th September 2015

Christo Bester

PhD Student

6th September 2015

Chapter 1. General Introduction

General introduction

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Detecting a signal of interest in competing noise, such as understanding the content of

one person‟s speech while others are talking, is a complex auditory task. A healthy

auditory system is surprisingly adept at this task, which forms the basis of Cherry‟s

“Cocktail Party Problem”, a research question that investigates the possible mechanisms

that enable us to separate sounds of interest from background noise (Cherry, 1953).

There are a number of stages within the auditory system that are involved in this ability,

and much of the processing, such as auditory scene analysis (Bregman, 1990), is located

in central auditory structures. However, this thesis is concerned only with a subset of

auditory processing that is achieved by the efferent control of the peripheral auditory

system.

The cochlea acts as the first detailed frequency analyser in the auditory system, but it is

not a passive receiver. The cochlea‟s fine frequency sensitivity and specificity are due to

the active cochlear amplifier, which is powered by the outer hair cells (OHCs). The

OHCs are the targets of an efferent projection from the olivocochlear system.

Consequently, this efferent projection is able to modify the auditory system‟s sensitivity

to incoming sound via the cochlear amplifier. Thus, the efferent control of the

peripheral cochlear amplifier is an ideal location to modify the detectability of incoming

auditory signals.

The first experiments to investigate the effects of selective attention on the detectability

of auditory stimuli used dichotic listening tasks that test the processing of competing

speech signals (Cherry, 1953). However, when we consider the basic physiology of the

peripheral auditory system, it is more useful to consider simple stimuli. Tanner and

Norman (1954) began these experiments by testing the detection rate of pure tones at an

attended frequency („target‟ tones), compared to pure tones presented at an unattended

frequency („probe‟ tones). In their study, participants were trained to detect a 1-kHz

target tone in noise, which was presented at a 65% detection threshold. After the


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training period, the stimulus was switched to a 1.3-kHz probe tone, without informing

the participants. The tone presented at the attended, target, frequency was detected at the

65% threshold level, while the tone presented at the unattended, probe, frequency was

not detected above chance. In fact, the participants reported that they had failed to

switch on the signal generator! The results of this experiment, and a similar study by

Greenberg (1962), were taken as evidence that the auditory system behaves, in part, as

a narrow-band receiver that allows the input of attended stimuli while attenuating the

input of unattended stimuli.

1.1 The attentional filter: History

In 1968, Greenberg and Larkin took this research a step further with their probe-target

procedure (or probe-signal procedure in the original nomenclature). This procedure was

developed to measure the detection rate of target and probe tones as a function of

frequency. The original probe-target procedure used a similar structure to Tanner and

Norman‟s 1954 procedure described above. The participants were trained to detect a

1.0-kHz target tone, and led to only expect this tone during the experiment. After this

training period the procedure continued, but now with the target tone presented on only

70% of all trials, while the remaining 30% contained a probe tone. Each 100-trial run of

the procedure used only a single probe frequency, and multiple runs were done to

measure a range of probe frequencies. The data from multiple runs were combined to

show an apparent narrow band filter of detection rates, with a peak of detection rates at

the target frequency and a progressive reduction of the detection rates of probes with

increasing separation from the target frequency (Greenberg and Larkin, 1968). This is

known as the attentional filter (Botte, 1995). This attentional filter is a separate process

to the more general auditory filter (Fletcher, 1940), as demonstrated by the auditory

filter‟s slightly narrower bandwidth, and tendency to become skewed with increasing

masker level, whereas the attentional filter remains symmetrical (Glasberg and Moore,


4

1990; Botte, 1995). An example of the attentional filter is shown in Figure 1.1, from

Greenberg and Larkin‟s original 1968 research. The presence of the attentional filter

supports the notion that auditory signals presented in noise vary in detectability based

on the expectation built by previous trials.

Figure 1.1. Detection rate of the target tone, at 1.0 kHz and the probe tones, all others,

as a function of frequency, demonstrating the attentional filter. The tone at the target

frequency was presented on 70% of all trials, and the participants were only informed of

the presence of the target tone. Figure adapted from Greenberg and Larkin (1968).

Initially, there were concerns that the attentional filter was produced not due to the

attenuation of the probes, but because the participants were ignoring the probe tones that

they were not informed of, even when they were readily detectable. This is known as

the „heard but not heeded‟ hypothesis (Scharf et al., 1987). To address this concern,

Scharf et al. repeated the probe-target procedure, but informed the participants of the

presence of probe tones different from the target tone during the experiment, and found

no appreciable differences in the shape or depth of the filter, which indicates that prior

knowledge of the presence of probes does not affect the formation of the attentional

filter.


5

The probe-target procedure up to this point presented the target tone and only a single

probe tone during each run of the experiment, and therefore required several

experimental sessions, over 3 to 5 days, to measure the attentional filter. Dai et al.

(1991) changed this by modifying the procedure to include multiple probe tones during

each run. This was termed the „multi-probe‟ procedure. The multi-probe procedure still

used the 70% target presentation, but the remaining probe frequencies were randomly

dispersed throughout 30% of each run, in equal number. This allowed a more rapid

measurement of the attentional filter. Dai et al.‟s work further estimated the amount of

attenuation which, if applied to the distant probe tones during an auditory threshold

measurement, would result in the reduced detection rates seen in the attentional filter.

The probe suppression equated to roughly 7 dB of suppression at half a critical band

from the target frequency.

1.2 The attentional filter: Cues

A 70% or higher presentation rate of the target was the first method used to build the

expectation of the target tone. However, prior research had demonstrated that a clearly

audible cue tone, that preceded a single to-be-detected tone, increased the tone‟s

detection rate (Greenberg, 1962). In 1972, Penner extended this cueing effect to the

formation of the attentional filter (Penner, 1972). The experiment followed the same

structure as the previous probe-target experiments, but the to-be-detected target and 8

probe tones were presented with equal probability, and all tones were preceded by a

clearly audible cue tone at the target frequency. This cued probe-target procedure

formed attentional filters that were not substantially different from those in the previous

research, showing that the attentional filter can be produced by preceding the to-be-

detected tones with a cue tone. Penner explained the formation of the attentional filter in

response to this cue-effect as an alternative method of leading the subjects to

consciously expect the target tone at the cue frequency (Penner, 1972).


6

Research has shown that cues do not have to be presented at the target frequency to

produce the attentional filter. Ebata et al. (2001) used complex tones as cues, which

were constructed to have a missing fundamental frequency at 250 Hz. The probe-target

procedure was then used to measure the attentional filter around this missing

fundamental frequency, at which there was no real acoustic energy in the cue tone. The

normal attentional filters that were produced demonstrated that acoustic energy at the

cue frequency in the cochlea is not required for an effective cue tone. Borra et al. (2013)

supported this notion by demonstrating normal attentional filters were produced at

octave-related frequencies both higher and lower than the cue tone, even when the cue

tone was imagined (Borra et al., 2013). Therefore, the attentional filter can be formed

using cues that require complex frequency-extraction, or are imagined, which implicates

the involvement of high-order auditory processing.

However, the role of cue-effect on the formation of the attentional filter may not be

entirely dependent on high-level processing. In contrast to the cues discussed so far, Tan

et al. (2008) used a cued probe-target procedure which attempted to remove the

expectation building effects of the cue tones (Tan et al., 2008). In this experiment, the

cue tones were randomly selected from a set of 5, and the target and 4 probe tones were

selected with equal probability. Thus, the to-be-detected tone matched the cue tone on

only 20% of all trials, which resulted in a cue tone that was misleading in the majority

of trials, and should not have led the participants to consciously expect the target tone at

the cue frequency. Nevertheless, the on-cue target tone was detected at a higher rate

than any of the probe tones, and the subjects showed attentional filters of approximately

half the depth of those formed with a constant frequency cue and 75% target

presentation. This result demonstrated the formation of the attentional filter in response

to cue tones which did not build-up the expectation of a single target frequency,

although the filters were reduced in depth. While it seems reasonable to suggest that


7

these filters were produced using the same high-order auditory processing discussed in

the previous chapter, prior research supports a reflexive mechanism for the cue effect by

demonstrating that the emergence of the cue benefit can be extremely rapid. Pure-tone

cues were found to reduce the threshold of a transient tone in noise within 52 ms

(Scharf et al., 2007). The formation of the attentional filter in response to apparently

non-informative cues, which have been shown to have an effect on detection rates when

they preceded a to-be-detected tone by only 52 ms suggests, but does not necessarily

prove, that the cue-effect is partially provided by a subcortical reflex.

While the features of the attentional filter continued to be a focus for research, the

systems underlying the formation of the filter remained unclear. In the research

described above, the filter was shown to be formed in conditions consistent with high-

order, central processes, as well as in conditions that may be restricted to the effects of a

subcortical reflex. This thesis addresses the efferent control of the cochlear amplifier,

which will be shown below to fulfil both of these conditions, as a potential mechanism

for the formation of the attentional filter.

1.3 The medial olivocochlear system: Proposed role

In 1987, Scharf proposed that efferent control of the cochlear amplifier by the

olivocochlear system plays a role in forming the attentional filter (Scharf et al., 1987).

The cochlear amplifier, powered by the OHCs, was known to have substantial control of

auditory sensitivity (Dallos and Harris, 1978), by providing up to 50 dB of amplification

for incoming sound (Patuzzi et al., 1989b). The OHCs are the targets of the largest

efferent projection to the cochlea from the medial olivocochlear efferents. These

efferents have cell bodies located in the periolivary region of the superior olivary

complex, and both crossed and uncrossed projections to both cochleae (Moore et al.,

1999). The efferents synapse at the base of OHCs with cholinergic synapses (Fuchs,


8

1996). The synaptic release of acetylcholine hyperpolarises the OHCs, suppressing their

active processes and reducing the gain of the cochlear amplifier (Housley and Ashmore,

1991). Therefore, each cochlea is under efferent control from both ipsilateral and

contralateral medial olivocochlear efferents, and these efferents act to suppress the

cochlear amplifier gain. The medial olivocochlear efferents and their afferent inputs,

discussed below, form the medial olivocochlear system (MOCS).

1.4 The medial olivocochlear system: Anatomy

The MOCS has both ascending input from the auditory afferents, as well as descending

input from higher auditory structures, summarised in Figure 1.2.


9

Figure 1.2. Schematic diagram showing the inputs and output of one medial

olivocochlear system. Ascending afferent input is shown as dotted lines. The MOCS

acoustic reflex, with a feedback loop between the inner hair cells (IHCs) to the OHCs

via the MOCS is shown as dashed lines. Descending control of the MOCS by higher

auditory systems is shown by solid lines. Not shown is the uncrossed afferent input to

the MOCS required for binaural facilitation.

The ascending afferent input to the MOCS is through the primary auditory afferents,

which cross to the contralateral MOCS via interneurons in the cochlear nucleus

(Liberman and Brown, 1986; Robertson and Winter, 1988; De Venecia et al., 2005). As

this afferent input is crossed, it activates the contralateral olivocochlear efferents;

however, it is important to note that there are both crossed and uncrossed efferents, thus

afferent auditory input from a single cochlea will result in efferent suppression of both

cochleae. This creates an olivocochlear feedback system, where afferent auditory input


10

results in efferent suppression of the cochlea via the contralateral MOCS, which is

known as the MOCS acoustic reflex. The descending, top-down input to the MOCS

arises from both the auditory cortex and the inferior colliculus (Vetter et al., 1993;

Mulders and Robertson, 2000b; Xiao and Suga, 2001; Perrot et al., 2006; Schofield and

Coomes, 2006). Therefore, the MOCS can respond to auditory input via the auditory

afferents as the MOCS acoustic reflex, as well as through top-down input from higher-

order structures, which is consistent with MOCS activation based on experience and

auditory context. This anatomy, with both a subcortical reflexive component and

higher-order control, is consistent with the conditions under which the attentional filter

is formed.

1.5 The medial olivocochlear system: Physiology

Single MOCS efferent fibres have been shown to respond to auditory input in guinea

pigs and cats, and were as sensitive and sharply tuned as auditory afferents with the

same characteristic frequency (Robertson and Gummer, 1985; Liberman and Brown,

1986). These recordings from single MOCS efferent fibres demonstrated that MOCS

efferent fibres synapse on OHCs close to the cochlear regions which activated them.

Subsequent research supports these findings, with the extension that some of the single

efferents project to broad areas of the cochlea (Brown, 2014). An important

consequence of this result is that the MOCS acoustic reflex, which is activated by sound

and forms a feedback loop to the OHCs, will suppress the cochlear amplifier in the

cochlear regions which activated it.

The activation of the reflex in response to acoustic elicitors has been measured with

single olivocochlear neuron recordings in guinea pigs. Three groups of olivocochlear

neurons were found, those that responded to ipsilateral or contralateral input were

roughly equal in proportion, and made up the majority of the neurons, with a small


11

proportion responding to either-ear input (Robertson and Gummer, 1985). A strong

effect of binaural facilitation was found, such that even among the neurons that

responded to only one ear there was an increase in firing rate when binaural stimulation

was used (Robertson and Gummer, 1985; Liberman, 1988; Brown et al., 1998). The

stimuli that resulted in the strongest facilitation depended on the characteristic

frequency of the olivocochlear neuron. The facilitation was found to be strongest when

the facilitating stimulus was a pure tone in neurons that responded best to low-

frequency stimuli, but broadband noise was more effective when the neurons responded

best to high-frequency stimuli (Robertson and Gummer, 1985; Liberman, 1988; Brown

et al., 1998). The response of olivocochlear neurons to a continuous broadband noise

resulted in little to no adaptation when the noise was sustained, and this response was

active without significant change for the duration of long periods of noise (Brown,

2001). Therefore, during the measurement of the attentional filter, which includes

transient tones presented in a continuous background noise, there will be consistent

activation of the MOCS acoustic reflex, and the clearly audible cue tones may cause

additional activation of the reflex at the target frequency.

1.6 The medial olivocochlear system: Effects on hearing

The effect of MOCS activation on afferent nerve fibres‟ response to incoming sound

was first tested with electrical and then with acoustic activation of the system. Electrical

stimulation of MOCS efferent fibres in quiet resulted in a rightward level shift in the

firing rate of auditory-nerve fibres in cats, as shown in Figure 1.3. This rightward shift

indicated an increase in the sound level required to reach the same firing rate after

MOCS activation suppressed the cochlear amplifier (Gifford and Guinan, 1983; Gifford

and Guinan, 1987; Winslow and Sachs, 1987). The suppression of the cochlear

amplifier was not accompanied by a reduction in maximum firing rate in almost all the

auditory afferents, although a decrease was apparent in a small subgroup of afferents


12

(Brown et al., 2003). Measuring the effect of acoustic activation of the MOCS took

advantage of the bilateral efferent output of the system by measuring the response of

single auditory nerve fibres during the presentation of noise or tones to the contralateral

ear (Warren and Liberman, 1989). Auditory stimulation of the MOCS in quiet resulted

in rightward shift in the firing rate of auditory afferent fibres in a similar manner to the

electrical stimulation (Kawase et al., 1993).

Figure 1.3. Firing rate of a single auditory nerve fibre in response to pure tone elicitors

with and without additional electrical activation of the MOCS in quiet. The solid line is

for no MOCS activation and the dashed line for with MOCS activation. Figure adapted

from Winslow and Sachs (1987).

This decrease in auditory afferent firing rates was frequency-specific, as suggested by

the anatomy, with contralateral pure tones suppressing auditory fibres at the same

frequency (Liberman and Brown, 1986). Thus, the anatomy and physiology of the

MOCS acoustic reflex, at least as activated in quiet, suggests that the system acts as a

frequency-specific suppressor of the auditory system‟s response to sound via its

suppression of the cochlear amplifier.


13

More important to the present research question is the effect of MOCS activation on

transient pure tones that are presented in background noise, as these are the conditions

used to measure the attentional filter. The effects of MOCS activation on the reception

of transient signals in noise has been tested in experiments on single auditory afferent

fibre responses, which first used electrical stimulation of the MOCS (Winslow and

Sachs, 1987) and then acoustic activation by contralateral broadband noise (Kawase et

al., 1993). In low to moderate levels of background noise the activation of the MOCS

increased auditory afferent fibre thresholds, representing a poorer threshold, but

increased the fibres dynamic firing range, as shown in Figure 1.4. In high levels of

background noise, the activation of the MOCS did not detectably decrease auditory

thresholds, but the increase in dynamic firing range remained. The increase in dynamic

firing range is significant, as a higher dynamic firing range can improve the detectability

of near-threshold signals in noise. In support of this notion, Kawase et al. (1993)

additionally interpreted the firing rates of single auditory nerve fibres in terms of

psychophysical detection thresholds for pure tones in background noise, and showed

that MOCS activation could improve detection thresholds for pure tones presented in

background noise. The increases in dynamic range, and the subsequent improvement in

detection thresholds, were suggested to be due to antimasking. Antimasking, sometimes

known as unmasking, occurs when there is a release from the masking caused by

neuronal adaptation to continuous noise (Smith, 1979). Antimasking is thought to occur

by activation of the MOCS inhibiting the cochlear amplifier, which reduces the cochlear

response to background noise, and releases adaptation at the synapse between the inner

hair cells and the auditory nerve fibres (Smith, 1979; Winslow and Sachs, 1987;

Mulders et al., 2008). The release from adaptation provides the restoration of dynamic

range, which can be seen in Figure 1.4. A higher dynamic range increases


14

discriminability and signal detection in noise, which is consistent with an enhancement

to detection rates at frequency regions under MOCS activation.

Figure 1.4. Firing rate of a single auditory nerve fibre in response to pure tone elicitors

in noise with and without additional electrical activation of the MOCS. The solid line is

for no MOCS activation and the dashed line for with MOCS activation. Figure adapted

from Winslow and Sachs (1987).

Antimasking is not a guaranteed effect of suppression of the cochlear amplifier, and

Kawase et al. (1993) demonstrated its occurrence in guinea pigs only in certain

conditions. When the to-be-detected pure tone was presented at an auditory-nerve

fibre‟s characteristic frequency, antimasking only occurred with relatively high masker

levels, whereas low masker levels increase detection thresholds. When the tone was

presented below the auditory-nerve fibre‟s characteristic frequency, the activation of the

olivocochlear system always resulted in antimasking, regardless of masker level.

Therefore, the results of Kawase et al. (1993) show that antimasking is unlikely to occur

at low masker levels, whereas at higher masker levels antimasking is likely to increase

the detectability of transient signals in a continuous background noise.


15

The effects of antimasking have been shown to persist at higher levels of the auditory

system in guinea pigs. Mulders et al. (2008) measured the effect of electrical

stimulation of the MOCS on single inferior colliculus neurons‟ responses to pure tones

presented in background noise. Eighty-five percent of the inferior colliculus neurons

showed an increase in dynamic firing range that was accompanied by either no change,

or a slight deterioration in auditory threshold, which is similar to the responses of single

auditory afferents discussed above. However, a subset of the neurons showed a

surprising leftward shift in firing pattern with MOCS activation, which indicates

improved auditory thresholds. These responses from neurons in the inferior colliculus

demonstrate the improvement in auditory thresholds that can occur with antimasking,

and support the notion that the activation of an inhibitory system, like the MOCS, can

improve the detectability of near-threshold tones in noise.

1.7 The medial olivocochlear system: In humans

In human research, the activation of the MOCS can be estimated by exploiting the

system‟s effect on otoacoustic emissions (OAEs). OAEs are acoustic signals recorded in

the ear canal that are classically evoked in response to an auditory stimulus. There are

several types of OAEs, which are classified by the stimulus (or lack thereof in

spontaneous OAEs) used to evoke the emission. The most commonly used emissions

are transiently evoked (TEOAE) and distortion product (DPOAE) OAEs (see Shera and

Guinan (1999) for a review). TEOAEs are produced in response to a transient stimulus,

typically a broadband click, and are not considered frequency specific because of the

broadband stimulus. DPOAEs are produced by two pure tone stimuli presented near to

each other in frequency and give a more frequency-restricted measurement of cochlear

amplifier activity. Previous research has demonstrated two, fundamentally different

mechanisms that underlie the generation of otoacoustic emissions (Shera and Guinan,


16

1999), however as the emissions are currently measured it is unclear how to separate

these mechanisms, or what the significance of this separation would be (Shera, 2004).

The magnitude of the OAE emission is used as a measure of health of the cochlear

amplifier because it is reduced with mild sensorineural hearing loss (SNHL) and lost

with moderate SNHL (Kim et al., 1996), although the raw OAE magnitude cannot be

used as a measure of strength of the cochlear amplifier (Kemp, 2002). However, more

relevant to the current research question is the suppression of the OAE response by the

activation of the MOCS. Otoacoustic emissions are typically suppressed using

contralateral broadband noise in a manner consistent with a reduction of gain of the

outer hair cell amplifier by the activation of the MOCS (Veuillet et al., 1991). The

contralateral noise is a potent elicitor of the MOCS acoustic reflex, which then acts to

suppress the cochlear amplifier, and thus reduce the magnitude of the OAE response

(Ryan et al., 1991). This enables the use of contralateral noise suppression of OAEs as

an index of the function of the MOCS in humans: a greater suppression of the OAE by

contralateral noise suggests a greater magnitude of cochlear amplifier suppression by

MOCS activation in that individual (Berlin et al., 1994; Giraud et al., 1995). In support

of OAE suppression as a useful measure of MOCS action, there exists considerable

variation in the magnitudes of OAE suppression in normal hearing individuals (Backus

and Guinan, 2007; Collet et al., 1992), and OAE suppression has been successfully

correlated with speech perception measures that are thought to require the functioning

of the MOCS (Kumar and Vanaja, 2004).

The suppression of the OAE response by MOCS activation has been used to test the

frequency-tuning of the MOCS acoustic reflex in humans. The tuning of the reflex was

tested using pure tones and narrow-band noises that were presumed to activate the

reflex („elicitors‟), and measuring the suppression of a frequency specific type of OAE,

called stimulus frequency OAEs, in the contralateral ear (Lilaonitkul and Guinan,


17

2009b; Lilaonitkul and Guinan, 2012). Pure tone and narrow-band noise elicitors were

found to suppress the contralateral OAEs of similar frequency, which is a result

consistent with the previously discussed anatomy of the MOCS in guinea pigs and cats.

However, this suppression was not restricted to the elicitor frequency, and the

maximum suppression of the contralateral OAEs was achieved when the MOCS

elicitors were skewed up to half an octave from the tested OAE frequency. The

direction of the skew depended on the frequency tested, with a skew towards higher-

frequency elicitors at 0.5 kHz, lower-frequency elicitors at 1 kHz, and frequency-

matched elicitors at 4 kHz. Thus, while the human research supports a suppression of

the cochlear amplifier at the same frequencies used to elicit MOCS activity, the

maximum suppression of the cochlear amplifier by MOCS activation is suggested to be

skewed up to half an octave from the elicitor frequency, depending on the frequency

used.

The suppression of OAEs has been used to test the function of the top-down MOCS

control in humans. The existence of top-down control was confirmed in humans by the

electrical activation of the auditory cortex in humans during pre-surgical brain mapping

for epilepsy (Perrot et al., 2006). During this procedure, the auditory cortex was

electrically stimulated while OAEs were measured in the contralateral ear. There was a

significant reduction in OAE amplitude during the electrical stimulation, consistent with

the presence of the top-down input to the MOCS from the auditory cortex in humans.

Furthermore, this activation has been demonstrated to occur in humans by measuring

OAE amplitude during different task conditions. This is evident in a slight reduction in

OAE amplitude during a visual task as compared with an auditory task (Puel et al.,

1988; Meric and Collet, 1992), although a later study found no change in the

suppression of OAEs by contralateral noise between a visual task and an auditory task

(de Boer and Thornton, 2007). A frequency-specific effect of the top-down MOCS


18

control was suggested by Maison et al. (2001). This study used a variant of TEOAEs

evoked by pure tone pips, and measured the contralateral acoustic noise suppression of

OAEs that were evoked by these pips at two different frequencies during an auditory

task. The tone pips were presented while the participants were simultaneously tasked

with detecting infrequent, near threshold pure tones in noise in the opposite ear, which

matched the frequencies of the tone pips on only some presentations. The results

demonstrated an increased magnitude of suppression of OAEs that were evoked by tone

pips that matched the frequency the participants were attending to, but not of the OAEs

evoked by the tone pips at an unattended frequency (Maison et al., 2001). This suggests

an increase in the suppression of the cochlear amplifier at frequencies under focused

auditory attention. In contrast however, a similar experiment by de Boer and Thornton

(2007), which measured OAE suppression when a participant attended to stimuli

presented in only one ear with dichotic noise, found less OAE suppression in the

attended ear. Therefore, while the actions of the higher-order inputs to the MOCS are

apparently similar to the actions of the MOCS acoustic reflex, in that they would be

active at the target frequency during the attentional filter measurement, there are

contradictory studies that find either no such evidence, or the opposite relationship.

Thus, while the top-down input to the MOCS from higher-order structures may act in a

similar manner to the MOCS acoustic reflex to cause additional suppression of the

cochlear amplifier at the attended target frequency, the evidence supporting this

conclusion is inconsistent.

The above research demonstrates that MOCS activation in humans may have a similar

inhibitory effect on the cochlear amplifier to what was identified in animals in the

previous section. Furthermore, human research into the effects of MOCS activation

supported the presence of an antimasking effect brought about by the system‟s

activation, which can improve the detectability of transient pure tones in noise. The


19

activation of the MOCS has been shown to generally enhance the detectability of

transient tones presented in noise, although this effect depends on the participant and

the conditions used (Micheyl and Collet, 1996). Detection thresholds for 1- and 2-kHz

pure tones presented monotically in broadband noise were measured in the same ear as

TEOAEs, which was done successively with and without a contralateral broadband

noise thought to activate the MOCS. The detection thresholds for the 2-kHz tone

improved with the addition of the contralateral broadband noise, and the magnitude of

this improvement correlated with the magnitude of TEOAE suppression. This result is

consistent with an improvement in signal-in-noise detection rates associated with the

activation of the MOCS, in this case by the contralateral broadband noise, and this

improvement scaled with the index of MOCS function. No such relationship was

present for the 1-kHz pure tone. The frequency-specific effects may be due to the

broadband clicks used to test the OAE suppression. Similar research used DPOAEs to

assess MOCS strength, and again correlated this strength with the detectability of

masked tones at 1 and 2 kHz (Bhagat and Carter, 2010). Using DPOAEs, there was a

positive correlation between the magnitude of suppression of DPOAEs and reduced

masking of only 1-kHz pure tones.

1.8 The medial olivocochlear system: Forming the attentional filter

Overall, the above research demonstrates that the activation of the MOCS can cause

frequency specific suppression of the cochlear amplifier, and the system can be

activated in response to pure-tones, like the cues used to form the attentional filter, or in

response to top-down control, consistent with the filter‟s formation in response to

complex cues. Furthermore, the effect of MOCS activation has been demonstrated to

cause antimasking-mediated enhancements of pure-tones in noise in animals, and in

humans there is limited evidence that the system can improve the detectability of


20

transient tones. Therefore, the MOCS has an anatomy, physiology and function

consistent with a role in generating the attentional filter.

The specific role that the MOCS has in generating the attentional filter is likely to be an

antimasking-based enhancement at the target frequency. The antimasking effect,

schematized in Figure 1.5 would rely on the activation of the MOCS at the target

frequency, either by the clearly-audible cue tone activating the MOCS acoustic reflex,

or by more-frequent target presentations activating the MOCS by its top-down inputs.

The resulting suppression of the cochlear amplifier at the target frequency then causes

an antimasking effect to enhance the target‟s detection rate, with a rapid drop-off of this

effect with increasing frequency separation from the target. Previous research by Tan et

al. (2008) has suggested that the filter is formed both by an enhancement at the target

frequency as well as a suppression at the probe frequencies. It is unclear how the MOCS

might be involved in this suppression, when the anatomy and physiology discussed so

far has suggested a tonotopic tuning of the MOCS, in which the system suppresses the

cochlear amplifier at, or very near to , the frequencies at which it is active. Therefore,

the present thesis is concerned primarily with MOCS-mediated enhancement at the

target frequency, although probe suppression is not discounted.


21

Figure 1.5. Schematic of the proposed role of the MOCS in forming the attentional

filter, demonstrating the suggested antimasking effect at the target frequency.

Support for a causal role for the MOCS specifically forming the attentional filter is

provided by Scharf et al. (1997), who measured auditory function before and after a

vestibular neurectomy. The vestibular neurectomy is a surgical procedure to relieve

severe vertigo, generally associated with Ménière‟s disease, and all of the participants

included in Scharf‟s study except one were diagnosed with Ménière‟s disease. In

addition to relieving severe vertigo, the vestibular neurectomy sections the MOCS

efferent connection to the cochlea as the system‟s efferent output travels with the

inferior vestibular nerve (Bodian and Gucer, 1980). Scharf and his colleagues measured

the auditory capacities of 16 individuals before and after undergoing the surgery,

including measurements of pure tone thresholds, intensity discrimination, loudness

adaptation, and, of relevance to the current work, the difference in detection rate

between expected and unexpected near-threshold tones presented in background noise.


22

The only significant change was shallower attentional filters in participants who

previously showed normal filters, as shown in Figure 1.6. The loss or reduction in the

formation of the attentional filter with the presumed total loss of MOCS efferent output

was taken as support that the MOCS has a role in the generation of the attentional filter.

Figure 1.6. Mean difference (± SD) in detection rate between target tones and lower-

(LF) or higher- (HF) frequency probe tones in noise either before the surgery (n = 8), or

in the contralateral healthy ear (n = 3) (left panel) and after (right panel) a vestibular

neurectomy. Prior to the surgery participants showed a larger decrease in detection rate

between the target and the probes relative to after the surgery. This demonstrates the

decrease in depth of the attentional filter with the sectioning of the MOCS output,

however many participants retain a target-probe difference at or greater than 10%. The

figure was composed with estimates from figures published in Scharf et al. (1997).

Similar research has used dysfunction of the MOCS, presumed from hearing loss, to test

the proposed role for the system in forming the attentional filter. Moore et al. (1996)

measured the attentional filter in two individuals with moderately-severe SNHL. SNHL

is typically, but not necessarily, caused by the loss or damage of the OHCs, which are

the MOCS efferent targets. Individuals with a moderately-severe SNHL may have a


23

near-complete loss of OHC function (Stebbins et al., 1979; Hamernik et al., 1989).

Moore et al. (1996) found no evidence for the attentional filter in the two individuals

with SNHL, consistent with the loss of the filter with impairment to the MOCS action

on the cochlea. In this study, Moore et al. suggest that the loss of the filter in SNHL

participants is due to the broadening of auditory filters, and thus a loss of frequency

selectivity. This loss of frequency selectivity may have prevented the cue tone from

producing a distinct pitch cue for the auditory system, and therefore lead the SNHL

participants to adopt a “broadband” listening strategy that prevented the formation of

the attentional filter. However, the study did not address the potential involvement of

the MOCS in the formation of the attentional filter, and so the possible contributions of

the loss of the MOCS efferent targets, the OHCs, was not addressed.

In similar research Tan (2008) measured the benefit of a cue tone to the detection of

near-threshold tones presented in noise at a randomly selected frequency in eight SNHL

participants with moderately-severe to profound SNHL. Tan (2008) additionally tested

for the absence of detectable OAEs as an indicator of OHC impairment. The eight

SNHL participants showed a loss of the cue-benefit, which equated to a 3-dB

improvement in detection thresholds in a group of normal hearing individuals. Tan had

argued that this cue-benefit was an important part of the filter‟s formation; however, no

direct measurement of the attentional filter was made. The apparent loss of the

attentional filter in Moore et al.‟s SNHL participants, and the loss of a cue-benefit in

Tan‟s SNHL participants is consistent with the results of Scharf et al.‟s vestibular

neurectomy studies in suggesting that the normal formation of the attentional filter, or at

least components of the filter in the loss of the cue-benefit, is dependent on the normal

function of MOCS action on hearing.

Improved speech reception in noise might be expected from a functioning attentional

filter, as the filters presence indicates an ability to attenuate unwanted signals in favour


24

of a repeated, or expected signal. Evidence of such an improvement with increasing

OAE suppression by contralateral broadband noise would provide additional support for

the proposed role for the MOCS in forming the attentional filter. In line with this

expectation, some studies have found a positive correlation between the magnitude of

suppression of OAEs by contralateral broadband noise and improvements in speech-in-

noise intelligibility (Giraud et al., 1997, De Boer and Thornton, 2008, Kumar and

Vanaja, 2004). However, conflicting results are present in the literature, as other studies

have either failed to replicate this relationship (Wagner et al., 2008), or found the

opposite relationship (de Boer et al., 2012). The most apparent sources for these

conflicting results are a change in the type of OAE measurement and the speech-in-

noise intelligibility measurement used in the experiment. The experiments that found an

improvement in speech-in-noise intelligibility used the suppression of TEOAEs, which

are evoked in response to broadband click stimuli. In contrast, Wagner et al. (2008)

found no relationship between speech-in-noise intelligibility and the suppression of

DPOAEs, which are measured using 2 pure tones near to each other in frequency. These

two OAE types are thought to be produced by two different mechanisms in the cochlea

(for a review see Shera and Guinan (1999)), although the significance of a result present

with one OAE type but not the other is unclear. The conflicting results may also be due

to different stimuli used; in almost all experiments listed above the speech stimuli were

different. The clearest example of the effects of a change in stimulus comes from de

Boer et al. (2008) and de Boer et al. (2012). These studies used identical procedures and

equipment, with the only changes in the participants and the speech signals used. In the

studies, the suppression of TEOAEs by contralateral noise was correlated with the

discrimination of /bee/ to /dee/ in 2008, and then of /ga/ to /da/ in 2012. Significant

correlations between OAE suppression and phoneme discrimination were found in both

studies, but they were in opposite directions: a positive correlation for improved


25

phoneme discrimination with increased OAE suppression was found in 2008, but in

2012 a negative correlation for impaired phoneme discrimination was found. The above

studies demonstrate a complex relationship between the activation of the MOCS and the

detection of signals in noise, in which the type of OAE used to estimate MOCS activity

and the type of signal that is to be detected has important consequences on the direction

of the relationship.

Overall, the above research supports a role for the MOCS in improving the detectability

of transient tones within a background noise. The most direct support that the MOCS

forms the attentional filter is the loss of the filter in Scharf et al.‟s participants after a

vestibular neurectomy. This result occurred without any changes in pure-tone thresholds

or frequency discrimination, and so cannot be explained by any impairment to the

auditory system except for a reduction in MOCS efferent control of the cochlear

amplifier.

1.9 The medial olivocochlear system: Related structures

When considering the involvement of the medial olivocochlear system in the formation

of the attentional filter, it is important to consider related structures which may be

difficult, or impossible, to separate from the medial olivocochlear system during the

experiments.

In addition to the medial olivocochlear efferents, which have myelinated axons that

originate from the medial part of the superior olivary complex, there are lateral

olivocochlear efferents, which have unmyelinated fibres that originate from the lateral

part of the same structure (Rasmussen, 1960). These lateral olivocochlear efferents,

which form the lateral olivocochlear system (LOCS) with their inputs, travel through

the vestibular nerve as the MOCS efferents do, but project to the dendrites of the

auditory afferent fibres at the base of inner hair cells (Warr and Guinan Jr, 1979). The


26

synapses of the LOCS efferents contain ACh, although there is evidence of additional

neurotransmitters and neuromodulators, including GABA and CGRP in humans

(Schrott-Fischer et al., 2007). The LOCS receives input from the auditory afferents, but

the efferent fibres have not been directly shown to respond to sound. The LOCS is

presumed to respond to sound, as it receives input from the auditory afferents, and the

lateral superior olivary complex from where the fibres originate has been shown to

respond to ipsilateral auditory input (Adams, 1995). The LOCS cannot be directly

activated by electrical stimulation, as its unmyelinated efferent fibres cannot be

stimulated electrically, but indirect activation is possible by the electrical stimulation of

the inferior colliculus (Groff and Liberman, 2003). This indirect electrical stimulation

resulted in complex changes in auditory nerve firing rates, which took over one minute

to take effect, and lasted up to 5 to 20 minutes after the stimulation ended. Thus, the

function of LOCS activation is unclear, although two proposed roles are the balance of

left to right auditory inputs (Darrow et al., 2006) (although subsequent research by

Larsen and Liberman (2010) did not replicate this result), and the protection of the

auditory system from the effects of aging (Liberman et al., 2014). Importantly for the

work described in this thesis, the MOCS and LOCS systems may interact, and

disentangling the effects of the systems is not always possible. These interactions occur

at a basic level because the systems both receive auditory afferent input, and act to

change the auditory nerve‟s response to input. However, there is evidence for a direct

connection, as the LOCS efferent fibres appear to synapse on MOCS efferents en

passant (Liberman, 1980). Thus, the potential interactions between the LOCS and the

MOCS may prevent a clear separation between the actions of the two systems.

Both the MOCS and the LOCS have collateral branches to the cochlear nucleus in

addition to their efferent outputs to the cochlea (Brown et al., 1988; Ryan et al., 1990).

Collaterals from the two olivocochlear systems innervate specific cell types in the


27

cochlear nucleus, and there is evidence of both excitatory and inhibitory effects on

specific cell types (Mulders et al., 2002; Mulders et al., 2003). The function of these

collaterals is unclear, although the MOCS collaterals have been proposed to modulate

the system‟s inhibitory effects on the cochlear amplifier (Benson and Brown, 1990; Kim

et al., 1995; Mulders et al., 2003). Previous research on the formation of the attentional

filter in individuals with altered auditory system function has not tested the potential

influence of the MOCS collaterals on the filter‟s formation. For example, the sectioning

of the vestibular nerve in Scharf et al.‟s research (1997) might not directly change the

collaterals activation in the cochlear nucleus, nor would the loss of the MOCS efferent

targets after SNHL in Moore et al. (1999). It is unclear whether the collaterals have any

role in forming the attentional filter, if indeed the MOCS is responsible for the filter‟s

formation, however the function of the collaterals is likely to be linked to the function

of the MOCS efferents, and their presence must be considered when measuring MOCS

action.

1.10 Central mechanisms

Prior research has argued that auditory attention relies on the formation of perceptual

objects in a manner similar to visual attention, and it is this formation of perceptual

objects that drives the detectability of target stimuli versus off-target stimuli (Shinn-

Cunningham, 2008). Indeed, recent research has demonstrated that when attention is

focused on a single speaker within a background noise, auditory cortical activity

synchronizes with the temporal modulations of the speaker, and that the precision of

this synchronization predicts the speech recognition of the listener (Ding and Simon,

2013). Thus, the detectability of complex speech signals in background noise may be

directly linked to centrally-mediated auditory attention, and the formation of the

attentional filter may be partially a result of these central mechanisms. However, a filter

formed only by central mechanisms is not sufficient to explain the loss of the filter after


28

a vestibular neurectomy in Scharf et al‟s studies, in which severing the MOCS efferent

fibers resulted in a loss of the attentional filter, but no other significant impairments to

auditory function (Scharf et al., 1994; Scharf et al., 1997). This strongly suggests a

significant involvement of the efferent output of the MOCS in the formation of the

attentional filter. In the present work, the MOCS is suggested to modulate the

detectability of transient tones prior to these tones becoming perceptual objects, and

therefore these central mechanisms are not a focus of the present work.

1.11 Structure and aims of the thesis

This thesis examines a suggested role for the medial olivocochlear system‟s efferent

control of the cochlear amplifier in forming the attentional filter. Previous research has

established that the MOCS has an anatomy, physiology and function consistent with the

proposed role, and that severely reducing the MOCS action on the cochlea, through a

moderately-severe SNHL or a vestibular neurectomy, reduces the depth of the

attentional filter. The present work aims to correlate the strength of the MOCS with the

depth of the attentional filter, as well as extend the research that shows that the

attentional filter is impaired in conditions presumed to impair the MOCS action on

hearing. Three research questions will be addressed in the thesis. First, is there evidence

that the MOCS acts to form the attentional filter in normal hearing individuals? Second,

does the reduction in depth of the attentional filter with presumed MOCS impairment

scale with the severity of that impairment? Third, can the attentional filter be formed in

conditions where no MOCS action on hearing is possible? The structure of the thesis is

as follows:

Chapter two details the psychophysical methods common to all experiments.

Chapter three focuses on the contralateral noise suppression of OAEs as an index of the

strength the MOCS acoustic reflex in normal-hearing participants, and whether this


29

correlates with the depth of the attentional filter. The aim of these experiments was to

investigate whether individuals with relatively strong MOCS acoustic reflexes had

deeper attentional filters when compared with individuals with relatively weak reflexes.

Chapter four continues the use of auditory dysfunction to test the MOCS involvement in

forming the attentional filter, using individuals with SNHL and conductive hearing loss.

SNHL with established OHC damage, by the loss of detectable OAEs, are considered to

have reduced MOCS function due to a loss of the MOCS efferent targets, and there is

evidence that the reduction in MOCS function scales progressively with increasing

hearing loss. This is an opportunity to investigate the formation of the attentional filter

in individuals with decreasing MOCS function as hearing loss increases. Conductive

hearing loss participants were used as a control group presumed to have intact cochlear

amplifiers, but long-standing hearing impairments. The aim was to investigate whether

individuals with SNHL show similarly impaired attentional filters to Scharf et al.‟s

(1997) vestibular neurectomy participants, and if this impairment scaled with the

severity of the hearing impairment.

In chapter five, the attentional filter is measured in individuals presumed to have no

remaining MOCS action on hearing, due to profound SNHL and the use of a cochlear

implant (CI) that bypasses the cochlear amplifier. The experiments contained within this

chapter test for the presence of the attentional filter in six individuals with CIs using

acoustic presentation of the stimuli with a loudspeaker. CI recipients give a unique

perspective on selective attention because the cochlear amplifier and much of the

peripheral auditory system are bypassed, and this is combined with near-normal

auditory thresholds, a substantially different electrical form of hearing, and a period of

auditory relearning.


30

In chapter six, attentional filters are again measured in CI recipients; however, the

stimuli are presented using a programmed, direct stimulation mode. This stimulation

mode does not include an acoustic stimulus, and so there is no possible involvement of

the MOCS efferent control of the cochlear amplifier on the reception of the signals. In

addition, the programmed, direct stimulation mode enables a specific set of stimuli to be

presented to each participant, without the use of the commercial speech processor that

was used in the experiments of chapter five.

Chapter 2. General Methods

General methods

32

2.1 Acoustic Stimuli

All experiments were conducted in a sound-attenuating room using a Windows PC with

an ASUS Xonar STX soundcard located in an adjacent room. Except when otherwise

specified, the continuous broadband noise was generated on a separate Windows laptop

running SoundForge XP v4.5. The amplitude of this noise was calibrated to 60 dB(A)

SPL with a Brüel & Kjær 2260 Sound Level Meter combined with a B&K Artificial Ear

Type 4152. Figure 2.1 shows the spectrum of the background noise, with a flat response

from 1 to 3 kHz, and less than 1-dB variation in power. The output of the stimuli-

generating Windows PC and the noise-generating Windows laptop were mixed by a

Behringer Eurorack MX 802, and presented diotically in all experiments except those in

chapter 5, with a pair of Sennheiser HD-280 PRO headphones.

Figure 2.1. Sound spectrum of the broadband noise used during the experiments. Sound

spectrum recorded using the same equipment used to calibrate the 60 dB(A) background

noise, with the output of the sound level meter to a Powerlab 4ST by ADInstruments in

10 second samples. Units are reported in dB relative to 0 mV recorded by the meter,

with an overall amplitude of 60 dB(A) SPL.

General methods

33

2.2 Psychophysical procedures

The psychophysical tasks described in this thesis use a 2 interval forced choice design

(2IFC), the design of which is shown in Figure 2.2. The 2IFC structure presents two

detection intervals, only one of which contains a to-be-detected signal, and requires the

participant to select the interval with the signal. This avoids criterion effects because it

forces the participant to choose which detection interval contained a signal, rather than

whether the signal was presented. Because there are two intervals to choose from, when

a participant is unable to detect the signal their detection rate will be at 50%.

Figure 2.2. Structure of the 2IFC procedure. Each trial began with a 600-ms period with

a blank interval presentation box. The first 300-ms held a cue in some experiments, but

otherwise contained only noise. The first detection interval began at 600 ms, as

indicated by a “1” in the interval presentation box, which remained for the duration of

the interval. The interval presentation box was blank for the 300 ms between the two

detection intervals, until the second detection interval at 1200 ms. Participants were

prompted to respond 300 ms after the completion of the second detection interval, and

no response input was recorded prior to this request. The next trial began 1 s after the

participant‟s response. In almost all the experiments, broadband noise was present

continuously throughout the experiment.

There are two procedures that are common to each experiment in this thesis. The first is

a threshold estimation procedure, which was used at the beginning of each session. The

second is the probe-target procedure, which was used to measure the attentional filter.

Small alterations are made to the procedures in each chapter, and these will be defined

in the appropriate chapters. The psychophysical procedures were programmed in

General methods

34

LabVIEW 7 or 12 and presented on a Windows 7 PC with an ASUS XONAR STX

Soundcard, at a 44100 Hz sample rate.

2.3 Auditory thresholds

Auditory thresholds were estimated in the presence of continuous background noise

using a three-down one-up adaptive staircase procedure that produced a threshold

corresponding to a 79% detection rate (Levitt, 1971). The threshold procedure used the

2IFC structure described above. One of the 300-ms long intervals was randomly

assigned to contain a stimulus, chosen with a 50% probability and no constraints.

Subjects signalled their response by left clicking if they thought they heard the signal in

interval 1, or right clicking for interval 2. Correct responses were signalled to the

participant with a green visual indicator and incorrect responses by a red visual

indicator displayed on the monitor. Initially, a correct response changed tone amplitude

in 5-dB steps, which changed to 1-dB steps after the first incorrect response. Eighty

trials were presented for each threshold procedure, and the mean of the last eight

reversals, i.e. a change from correct-correct-correct-incorrect or incorrect-correct, was

taken as the threshold estimate.

2.4 Cued probe-target procedure to measure the attentional filter

The attentional filter was measured over at least 4 one hour long experimental sessions.

The first session contained 3 practice runs each of the threshold and probe-target

procedures. Subsequent sessions, which were held at least one hour but not more than

one week apart, began with threshold estimation, and then 3 runs of the probe-target

procedure. The probe-target procedure is based on those previously reported in the

literature (Greenberg, 1962; Dai et al., 1991; Schlauch and Hafter, 1991; Botte, 1995;

Tan et al., 2008).

General methods

35

The probe-target procedure used the same 2IFC structure to measure the attentional

filter, with the addition of a cue tone in some experiments. Four probes were presented

around the 2.0-kHz target frequency; the specific probe frequencies will be outlined in

the relevant chapters. In the experiments with a cue tone, shown in table 2.1, a 300-ms

2-kHz cue tone preceded the first detection interval by 300 ms, and was presented at 14

dB above the 2-kHz target tone‟s threshold. In the experiments with normal-hearing

participants, the target and all probes were presented at the previously measured 2.0-

kHz threshold. The alternative procedure for hearing impaired participants will be

outlined in the relevant chapters. Each run of the experiment contained 192 trials, with

the order of the to-be-detected tones set at the beginning by randomizing blocks of 48

trial tones plus 4 of each of the probe tones equating to 75% target presentation and

equal numbers of each of the probe tones over the remaining 25%. The 192 trial runs

were repeated 3 times in each session, with a 5 minute break between each run. In total

the target was presented 1296 times, and each probe 108 times for each participant.

Table 2.1. Inclusion of a cue tone during the attentional filter experiment.

Experiment Cue?

Chapter 3: Normal hearing participants Yes

Chapter 4: Hearing impaired participants Yes

Chapter 5: Cochlear Implant recipients using

acoustic presentation No

Chapter 5: Cochlear Implant recipients using

programmed, direct presentation Yes

General methods

36

Chapter 3. Formation of the attentional filter in normal-hearing

participants

Formation of the attentional filter in normal hearing participants

38

3.1 Introduction

The formation of the attentional filter is impaired when the efferent fibres of the MOCS

are sectioned (Scharf et al., 1994; Scharf et al., 1997). Currently, this is the only direct

evidence that the function of the MOCS affects the formation of the attentional filter,

and it relies on an abnormal, surgical dysfunction of the MOCS in individuals with pre-

existing medical conditions, mainly Ménière‟s disease. At present, no research has

demonstrated a relationship between the function of the MOCS and the formation of the

attentional filter in individuals with normal MOCS function and normal auditory system

function. Such a relationship is expected if the MOCS does act to form a significant

portion of the attentional filter.

To study the relationship between the function of the MOCS and the formation of the

attentional filter, the experiments included in this chapter used the suppression of OAEs

by contralateral broadband noise as an index of MOCS function (Berlin et al., 1994).

This measurement of MOCS strength was then correlated with specific features of the

attentional filter, to test whether a stronger MOCS was associated with a deeper

attentional filter. In past literature the typical range of OAE suppression has been

between -1 to 3 dB, which has correlated with up to 10% improvements in phoneme

recognition (Giraud, 1997), or a 5 dB improvement in the detection threshold of a multi-

tone complex in noise (Micheyl et al., 1995). Previous research has suggested that the

attentional filter may be formed by up to 7 dB of effective suppression at the distant

probes (Dai et al., 1991), which provides an adequate size of change to be detectable

with OAE suppression, if this relationship is present.

The experiments described in this chapter aimed to correlate the magnitudes of

suppression of both TEOAEs and DPOAEs by contralateral broadband noise with

specific features of the attentional filter. In the primary experiment, a measurement of


39

OAE suppression was made in each individual in a separate session, which was held

after three sessions used to measurement the attentional filter. This is a commonly used

procedure in the literature, and is based on the assumption that the magnitude of OAE

suppression by contralateral broadband noise is a stable measurement in an individual

over time. A previous study supported the assumption by showing that the suppression

of TEOAEs is stable in individuals across sessions, with a within-subject variability of

0.01 to 0.07 dB, and a Cronbach‟s alpha of 0.8 (Mishra and Lutman, 2013). The same

data do not exist for the suppression of DPOAEs. A preliminary study is included in this

chapter to examine the validity of this assumption in comparison with the previous

research on TEOAEs, and as an extension of this research to DPOAEs.


40

3.2 Methods

3.2.1 Participants

Six male and 9 female individuals ranging in age from 19 to 25 years participated in this

research (median age = 22). Participants had normal hearing (<20dB HL) from 250 Hz

to 8 kHz as tested using a Grason Stadler GSI 61 Clinical Audiometer. All

psychophysical stimuli were presented diotically through Sennheiser HD280 Pro

headphones.

3.2.2 MOCS acoustic reflex strength measurement

The strength of MOCS acoustic reflex in each subject was assessed using contralateral

noise suppression of both DPOAEs and TEOAEs using an Otodynamics ILO292 with

an Otodynamics DPOAE Probe. Probe fit was tested at the beginning of each trial using

the procedure specified by Otodynamics, and the probe was left in position between

trials unless a refit was required, as indicated by the Otodynamics ILO v6 software.

Each OAE waveform was averaged into one of two alternating buffers, A and B. The

response magnitude was measured from the average of the A and B buffers, while noise

was estimated from an A minus B waveform. Waveform reproducibility was measured

by the cross-correlation of the averaged A and B buffers, and OAEs were only included

when reproducibility was above 80%. All normal hearing participants had DPOAE

amplitudes greater than 5 dB tested for L1 = L2 = 65 dB elicitors, with f2 = 2 kHz and

with f1/ f2 = 1.22

DPOAE fine structure was assessed by measuring the DPOAE responses for L1 = L2 =

55 dB elicitors, with f1/f2 = 1.22 and f2 frequencies of 220 Hz above and below 2 kHz

measured in small increments (initially 50 Hz followed by 20 Hz in the vicinity of

identified peaks in DPOAE amplitude). Following the method described by Abdala et

al., (2009) DPOAE suppression was measured at an individual‟s peak, or maximum,


41

DPOAE response in their fine structure (Abdala et al., 2009). In cases where two peaks

of identical amplitude were found, the peak closer to 2 kHz or the peak at a higher

frequency was used. For suppression measurements, a DPOAE I/O function was

measured for L1 = L2 = 45 to L1 = L2 = 55 dB SPL in 1 dB increments, with f2 equal to

each individual‟s peak of DPOAE amplitude and with f1/f2 = 1.22. For each

measurement, DPOAE amplitude was averaged over at least 60 seconds. A WO

condition that did not include contralateral noise was interleaved with a WN condition

that included a contralateral 60 dB SPL broadband noise, presented with the Sennheiser

HD-280 PRO headphones. The conditions were separated by 60 seconds. Three

measurements each of the WO and WN conditions were made, and DPOAE suppression

is expressed as a decrement from the averaged WO amplitude minus the averaged WN

amplitude at either the L1 = 45 or L1 = 55 dB SPL amplitudes. Figure 3.1 shows

examples of the OAE data collected during the experiments.


42


43

Figure 3.1. OAE responses for two subjects included in chapter 3. A: DPOAE

amplitude spectrum for a single measurement, including the elicitors used to evoke the

emission, the emission itself, and the noise included in the recording. B: DPOAE fine

structure measured for a single participant, showing DPOAE measurements that were

taken from 1850 to 2150 Hz at 50-Hz intervals, with a further 4 measurements taken

around the highest DPOAE response at ±10 Hz and ±20 Hz intervals. The arrow

indicates this individual‟s peak DPOAE response magnitude. C: DPOAE input/output

function for a single participant. WO represents the without noise condition, and WN

the with contralateral broadband noise condition. Subsequent DPOAE suppression is

measured as the decrement between the WO and WN conditions at the L1 = 45 or L1 =

55 dB amplitude. D: TEOAE response waveform for the WO condition (black line) and

WN condition (grey line) from a single participant.

The TEAOE threshold was determined following the procedure described by De

Ceulaer et al. (2001). TEOAEs were evoked by brief clicks (80-µs duration) in the

presence of 60-dB SPL broadband noise in the contralateral ear. Clicks were presented

at 50 Hz, in the linear presentation mode which presents all clicks at an equal

magnitude. Although this presentation mode does not remove the presence of the initial

click from the recording, known as the click artefact, like the non-linear mode, which

presents 3 clicks equal in magnitude and a fourth click with inversed polarity and tripled

in magnitude, it does keep the entire emission intact, and preserves useful emission

information. In the following data, the click artefact is limited by the relatively low click

amplitude. The ILO292 software uses a fast Fourier transform (FFT) to measure the

magnitude of the TEOAEs over a window beginning 20 ms after the click, with a cosine

window applied to the first 2.5ms to attenuate the ringing of the click stimulus. Initially

the clicks were presented at 60 dB SPL, which was decremented in 3-dB steps until the

TEOAE was no longer detectable above the noise floor. Subsequent TEOAE testing

was performed 12 dB above this threshold in each participant, which previous research

has demonstrated to be the most effective elicitor amplitude with a 40 dB SPL

contralateral noise suppressor (De Ceulaer et al., 2001). Each trial ran for 260


44

presentations of the click train. A WO condition that included no contralateral noise was

interleaved with a WN condition that included a contralateral 60 dB SPL broadband

noise, presented with the Sennheiser HD-280 PRO headphones. TEOAE suppression

was expressed as the decrement in TEOAE amplitude between the averaged WO and

the averaged WN conditions.

In addition to activating the MOCS acoustic reflex, contralateral broadband noise has

been shown to activate the middle-ear muscle reflex, and this activation can confound

the effect of MOCS activation. Ten participants were tested for the activation of the

reflex by testing for an observable change in admittance of the tympanic membrane

caused by the presentation of up to 95 dB SPL contralateral broadband noise using the

same equipment as used in the later experiments. The activation of the reflex was

monitored using a Grason-Stadler GSI-38 Auto Tymp.

3.2.3 Preliminary study

A preliminary study was used to establish typical OAE magnitudes, and the variability

and test-retest repeatability of the suppression of the OAEs. The OAE measurements

were paired with a simplified selective attention procedure on each session, which was

used to ensure that the detection rate of the target and a representative probe were

within a range which would allow an appropriate comparison in the following

experiment. Reliability of the OAEs was measured using Cronbach‟s α, which was

calculated using the following equation:

where n is the number of sessions (4), c is the average of the covariance‟s for each

session, and v is the average variance across the sessions. The interpretation of the

subsequent α is for: α ≥ 0.9 indicates excellent reliability, α ≥ 0.8 is good reliability, α ≥


45

0.7 is acceptable, α ≥ 0.6 is questionable, α ≥ 0.5 is poor, and less than 0.5 is

unacceptable. Cronbach‟s α calculation and interpretation was taken from the protocol

outlined by Mishra and Lutman (2013).

Three of the fifteen subjects participated in the preliminary study. The study included 4

sessions over two days, with a morning and afternoon session each day, which were

matched in time the following day. Each session consisted of a measurement of DPOAE

and TEOAE suppression, followed by a threshold estimation and then a shortened cue-

probe procedure. The shortened cued probe-target procedure used the same 2IFC

structure as the probe-target procedure described in section 2.3. Only a single 2.08-kHz

probe was included in the measurement to accompany the 2-kHz target tone. The target

and the probe were presented with equal probability, with 192 presentations of each in

every session.

3.2.4 Primary experiment: Attentional filters and the suppression of OAEs

This experiment evaluated the attentional filter and its relationship to the contralateral

broadband suppression of OAEs measured in all 15 subjects. OAE suppression was

measured in each subject in a single separate session after all the psychophysical

measurements had been completed. Participants attended 5 sessions, the first of which

was to conduct initial hearing tests, perform initial OAE calibration as described above,

and two training runs each of the below experiments. Sessions two to four were used to

measure the attentional filter, and then DPOAE and TEOAE suppression were

measured on session 5.

Sessions used to measure the attentional filter began with a threshold measurement

(described in section 2.2) for the 2-kHz target tone in noise. After the threshold

measurement there were 3 runs of the cued probe-target procedure. The cued probe-

target procedure (described in section 2.4) used a 75% presentation of the 2-kHz target


46

and 25% presentation of the probes at 1.8, 1.92, 2.08 and 2.2 kHz, which were

presented with equal number.

3.3 Results

3.3.1 Activation of the middle-ear muscle reflex

The threshold for activation of the middle-ear muscle reflex was monitored in 10 of the

15 subjects, using broadband noise of up to 95 dB SPL. Six of the subjects showed

activation of the reflex, with one subject showing activation at 75 dB SPL, four at 80 dB

SPL, and one at 85 dB SPL. The other 4 subjects showed no measureable middle-ear

reflex activation at contralateral noise levels of up to 95 dB SPL. The amplitude of

broadband noise used in the later experiments was 60 dB SPL, and so not expected to

activate the reflex.

3.3.2 Preliminary study: TEOAEs

Contralateral broadband noise reliably suppressed TEOAEs, with the three subjects

included in the preliminary study all showing a suppression of the TEOAE magnitude in

each session, as shown in Table 3.1, and as measured by the decrement from the

without noise emission amplitude from the with noise emission amplitude. Table 3.1

also shows the variations in the magnitudes of TEOAE suppression within individuals,

with the coefficient of variation for subjects 1, 2 and 3 equal to 0.26, 0.08 and 0.25

respectively. Figure 3.2 shows the raw TEOAE magnitudes for both the without noise

and with contralateral noise conditions. A concern was whether the magnitude of the

TEOAE suppression was dependent on the initial magnitude of the TEOAE in quiet,

however plotting the raw TEOAE magnitude for with and without noise shows an

approximately linear relationship that is parallel to y = x, which demonstrates that the

magnitude of TEOAE suppression was independent of the initial emission magnitude.


47

Table 3.1. Magnitudes of TEOAE suppression with mean and standard deviations for

the three subjects on each session in the preliminary study.

Figure 3.2. The relationship between TEOAE response without (WO) and with noise

(WN) for 3 participants over 4 experimental sessions. The dotted line shows y = x.

TEOAE suppression shows a relatively small amount of variability within individuals

when averaged across the four sessions,

The TEOAE measurement was taken twice in the 15 individuals for the experiment

below, to calculate the reliability of the magnitude of TEOAE suppression in the form

of Chronbach‟s alpha. For the suppression of TEOAEs, α = 0.79. TEOAEs were

measured at +12 dB SL, and for the 15 participants the median TEOAE amplitude was

62 dB SPL ± 6.1, which equates to a median TEOAE threshold of 40 dB SPL.

Session 1 Session 2 Session 3 Session 4 Mean SD

Subject 1 0.70 0.75 1.10 1.30 0.96 0.25

Subject 2 1.70 1.45 1.45 1.40 1.50 0.12

Subject 3 0.75 1.30 1.25 1.60 1.23 0.31


48

3.3.3 Preliminary study: DPOAEs

Contralateral broadband noise resulted in an overall suppression of DPOAEs in all

participants, although as shown in Table 3.2, in Subject 2 there was one session which

had a small increase in emission amplitude. The magnitude of DPOAE suppression

shows more variability when compared to that of TEOAEs, with the coefficient of

variation for subjects 1, 2 and 3 equal to 0.44, 0.92 and 0.19 for L1 = 45 dB DPOAEs,

and 0.57, 0.31 and 0.39 for L1 = 55 dB DPOAEs respectively. Figure 3.3 shows the raw

DPOAE magnitudes for the without noise and with contralateral noise conditions. As

reported for the TEOAEs, the raw TEOAE magnitudes for both the with noise and the

without noise conditions show an approximately linear relationship that was parallel to

y = x, which demonstrates that the magnitude of DPOAE suppression is independent of

the initial emission magnitude.

Table 3.2. L1 = 45 and L1 = 55 DPOAE suppression values on each of the 4

experimental session as well as the mean and standard deviation across the sessions for

the three subjects in the preliminary study.

L1 Session 1 Session 2 Session 3 Session 4 Mean SD

Subject 1

45 1.3 1.0 2.5 2.5 1.8 0.80

55 1.9 0.2 1.3 1.6 1.3 0.74

Subject 2

45 -0.1 1.1 4.6 4.2 2.5 2.31

55 1.3 2.4 2.7 2.9 2.3 0.71

Subject 3

45 3.1 4.6 3.9 3.1 3.7 0.71

55 1.3 1.8 1.7 0.6 1.4 0.55


49

Figure 3.3. The relationship between DPOAE response without (WO) and with noise

(WN) for 3 participants over 4 experimental sessions for the L1 = 45 and L1 = 55 dB

DPOAEs. The dotted line shows y = x.

The reliability of the DPOAE measurements was slightly lower than that of the TEOAE

measurements for the L1 = 45 dB DPOAEs, with α = 0.72, but identical to the TEOAE

measurements for the L1 = 55 DPOAEs, with α = 0.79.

3.3.4 Preliminary study: OAE relationships and the selective attention task

The use of contralateral noise suppression of OAEs in the literature typically includes

only a single OAE type. However, as discussed in section 1.6, research suggests that

DPOAEs and TEOAEs arise from different mechanisms in the cochlea, and therefore

each OAE type may provide unique information on the function of the cochlear

amplifier. The use of more than one type of OAE during an experiment would be

justified if the different measurement types provided different results, which can be

assessed by measuring the correlation between the OAE types. The two DPOAE

suppression measurements, the suppression of L1 = 45 dB DPOAEs and of L1 = 55 dB

DPOAEs, were well correlated, but did not correlate well with TEOAE suppression, as


50

shown in Table 3.3. Despite the good correlation between the DPOAEs, both

suppression measurements are reported in the results. The lack of a correlation between

DPOAE suppression and TEOAE suppression supports the use of both OAE types in

research investigating the effect of OAE suppression on auditory ability.

Table 3.3. Correlation coefficients with 95% confidence intervals for the relationships

between each OAE suppression measurement type.

L1 = 55 DPOAE L1 = 45 DPOAE

L1 = 45 DPOAE r = .67 (.19, .89)

TEOAE r = .08 (-.47, .59) r = -.22 (-.70, .41)

The preliminary study included a simplified selective attention task which measured the

difference in detection rate between a 2-kHz target and a single probe at 2.08 kHz. As

shown in Table 3.4, the three participants detected the target near to the 79% detection

rate estimated by the preceding threshold experiment, and two of the three participants

showed a detection rate of the probe frequency which was below 79%.


51

Table 3.4. The mean detection rates and SEM of the target and probe for each subject in

the preliminary study.

Target Probe

Subject 1 77.7 ± 5.2% 61.5 ± 2.3%

Subject 2 71.4 ± 5.3% 64.8 ± 4.5%

Subject 3 80.3 ± 3.2% 79.1 ± 3.5%


52

3.3.5 Primary experiment: Attentional filters and the suppression of OAEs

Attentional filters were measured in 15 subjects. Figure 3.4 shows the mean detection

rate of the target tone and the probe tones aggregated from the 15 subjects, and Table

3.5 shows the difference in detection rates between the target and the probes and

between the different probes. The detection rate of the 2.0-kHz target was significantly

higher than that of any probe. However, while the detection rates of the 1.8-, 1.92-, and

2.08-kHz probes were not significantly different from each other, they were all

significantly higher than the detection rate of the 2.2-kHz probe. Tested with a repeated-

measures 1-way ANOVA for frequency, F(4, 56) = 15.01, p < 0.0001, and the multiple

comparisons statistics are shown in Table 3.5. In addition, the detection rate of the 2-

kHz target tone was significantly lower than the estimated 79% threshold, with a mean

detection rate of 72% (± 4.3 SD)(t14 = 6.45, p < 0.0001).

Figure 3.4. Detection rates of the target and probe tones as a function of frequency for

each participant (grey) and for the average of all participants (black, n=15; error bars

show SEM).


53

Table 3.5. Statistics for the multiple comparisons between the 2.0-kHz target and all

probes. No correction for multiple comparisons was made.

Frequency Mean difference

95% CI of difference Significant?

Target vs. 1.8-khz probe 11.0 (16.7, 5.9) Yes

Target vs. 1.92-kHz probe 11.3 (16.7, 5.9) Yes

Target vs. 2.08-kHz probe 10.5 (5.2, 15.9) Yes

Target vs. 2.2-khz probe 17.4 (12.0, 22.8) Yes

1.8-khz probe vs. 1.92-khz probe 0.3 (-5.1, 5.6) No

1.8-kHz probe vs. 2.08-kHz probe -0.5 (-5.9, 4.8) No

1.8-kHz probe vs. 2.2-kHz probe 6.3 (1.0, 11.7) Yes

1.92-khz probe vs. 2.08-kHz probe -0.8 (-6.2, 4.6) No

1.92-khz probe vs. 2.2-kHz probe 6.1 (0.7, 11.4) Yes

2.08-kHz probe vs. 2.2-khz probe 6.9 (1.5, 12.2) Yes

The attentional filters shown in the earlier Figure 3.4 are the result of three sessions of

psychophysical measurements, which were taken before a separate session used to

measure OAE suppression. The three attentional filter measurement sessions will now

be considered as separate, complete measurements. Figure 3.5 shows the mean and

individual attentional filters produced for each session. The filters were stable across the

sessions, with each session demonstrating a clear increase in the detection rate of the

2.0-kHz target compared to the probes.


54

Figure 3.5. Detection rates of the target and probe tones as a function of frequency for

the three sessions used to measure the attentional filter. Filters are shown for each

participant (grey) and for the average of all participants (black, n=15; error bars show

SEM).

Figure 3.5 shows the consistent presence and shape of the attentional filter across three

sessions in two individual participants,. In Figure 3.6 below, the attentional filters of

two individual participants are shown across the three sessions. While the presence of

the attentional filter is consistent within each of these participants, there is considerable

variation present across the three measurement sessions.


55

Figure 3.6. Detection rates of the target and probe tones as a function of frequency

across three sessions for two individual participants.

3.3.6 Primary experiment: Detection rates measurement

The correlations that are reported below show the detection rate of the target and each

of the probes as a function of either the magnitude of TEOAE or DPOAE suppression.

Previous research has additionally used a measure of the depth of the attentional filter,

which is made by subtracting the detection rate of the probes from that of the target.

However, this measurement did not correlate significantly with any OAE suppression

measurement in the present work, and is shown only in the Appendix in Figures 8.1, 8.2

and 8.3.

3.3.7 Primary experiment: TEOAE suppression

As the TEOAEs were presented at 40 dB SL, the actual click amplitude varied across

participants, with a mean of 62 dB SPL ± 6.2. The relationships between the mean

detection rate of the target and the probes were aggregated from 14 participants as a

function of the magnitude of the suppression of TEOAEs is shown in Figure 3.7, with


56

the statistics for the correlations shown in Table 3.6. The TEOAE data includes only 14

of the 15 subjects, as one subject was removed due to TEOAE emissions that were

below the accepted noise floor. The only relationship that neared significance (p < 0.1,

with 95% CIs for the r of -.08 to .80) was for a positive correlation between the

detection rate of the 2.08-kHz probe and the magnitude of the TEOAE suppression.

Figure 3.7. The relationship between the suppression of TEOAEs and the detection rate

of the target and probes (N = 14).


57

Table 3.6. The correlation coefficients and associated statistics for the detection rate of

the target and probes as a function of the suppression of TEOAEs (N = 14). No

correction for multiple comparisons was made.

In the above correlations there is a consistent trend for the increasing detection rate of

both of the nearby (1.92- and 2.08-kHz) probes with increasing magnitude of TEOAE

suppression, as well as consistent decreases in the detection rate of both of the distant

(1.8- and 2.2-kHz) probes with increasing magnitude of TEOAE suppression. The

nearby probes and the distant probes were averaged in each individual, and these

“Nearby” and “Distant” probe groups were used to test for a more reliable estimate for

the relationship between TEOAE suppression and pooled probe detection rates, shown

in Table 3.7.

Table 3.7. The correlation coefficients and associated statistics for the relationships

between the detection rate of the target and probes when the probes nearby to the target

and the probes distant to the target were pooled together, as a function of the

suppression of TEOAEs (N = 14).

r 95% CI

Nearby probes .53 (.01, .83)

Distant probes -.32 (-.73, .26)

2.0-kHz target .28 (-.29, .70)

r 95% CI

1.8-kHz probe -.24 (-.69, .33)

1.92-kHz probe .44 (-.12, .78)

2.0-kHz target .28 (-.29, .70)

2.08-kHz probe .47 (-.08, .8)

2.2-kHz probe -.30 (-.72, .27)


58

As suggested from the data in Table 3.6, when the data for the nearby probes, both

above and below the 2-kHz target, were pooled, the correlation between their detection

rate and the magnitude of TEOAE suppression was strengthened. This suggests that

there is a common relationship between the nearby probes and the suppression of

TEOAEs. Although the correlation coefficient for the relationship between the distant

probes and the magnitude of TEOAE suppression increased, again suggesting a

common connection to TEOAEs, it did not become significant.

The OAE measurements were taken after the three sessions of attentional filter

measurements were complete, which leaves the third attentional filter measurement as

the closest in time to the measurements of TEOAE suppression. The three attentional

filter measurements will now be considered as three individual measurements, to test

whether the above correlations were affected by the different separations in time. Table

3.8 shows the statistics for these correlations, which show that no correlations were near

significance, although the patterns of increasing detection rates of the two nearby (1.92-

and 2.08-kHz) probes and decreasing detection rates of the two distant (1.8- and 2.2-

kHz) probes with increasing magnitude of TEOAE suppression was present (with the

only exception being the 2.2-kHz probe in session 3).


59


between the detection rate of the target and probes on the three sessions as a function of

the suppression TEOAEs (N = 14).

Session r 95% CI

1.8-kHz probe

1 -.19 (-.65, .38)

2 -.31 (-.72, .27)

3 -.01 (-.54, .52)

1.92-kHz probe

1 .36 (-.21, .75)

2 .09 (-.46, .59)

3 .28 (-.29, .71)

2.0-kHz target

1 .44 (-.12, .79)

2 .04 (-.50, .56)

3 .14 (-.42, .62)

2.08-kHz probe

1 .37 (-.20, .75)

2 .17 (-.39, .64)

3 .27 (-.30, .70)

2.2-khz probe

1 -.26 (-.70, .32)

2 -.37 (-.75, .20)

3 .09 (-.46, .59)


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3.3.8 Primary experiment: DPOAE suppression

The relationship between the detection rate of the target and the probes, aggregated

from 15 participants as a function of the suppression of the L1 = 55 dB DPOAEs, and

from 13 participants for the suppression of the L1 = 45 dB DPOAEs in Figure 3.8A-B,

with the statistics of the relationships shown in Table 3.9. The results for the

suppression of the L1 = 55 dB DPOAEs include the full 15 subjects, however the

suppression of the L1 = 45 dB DPOAEs include only 13 subjects, as 2 were removed

due to unacceptable signal to noise ratios. The only significant correlation found in

these results was for the 1.8-kHz probe, which showed an increased detection rate with

increasing magnitude of the suppression of L1 = 45 dB DPOAEs. However, there was a

consistent trend for increasing detection rate of the target and all probes, except for the

2.2-kHz probe, with increasing magnitudes of suppression of both the L1 = 45 and L1 =

55 dB DPOAEs, and this trend was near significance (p < 0.1) for the 1.92-kHz in both

DPOAE conditions.


61

Figure 3.8. A, the relationship between the suppression of the L1 = 45 dB DPOAEs and

the detection rate of the target and probes. B, the same relationship for the suppression

of L1 = 55 dB DPOAEs. Asterisk in the top right hand panel in section A indicates the

significant correlation found for the 1.8-khz probe for L1 = 45 dB DPOAEs (p < 0.05)

(N = 13 for L1 = 45 dB DPOAEs, n = 15 for L1 = 55 dB DPOAEs).


62


between the detection rate of the target and probes and the suppression of the L1 = 45

dB, and L1 = 55 dB DPOAEs (N = 13 for L1 = 45 dB DPOAEs, n = 15 for L1 = 55 dB

DPOAEs).

In the TEOAE results, the nearby and distant probes were pooled to test for a more

stable relationship, as they showed trends with the same direction. The nearby and

distant probes do not show the same trends with the suppression of DPOAEs, however a

similar comparison can be made with the significant, or near significant positive

correlations between the two low frequency probes with the magnitude of suppression

of the L1 = 45 and L1 = 55 dB DPOAEs. To test for more stable relationships for this

pooled group, the two low frequency probes were pooled, and the two high frequency

probes were pooled (although their correlations were in opposite directions, and were

not expected to strengthen), with the correlation statistics shown in Table 3.10.

L1 r 95% CI

1.8-kHz probe 45 .58 (.04, .86)

55 .19 (-.36, .64)

1.92-kHz probe 45 .49 (-.09, .82)

55 .46 (-.06, .79)

2.0-kHz target 45 .46 (-.13, .81)

55 .36 (-.19, .74)

2.08-kHz probe 45 .19 (-.41, .67)

55 .30 (-.25, .71)

2.2-kHz probe 45 -.35 (-.76, .25)

55 -.21 (-.65, .34)


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between the detection rate of the target and pooled low and high frequency probe

groups, and the suppression of the L1 = 45 dB, and L1 = 55 dB DPOAEs (N = 13 for L1

= 45 dB DPOAEs, n = 15 for L1 = 55 dB DPOAEs).

L1 r 95% CI

Low frequency probes 45 .65 (.15, .88)

55 .40 (-.14, .76)

2.0-kHz target 45 .46 (-.13, .81)

55 .36 (-.19, .74)

High frequency probes 45 -.13 (-.63, .45)

55 .05 (-.48, .55)

As suggested by Table 3.9, when the two low frequency probes are pooled together the

correlation between their detection rate and L1 = 45 dB DPOAE suppression is

strengthened, although only for the L1 = 45 dB DPOAEs. As shown in the results with

the suppression of TEOAEs, this suggests that there is a common relationship between

the two low frequency probes and the magnitude of suppression of the L1 = 45 dB

DPOAEs.

The measurements of DPOAE suppression will now be correlated with the results from

the three separate attentional filter measurements, still as an aggregate from the 15

participants. Table 3.11 shows the correlation statistics for these relationships. The

results indicate the presence of numerous, but inconsistent, relationships between

DPOAE suppression and the detection rate of the target and each of the probes. At least

one significant correlation was identified between the magnitude of suppression of

either the L1 = 45 dB or the L1 = 55 dB DPOAES and changes in the detection rate of

each of the tones, and on at least one of the three sessions. The most stable relationship

was for the 1.92-kHz probe, which increased in detection rate with increased


64

suppression of the L1 = 45 dB DPOAEs in session 2, as well as with increased

suppression of the L1 = 55 dB DPOAES in session 3. Session 3, which was closest in

time to the DPOAE measurement, produced the highest correlation coefficients, with 4

significant correlations for increasing detection rate of the 1.8-kHz probe with

increasing magnitude of the suppression of L1 = 45 dB DPOAEs, as well as increasing

detection rates of the 1.92-kHz probe, 2.0-kHz target, and 2.08-kHz probes with

increasing magnitude of suppression of the L1 = 55 dB DPOAEs.


65


between the detection rate of the target and probes on each session and the suppression

of the L1 = 45 dB, and L1 = 55 dB DPOAEs. The target and each of the probes show a

single significant correlation, except for the 1.92-kHz probe which shows two. Sessions

1 and 2 each have only a single significant correlation, for the 2.2-kHz probe and the

1.92-khz probe respectively, while session 3, which was the closest in time to the

DPOAE measurement, shows four significant correlations. Bold entries indicate

significant correlations (p < 0.05).

DPOAE L1 Session R 95% CI

1.8-kHz probe

45 1 -.26 (-.70, .34)

2 -.45 (-.78, .08)

3 .61 (.09, .87)

55 1 .27 (-.28, .69)

2 .53 (-.02, .84)

3 .39 (-.16, .75)

1.92-kHz probe

45 1 .08 (-.50, .60)

2 .66 (.17, .89)

3 .33 (-.27, .74)

55 1 -.10 (-.58, .44)

2 .40 (-.14, .76)

3 .71 (.31, .90)

2.0-kHz target

45 1 -.03 (-.57, .53)

2 .50 (-.07, .82)

3 .27 (-.33, .72)

55 1 -.29 (-.70, .26)

2 .27 (-.28, .69)

3 .65 (.20, .87)

2.08-kHz probe

45 1 -.03 (-.57, .53)

2 -.15 (-.65, .44)

3 .47 (-.11, .81)

55 1 .10 (-.44, .58)

2 -.26 (-.69, .29)

3 .63 (.18, .86)

2.2-kHz probe

45 1 -.59 (-.86, -.05)

2 -.06 (-.60, .51)

3 -.14 (-.64, .44)

55 1 -.16 (-.62, .38)

2 .10 (-.43, .59)

3 -.35 (-.73, .20)


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3.4 Discussion

Previous research demonstrated a reduction in the formation of the attentional filter with

the loss of the MOCS output to the cochlear amplifier (Scharf et al., 1994; Scharf et al.,

1997). Based on that result, the aim of this chapter was to test whether individuals with

stronger MOCS acoustic reflexes formed deeper attentional filters, which would be

supported by an increase in the detection rate of the target, and/or a decreased detection

rate of the probes as a function of increasing reflex strength. In this chapter the strength

of the reflex was estimated using the suppression of OAEs by contralateral broadband

noise, with increasing OAE suppression consistent with increasing MOCS strength

(Berlin et al., 1994). The expected relationship was not present in the results, which

does not support a role for the MOCS in forming the attentional filter.

Contrary to the prediction of the hypothesis, the present results showed consistent trends

for increasing detection rate of some probe tones with increasing magnitudes of OAE

suppression, although the pattern of these increases was different for the two OAE

types. For the suppression of DPOAEs, there was a positive correlation between the

detection rate of the two low frequency probe tones and the magnitudes of L1 = 45 dB

DPOAE suppression, as well as limited evidence for increasing detection rate of the

target tone. The increasing detection rate of the target tone was significant only in a

correlation between the magnitudes of DPOAE suppression and the tone‟s detection rate

on the third attentional filter measurement session. In contrast, the first attentional filter

measurement session held the only evidence for the suppression of the probe tones, with

increasing DPOAE suppression correlating with decreasing detection rate of the highest

frequency probe. Increasing magnitudes of suppression of the TEOAEs however,

showed increasing detection rates of the two probes nearby to the target frequency,

which was significant only when the nearby and distant probes were pooled. No other

correlations between the detection rates of individual probes and the magnitudes of


67

TEOAE suppression approached significance. These results indicate increasing

detection rates of some of the probes with increasing MOCS strength, and therefore a

general decrease in filter depth associated with stronger MOCS reflexes. Overall, these

patterns are not consistent with a major role for the MOCS in forming the attentional

filter.

A pertinent feature of the attentional filter data shown here is the high degree of

variance present across participants, but as shown in Figure 3.6 this variance is not

present within individual participants. This result supports the variations in filter depth

across these participants as real variation in the filter, rather than measurement

variations. Previous research including attentional filter measurements often included

small numbers of participants (e.g. four participants in Dai et al. (1991) and three

participants in Schlauch and Hafter (1991)), and the present result supports these

methods.

Although the results do not support a role for the MOCS in forming the attentional

filter, there are aspects of the findings that are consistent with the normal function of the

MOCS in humans. The frequency-tuning of the MOCS acoustic reflex has been

measured by testing the suppression of stimulus frequency OAEs, a type of frequency-

specific OAE (Lilaonitkul and Guinan, 2009b, Lilaonitkul and Guinan, 2009a), or

spontaneous OAEs (Zhao and Dhar, 2012), in response to various MOCS elicitors.

Broadband noise was shown to be the most effective MOCS elicitor, although the

magnitude of suppression of the cochlear amplifier was not uniform across the

frequencies tested. In response to a broadband elicitor, the maximum suppression of the

cochlear amplifier was found at 1 kHz, with a progressive decline in suppression with

increasing frequency, although 2 kHz was not tested (Lilaonitkul and Guinan, 2009a).

These studies suggest that the broadband noise used during the present attentional filter


68

measurement would suppress the cochlear amplifier primarily below the 2-kHz target

frequency. If the MOCS activation results in an antimasking effect that is more effective

with increasing suppression, then the tendency for increased detection rate of the low-

frequency probes with increasing L1 = 45 dB DPOAE suppression fits the frequency

tuning of the reflex and its suggested antimasking benefit, at least as activated by

broadband noise. The response of the MOCS to a continuous broadband noise has been

shown to be sustained with very little adaptation (Brown, 2001), although that study

measured the system‟s activation over a maximum of ten seconds, whereas the present

research measures the attentional filter over several minutes, and so a sustained MOCS

response for the duration of the attentional filter can only be assumed. It is unclear why

this effect is present only for the low-frequency probes. Lilaonitkul and Guinan (2012)

demonstrated that the tuning of MOCS suppression can cause a significant suppression

at a particular frequency, with zero suppression within half an octave above that

frequency, so it is possible that this is an effect of the tuning of MOCS suppression.

Surprisingly, while the increase in detection rate of the low-frequency probes fits the

frequency-tuning of the MOCS acoustic reflex in response to the broadband noise, this

enhancement does not fit the reflex‟s response to the 2-kHz cue tone that was used

during the experiments. The maximum effect of a 2-kHz MOCS elicitor was found to be

located up to half an octave above the elicitor frequency (Lilaonitkul and Guinan,

2009b; Lilaonitkul and Guinan, 2012). This tuning would be expected to enhance the

detection rates of probes at a higher frequency than the target, which was not seen in the

present data. In summary, the increased detection rates of the low-frequency probes

with increasing L1 = 45 dB DPOAE suppression is consistent with an antimasking

mechanism that is mediated by the MOCS acoustic reflex‟s activation by broadband

noise. Thus, this result suggests that there is a MOCS-mediated antimasking benefit to

the detectability of transient pure-tones that can be elicited by a broadband noise (Smith,


69

1979; Winslow and Sachs, 1987; Mulders et al., 2008). However, this interpretation

must be treated with some caution, as it is important to note that the relationship

between DPOAE suppression, as the estimation of MOCS strength, and the increasing

detection rate of the low-frequency probes was a weak effect that was only present

under certain conditions.

The results obtained with the contralateral suppression of OAEs in the present research

should not be considered indicative of the entirety of the MOCS effects on hearing, and

particularly not for all of the system‟s effects during the task used to measure the

attentional filter. This is due to the use of a single, relatively simple measurement of

OAE suppression as an index of the strength of the MOCS acoustic reflex. This

measurement includes only a small subset of MOCS function, because the measurement

used a contralateral noise suppression of OAEs which was taken on a separate session

to the measurements of the attentional filter. Thus, the index of MOCS function will

likely contain only the action of the contralateral MOCS acoustic reflex, and not the

actions of the ipsilateral MOCS acoustic reflex, or any top-down MOCS activation. The

ipsilateral reflex is thought to be at least as strong as the contralateral reflex in humans,

at least in response to broadband noise (Lilaonitkul and John, 2002), and will be

activate during the binaural attentional filter task. More importantly to the measurement

of the attentional filter, because the index of MOCS function was performed separately

from the attentional task, the index will probably not include the effects of top-down

control of the MOCS. Top-down control of the MOCS has been shown to suppress the

cochlear amplifier in humans, which was demonstrated by electrical stimulation of the

auditory cortex during presurgical functional brain mapping prior to a surgery for

refractory epilepsy (Perrot et al., 2006). In that study, TEOAEs were recorded during

the functional mapping, and were shown to be suppressed by the electrical stimulation

of the auditory cortex, which provides evidence that a cortico-olivocochlear pathway is


70

present and is able to suppress the cochlear amplifier in humans. More specifically

relevant to the current work is the finding that the cochlear amplifier is suppressed at

frequencies under focused auditory attention (Maison et al., 2001). This research

demonstrated an increase in the suppression of OAEs, presumably by MOCS activation,

at frequencies that the subjects had their attention focused in anticipation of a to-be-

detected tone. The suppression of OAEs at frequencies under focused auditory attention

suggests that the top-down effects will suppress the cochlear amplifier during the

attentional filter measurement, which similarly requires the subjects to focus their

auditory attention on the target frequency. The separation in time between the OAE

measurement and the attentional filter measurement in the present experiments means

that this top-down effect may not be included in our measurement of MOCS strength.

Therefore, the present results may not include the activation of the MOCS component

critical to the systems potential role in forming the attentional filter.

How can we reconcile the apparent decrease in filter depth with an increase in the index

of MOCS strength found in the present chapter with the flattening of the attentional

filter seen in Scharf et al.‟s vestibular neurectomy research? It is important to reiterate

that the vestibular neurectomy, which was thought to completely remove the MOCS

efferent output to the cochlea, did not completely eliminate the attentional filter. Only

three participants out of the 8 that were tested for the filter before and after the surgery

had less than 10% difference in detection rate between the target and probes after the

surgery. The remaining 5 participants either showed no filter to begin with (n=2), an

asymmetrical loss of the filter (n=2), or only a small reduction in filter depth (n=1). It is

more accurate to say that the apparently complete loss of MOCS efferent output to the

cochlea only disrupted the formation of the filter, rather than stopping its formation, the

remaining filter formation may be due to other mechanisms, such as central

mechanisms, that may be involved in the filter‟s formation.


71

The 2-kHz target tone was presented at an amplitude that was estimated to produce a

79% detection rate in each participant, however the mean detection rate during the

attentional filter condition was 72%. This reduction in detection rate from the estimated

threshold may have been due to the changes in listening conditions from the threshold

estimation, which requires the participants to attend to a single frequency, compared

with the attentional filter measurement, which requires attention across a frequency

range. It may be that the spread of attention from a single frequency to the frequency

range has a negative effect on the participants‟ ability to detect the target tone, relative

to when the target tone is presented as the only to-be-detected signal.

While the OAE results in this chapter may not be useful as a measure of MOCS

involvement in forming the attentional filter, they provide a novel comparison of

TEOAE and DPOAE suppression within individuals, which is not currently present in

the literature. Previous research has identified the stability of TEOAE suppression

within individuals, and the present results support that stability (Mishra and Lutman,

2013). Similarly, the emission magnitudes and suppression magnitudes of the DPOAEs

were comparable to those in previous research (Abdala et al., 2009). However, the

magnitudes of DPOAE suppression were considerably more variable when compared to

those of the TEOAEs, with a coefficient of variation which was 30% higher in the

magnitudes of DPOAE suppression. In addition, the relationships between the

magnitude of OAE suppression by contralateral broadband noise and the detection rates

of the target and probes were different for the two OAE types. This may be related to

the different frequency specificity of the two OAE types. DPOAEs are thought to probe

a frequency-restricted portion of the cochlear amplifier, compared with TEOAEs that

typically use a broadband click stimulus, and so probe a wide band of the amplifier. An

important question is whether the variability shown in the magnitudes of OAE

suppression are caused by physiological changes measured with the suppression of


72

DPOAEs, but not TEOAEs, or if it is a source of error, but with only 3 participants over

4 sessions, the present work is unable to make a distinction. The result does demonstrate

the importance of selecting an appropriate OAE type during experiments on MOCS

function, and that some features of these emissions are still unclear.

The results of this chapter do not support a role for the MOCS in forming the attentional

filter. There is some evidence that the MOCS can enhance the detectability of near-

threshold probes at specific frequencies, and perhaps suppress others, but this pattern is

in line with a general anti-masking benefit and not specifically in forming the

attentional filter. It is unclear whether this result is due to an actual absence of MOCS

effects on the attentional filter, or if it results from inherent limitations in the

experimental design.


73

Chapter 4. Formation of the attentional filter in hearing-impaired

participants

Formation of the attentional filter in hearing impaired participants

75

4.1 Introduction

In the previous chapter the effects of MOCS action on the formation of the attentional

filter was investigated in a group of normal hearing individuals. However, limitations in

the methods used in the previous chapter, both by the experimental design and inherent

in the estimation of MOCS strength, may have prevented an accurate measurement of

the suggested MOCS role in forming the attentional filter. Previous research has

investigated the effect of the loss of MOCS output on the depth of the attentional filter,

using a surgical approach that severed the MOCS efferent connection to the cochlea

(Scharf et al., 1994; Scharf et al., 1997). In these vestibular neurectomy patients, the

difference in detection rate between the expected and the unexpected tones decreased,

and was eliminated in some cases, which demonstrates a decreased depth of the

attentional filter. This decreased filter depth associated with a loss of MOCS action on

the cochlea suggests that the MOCS is at least partially responsible for the generation of

the attentional filter. If the MOCS action on the cochlea is required for part of the

generation of the attentional filter, then other conditions in which MOCS action on the

cochlea is impaired should also decrease the depth of the filter. In this chapter, SNHL is

used as an alternative method of testing whether the attentional filter is affected by

impairment to the MOCS action on the cochlea.

Sensorineural hearing loss is typically, but not exclusively, caused by loss or damage to

the OHCs in the cochlea. Sensorineural hearing loss with OHC impairment can be

confirmed by reduced OAE amplitude, as the other causes of SNHL, which includes the

loss or damage to IHCs or auditory neuropathy, do not reduce OAE amplitude (Hood

and Poole, 1971; Kim et al., 1996; Trautwein et al., 1996; Abdala, 2000). The loss of

OHCs is a loss of the MOCS‟ efferent targets in the cochlea (Warr, 1978; Warr and

Guinan Jr, 1979). Therefore, participants with pure SNHL and reduced OAE amplitude

will have some degree of impairment to the MOCS efferent targets.


76

An earlier study by Moore et al. (1996) measured attentional filters in two participants

with SNHL and in two participants with normal hearing (Moore et al., 1996). The

participants with SNHL had a smaller difference between the detection rate of the

expected target and unexpected probes when compared with two normal-hearing

participants, which shows shallower attentional filters associated with SNHL. In the

present work, the attentional filter was measured in fourteen participants with varying

levels of hearing impairment, with the hypothesis that the attentional filter would be

decreased in depth in the SNHL group as compared with the normal-hearing

participants from chapter 3. In addition, using fourteen participants with varying levels

of SNHL enabled a correlation between any decreases in filter depth and the level of

SNHL, as an estimate of the impairment to the MOCS efferent targets.

In addition to the SNHL group, the attentional filter was measured in two participants

with long-term conductive hearing loss, and therefore a long-standing hearing loss

without direct impairment of OHC function. The participants with conductive hearing

loss were included to give an indication of how the attentional filter might be affected

by long-term hearing losses without direct impairment to the MOCS action on the

cochlea.


77

4.2 Methods

4.2.1 Participants

The SNHL group consisted of 9 male and 5 female participants with a median age of 45

years, ranging from 35 to 81. The two participants with conductive hearing loss were

female and of 35 and 45 years of age. The SNHL group and the two conductive hearing

loss participants will be compared with the normal-hearing group from chapter 3, and

although there are significant variations in age in these groups, previous research has

shown that age has no effect on the formation of the attentional filter, when hearing

level (HL) was accounted for (Ison et al., 2002). SNHL participants were characterized

based on the results of previous testing by professional audiologists at the Ear Science

Institute of Australia, and the stability of their audiogram was checked using a Grason

Stadler GSI 61 Clinical Audiometer on the first experimental session. SNHL was

classified if participants had > 20 dB HL with bone conduction and less than a 10 dB

difference between air and bone conduction thresholds at 2 kHz. In order to confirm

significant disruption to outer hair cell function, SNHL participants were excluded if

they showed greater than 5 dB SPL DPOAE with L1 = L2 = 65 dB SPL, f1 = 2 kHz, and

f1/f2 = 1.2, as normative data exists that these conditions indicate an impairment to the

outer hair cell amplifier (Kim et al., 1996). Conductive hearing loss was classified if

participants had less than 20 dB HL from 500 Hz to 4 kHz when tested with bone

conduction, but 20 dB HL or more at 2-kHz when tested with air conduction.

Participants were excluded if they reported a “considerable” or “irritating” tinnitus,

based on questions in the Tinnitus Severity Index (Meikle et al., 1995), or if they

matched a lesser tinnitus to a pure tone of between 1 to 4 kHz.


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4.2.2 Measuring the attentional filter

As described in chapter 3, the background noise that was present during the threshold

measurements and the attentional filter measurement task was presented at 60 dB (A)

SPL in the normal-hearing group. In the hearing-impaired groups, the level of the

background noise was adjusted for the amount of hearing loss in each individual hearing

impaired participant using the Loud16K hearing aid fitting algorithm (Moore and

Glasberg, 2004). This algorithm uses bone and air conduction thresholds and applies a

gain function to the noise in octave bands between 0.25 kHz to 8 kHz. The algorithm

was used to equalize the loudness perception of the broadband white noise in each

hearing impaired individual to the participants with normal hearing. The Loud16k

algorithm was not applied to the to-be-detected target and probe tones or the cue tone,

as the algorithm does not apply to pure tones.

The hearing-impaired participants attended 5 sessions, the first of which contained

initial hearing tests, and the measurement of DPOAE responses. The second session

included practice runs of the threshold and attentional filter procedures. The last 3

sessions were used to measure the attentional filter. Each of these sessions began with

the threshold measurements.

The hearing-impaired groups had 79% detection thresholds measured at 1.8, 2 and 2.2

kHz within the background noise adjusted according to the Loud16k algorithm, and the

thresholds for the 1.92- and 2.08-kHz probes were interpolated from these thresholds.

Each run contained 192 trials which were constrained so that the target was presented

on 75% of the trials, with the remaining 25% spread equally over the 1.8-, 1.92-, 2.08-,

and 2.2-kHz probe tones. Each session included three runs of the attentional filter

procedure. In total the target was presented 1296 times, and each probe 108 times for

each participant.


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4.3 Results

4.3.1 Normal-hearing & SNHL groups: Audiometric results

Figure 4.1 shows the audiograms for the normal-hearing group (top panel) and the

SNHL group (bottom panel). For both groups, the ear with the lower HL at 2 kHz is

shown, with the other ears shown in Appendix 8.4. For the SNHL group, the ear with

the higher threshold at 2 kHz was within 10 dB of the thresholds shown in Figure 4.1 at

this frequency. The normal-hearing group had < 20 dB HL across the tested frequency

range, and a range of HLs at the 2 kHz target frequency from -5 to 10 dB HL (mode = 0

dB HL). In contrast, the SNHL group had ≥ 25 dB HL at the 2 kHz target frequency,

ranging from 25 to 60 dB HL (mode = 40 dB HL).


80


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Figure 4.1. Audiograms for the normal-hearing group (left page) and the SNHL group

(right page). SNHL group includes air conduction thresholds (solid lines) and bone

conduction thresholds (dashed lines). Audiograms for the opposite ears are shown in

Appendix 8.4.


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Otoacoustic emissions were measured to assess OHC function. In the normal-hearing

group, DPOAEs varied in amplitude from 0.8 to 17.6 dB SPL (median = 11.7 dB SPL),

which was consistent with the range of normally hearing participants in previous studies

(from -5 to 16 dB SPL in (Kim et al., 1996)). The SNHL group had no detectable OAEs

with our equipment, consistent with outer hair cell amplifier dysfunction (Kim et al.,

1996).

4.3.2 Normal hearing & SNHL groups: Attentional filters

Figure 4.2 shows the average attentional filters of the normal-hearing group (left panel)

and the SNHL group (right panel). In contrast to the attentional filters in the normal-

hearing group, the SNHL group had elevated detection rates overall, and did not show a

distinct peak at the target frequency. The loss of the peak at the target frequency was

due to an increase in the detection rate of the low-frequency probe tones relative to that

of the target. In contrast, while the detection rate of the high-frequency probe tones was

higher in the SNHL group than in the normal hearing group, the detection rate of the

high-frequency probes relative to that of the target tone was similar in the two groups.

The target tone was presented at an amplitude that resulted in a 79% detection rate for

each individual participant, but as described in chapter 3, the normal-hearing group had

a lower than expected mean target detection rate of 72% (± 4.3 SD)(t14 = 6.45, p <

0.0001). In contrast, the SNHL group, with a mean detection rate of the 2-kHz target

tone at 82% (± 8.4 SD), was not significantly different to the 79% threshold (t13 = 1.37,

p = 0.20).


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Figure 4.2. Mean and individual detection rates for the target and probes as a function of

frequency for the normal-hearing group (left panel) and the SNHL group (right panel).

Black lines for mean ± SEM, and grey lines for individual data.

Where Figure 4.2 showed detection rates pooled from each group regardless of HL,

Figure 4.3 shows the difference in detection rate of each probe compared to that of the

2-kHz target tone, plotted as a function of HL at 2 kHz for both the normal-hearing and

SNHL groups. When the 4 panels of Figure 4.3 are taken as a whole, the figure shows

that the attentional filter as a whole was effectively flat at 60 dB HL. However, the

high-frequency and the low-frequency sides of the filter were affected at different HLs.

In the SNHL group, the high-frequency side of the attentional filter showed a normal

depth with mild SNHL, and then progressively decreased in depth with increasing HL.

The depth of the high-frequency side of the filter was at zero by 60 dB HL. While the

high-frequency side of the filter decreased in depth with increasing HL, there was

however no apparent difference between the depth of the high-frequency side of the


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filter in the SNHL group (2.08 kHz depth = 10.4% and 2.2 kHz depth = 16.4%) with the

normal hearing group (2.08 kHz depth = 10.6% and 2.2 kHz depth = 17.4%). This,

apparently contradictory result, is achieved by the wide range of filter depth results

present in the NH group, which is similar to the range present in the SNHL group, but

not arranged with a relationship to HL.

The low-frequency side of the attentional filter however, was around zero in depth at the

lowest level of SNHL, and the trend line remained slightly below zero (i.e. the probes

were detected better than the target) across the full range of HLs.

In the normal hearing group, the depth of the low-frequency side of the attentional filter

decreased with HL. The depth of the lower, 1.8-kHz probe decreased to be zero within

the tested range of HLs, whereas the depth of the 1.92-kHz probe would be extrapolated

to reach zero before 20 dB HL, so that the filter depth was zero by 15-20 dB HL to be

continuous with the SNHL group.

Table 4.1 shows the statistics for the correlations in Figure 4.3. The correlation between

increasing HL and decreasing filter depth was significant for both high-frequency

probes in the SNHL group and for only the 1.8-kHz prone in the normal hearing group.


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Figure 4.3. Relative change from the detection rate of the target to each probe as a

function of hearing loss (dB HL) for the normal-hearing (closed circles) and SNHL

groups (open circles).

Table 4.1. The Spearman‟s rank-order correlation statistics between the relative change

between the detection rate of the target and each probe as a function of dB HL for the

normal-hearing and SNHL groups.

Group r 95% CI

1.8-kHz probe NH -.73 -.91 to -.33

SNHL -.06 -.60 to .52

1.92-kHz probe NH -.30 -.71 to .26

SNHL .02 -.55 to .57

2.08-kHz probe NH -.40 -.76 to .16

SNHL -.60 -.87 to -.05

2.2-khz probe NH -.23 -.67 to .33

SNHL -.75 -.92 to -.32


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Figure 4.4 shows a schematic diagram for the attentional filters for normal hearing, mild

SNHL and for moderately-severe SNHL, which were constructed using the trend lines

shown in Figure 4.3. The diagram shows the typical formation of the attentional filter in

the normal hearing group, the loss of the low-frequency side in the mild SNHL group,

and the abnormal filter in the moderately-severe SNHL group.

Figure 4.4. Schematics for the attentional filters with normal hearing (solid black line),

mild SNHL (dashed line) and moderately-severe SNHL (solid grey line).

Chapter 3 included the same 15 normal hearing individuals used in the present chapter,

but presented the depth of the attentional filter as a function of OAE suppression rather

than HL. Both OAE suppression and HL correlated with reduced depth of the low-

frequency side of the attentional filter, and, as shown in Figure 4.5, there is some

evidence for this link. There was a near-significant positive correlation between HL and

the magnitude of DPOAE suppression in the 15 normal hearing individuals, although no

relationship was found for HL and the magnitude of TEOAE suppression. The


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suppression of L1 = 55 dB DPOAEs showed no apparent relationship with HL, and is

not shown here.

Figure 4.5. OAE suppression, in L1 = 45 dB DPOAEs (closed circles) and TEOAEs

(open circles), as a function of hearing level for the 16 normal hearing individuals.

4.3.3 Conductive hearing loss participants: Audiometric results

Extensive attempts to recruit suitable conductive hearing loss participants were made,

however extremely low response rates and the presence of SNHL limited the testing to

only 2 participants. Individual audiograms for the conductive hearing loss participants

are shown in Figure 4.6. An important aspect of the conductive hearing loss participants

is that both participants showed 15 dB HL for their bone conduction thresholds at 2

kHz. This bone conduction threshold is too low to be clinically relevant; however, it is a

higher level of hearing loss than the maximum of 10 dB HL present in the normal-

hearing group.


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Figure 4.6. Audiograms for the two conductive hearing loss participants (CHL). The

audiograms include both air conduction thresholds (solid lines) and bone conduction

thresholds (dashed lines).


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4.3.4 Conductive hearing loss participants: Attentional filters

Figure 4.7 shows the attentional filter for the two participants with pure conductive

hearing loss. Neither of these participants demonstrated a clear attentional filter.

Figure 4.7. Mean ± SEM detection rates for the target and probes as a function of

frequency for the 2 participants with conductive hearing loss (CHL).


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4.4 Discussion

In the present chapter SNHL was associated with decreased depth of the attentional

filter. When considered as a whole, the SNHL group showed a loss of the attentional

filter on only the low-frequency side, although this measurement includes a range of

SNHL from mild to moderately-severe and obscures the relationships between the depth

of the filter and the severity of the hearing loss. When the level of hearing loss was

taken into account, the low-frequency side of the attentional filter was found to be

highly vulnerable to hearing loss, with this side of the filter reducing in depth to be

approximately equal to the target‟s detection rate before a mild SNHL was reached. The

high-frequency side of the filter was not immune to hearing loss however, as the depth

of this side of the filter decreased progressively with increasing hearing loss, until it was

absent by about 60 dB HL. This demonstrates a complete loss of the formation of the

attentional filter by moderate to moderately-severe SNHL, which is a result that is

supported by previous research that demonstrated a complete, symmetrical loss of the

formation of the attentional filter in two individuals with moderately severe (55 & 60

dB HL) SNHL (Moore et al., 1996). The present work also included a range of hearing

levels in the normal hearing group, from -5 to 10 dB HL. Over this small range of

subclinical hearing levels, there was a progressive decrease in the depth of the low-

frequency side of the attentional filter, and although this was only significant for the

lower, 1.8-kHz probe, there was a similar trend for the 1.92-kHz probe that suggests a

loss of this side of the attentional filter at a subclinical hearing level. The present work

is the first to show a deficit in the formation of the attentional filter in individuals with

normal hearing, the progressive loss of the filter with increasing hearing impairment,

and the asymmetric loss of the filter about the target frequency at different hearing

levels. The loss of the attentional filter in individuals presumed to have reduced MOCS

action on the cochlea is consistent with a role for the MOCS in the generation of the


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attentional filter; although the asymmetric loss on the low- and high-frequency sides of

the filter at different hearing levels suggests a more complex relationship than initially

proposed.

Whether the decreased depth of the attentional filter with SNHL supports a role for the

MOCS in the generation of the filter relies on the assumption that increasing SNHL

serves as a useful measurement of impairment to the MOCS efferent targets, the OHCs.

Animal research on the physiology underlying different levels of hearing loss after

noise trauma show a primarily OHC-based loss with a mild SNHL, and that OHC

function decreased progressively with increasing hearing loss up to 60 dB HL (Stebbins

et al., 1979; Hamernik et al., 1989). This 50 to 60 dB SNHL is physiologically

significant, as it represents the maximum amplification of the OHC amplifier, and is

therefore the level of hearing loss associated with a complete loss of function of the

cochlear amplifier (Patuzzi, 1987; Patuzzi et al., 1989a). Decreased OHC function can

be confirmed with a reduction of OAE amplitude, as the other causes of SNHL,

including the impairment to IHCs or auditory neuropathy, do not reduce OAE amplitude

(Kim et al., 1996; Trautwein et al., 1996; Abdala, 2000). It is important to note,

however, that the reduction in OAE amplitude cannot be used to grade the loss of OHC

function. Otoacoustic emissions become undetectable with a relatively small loss of

function of OHCs, hence the loss of detectable OAEs at the lowest levels of SNHL

when the total loss of OHC function is only expected at 55-60 dB HL (Attias et al.,

1995; Kim et al., 1996). Therefore, in the present work the high-frequency side of the

attentional filter decreased in depth progressively with hearing loss in a manner that was

consistent with decreasing OHC function, and the filter was absent by the level of

hearing loss associated with a total loss of OHC function. Thus the progressive decrease

in the depth of the filter was consistent with progressive impairment to the MOCS

action on the cochlea, which supports a substantial role for the MOCS in forming the


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attentional filter. However, it is important to note that the present research can only

confirm a degree of impairment to the OHCs by the loss of detectable OAEs, and any

further OHC impairment must be inferred from the increasing HL.

It is unlikely that the loss of the high-frequency side of the attentional filter with

moderate SNHL was due to other effects of SNHL, which includes an increase in

loudness growth and the broadening of tuning curves. In the present work the effect of

increased loudness growth on the background noise was addressed using the Loud16k

algorithm, which takes the increased recruitment into account when equalizing the

loudness of the background noise in each hearing impaired individual to that of the

normal hearing group (Hellman, 1999; Moore and Glasberg, 2004). The increase in

loudness growth was not relevant to the to-be-detected tones, as their amplitudes were

set adaptively to a threshold of detection, although the Loud16k algorithm cannot be

used for pure tones, and so it could not compensate for the loudness growth for the cue

tone. The cue tone was presented at 12 dB above the threshold of the target tone, which

was the same increment for the SNHL group as used in the individuals with normal

hearing. The increased loudness growth which was likely to be present in the SNHL

group may have rendered the cue tone louder for some SNHL participants compared to

the normal-hearing participants, as the louder cue tone may have provided a more

effective cue. This louder cue tone may explain the increased detection rates of the

target and probes present in some of the SNHL participants, although this is based on

the assumption that a louder cue tone would result in an increase in detection rate above

the to-be-detected tone‟s threshold. It is important to note however, that normal

attentional filters are formed with a target detection thresholds of up to 90% (Greenberg

and Larkin, 1968; Dai et al., 1991). Therefore, the SNHL participants who had generally

increased detection rates would still be expected to form the attentional filter, if the

filter was present. A second effect of SNHL is reduced peripheral bandwidth due to a


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broadening of tuning curves (Dallos and Harris, 1978). The broadening of tuning curves

has the potential to eliminate the discriminability between the target tone and the probes

tones in the attentional filter measurement, which might eliminate the formation of the

filter. Previous research has shown that frequency difference limens at 2 kHz can be as

high as 60 Hz in individuals with a typical SNHL of up to 60 dB SNHL, although the

mean for a 60 dB SNHL was 10 Hz (Simon and Yund, 1993). However, in the worst

case scenario for broadening of tuning curves, a severe SNHL with a steeply sloping

hearing loss, the difference-limens may be as large as 140 Hz at 2 kHz with a 60 dB

SNHL (McDermott et al., 1998). This suggests that some individuals with SNHL may

be unable to discriminate between the 2-kHz target and the nearby probes, at 1.92 and

2.08 kHz. This could eliminate the formation of the attentional filter, at least between

the target and the nearby probes. However, even in this worst-case scenario, the

participants would be able to discriminate between the target and the distant probes, at

1.8 and 2.2 kHz they were 200 Hz from the target frequency. Thus, the SNHL

participants would be expected to form an attentional filter, if the filter was present,

although the filter may have only been present between the target and the distant probes.

The present results demonstrate a consistent flattening of the attentional filter across the

entire frequency range. Therefore, the broadening of tuning curves is unlikely to be

responsible for the loss of the attentional filter in the SNHL group, although without

directly measuring auditory filters in these participants, it cannot be ruled out and

remains a limitation of the present work.

Sensorineural hearing loss is not caused exclusively by OHC loss, and the other causes

of SNHL, IHC loss and auditory neuropathy, are important considerations when

assessing the effects of SNHL on the formation of the attentional filter. In animal

models on the effects of noise-induced SNHL loss, the loss of IHCs was restricted to

hearing losses above 30 dB HL, and did not become pronounced until greater than 60


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dB HL (Stebbins et al., 1979; Hamernik et al., 1989), which suggests a minimal

involvement in the present work. However, the loss or damage of IHCs can also result

from short but high amplitude noise exposure (Engström, 1984) or ototoxic drug

exposure (Johnsson et al., 1981), and IHC losses of up to 75% of the total IHC

population do not affect auditory thresholds (Schuknecht and Woellner, 1955).

Therefore, some of the participants in the present work may have had reduced IHC

function, and the pure-tone thresholds that were used as a measurement of hearing

impairment will not detect this impairment. Similarly, recent research has suggested that

the “cochlear neuropathy” associated with hidden hearing losses is selective for the

afferent subtype that forms the afferent input to the MOCS, and may be present to a

significant extent in individuals with subclinical auditory thresholds (Liberman, 1988;

Kujawa and Liberman, 2009; Furman et al., 2013). The extent of any impairment to the

input to the MOCS will not be reflected in the auditory thresholds, but may be present

in individuals with subclinical hearing losses, but previous exposures to loud sound

(Kujawa and Liberman, 2009). These forms of hearing loss will reduce the input to the

auditory system, and their effects will not be present in the tested audiograms, and so

cannot be measured in the present work. The potential decreases in input to the auditory

system input due to IHC loss or auditory neuropathy may render the assumption that the

level of hearing loss can be used as an estimation for the loss of the MOCS efferent

targets imperfect. For this reason, IHC loss and auditory neuropathy are considered

confounding factors in the present work, which may account for some of the variability

present in the depth of the high-frequency side of the attentional filter at higher levels of

SNHL.

In the present chapter a reduction in filter depth was shown with increasing HL in the

normal hearing individuals, and in this chapter increasing HL is argued to indicate some

form of impairment to the MOCS action on the cochlea. However, in chapter 3 a


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relationship was shown for the same participants that demonstrated reducing filter depth

with increasing DPOAE suppression, which was used as an estimation of increasing

strength of the MOCS acoustic reflex. In the present chapter there was some evidence

that HL and the magnitude of DPOAE suppression were linked, as shown in Figure 4.5.

How would subclinical elevations in HL affect this estimation of MOCS activation? In

normal hearing individuals, this HL is not typically associated with appreciable

impairment to the MOCS efferent targets (Hamernik et al., 1989), and any appreciable

impairment to these efferent targets would have resulted in a reduction of OAE

amplitude, which was not detected in this group. As discussed in the previous

paragraph, recent research has identified potentially relevant hearing impairments at

subclinical hearing levels. These so-called „hidden‟ hearing losses include the

neuropathy of auditory afferents (Kujawa and Liberman, 2009; Schaette and McAlpine,

2011), which are selective for the fibres that form the afferent input to the MOCS

(Furman et al., 2013). It is known that individuals with a diagnosed auditory neuropathy

show an absence of suppression of DPOAEs (Abdala, 2000), however it is unclear how

low-level auditory neuropathies might affect DPOAE suppression. Thus, while the

present work is unable to identify the cause of the elevated thresholds in the normal

hearing individuals, elevations in auditory thresholds have been suggested to result in a

plastic response to the decreased input which leads to an increase in central auditory

system sensitivity, and this has been linked to an increase in MOCS excitability.

Previous research identified an increase in auditory sensitivity, thought to be due to

loudness recruitment, in individuals with normal audiograms, but evidence of hidden

hearing losses (Schaette and McAlpine, 2011; Hébert et al., 2013). In addition,

individuals with increased auditory sensitivity, measured as a decreased sound-level

tolerance, have been shown to have increased suppression of DPOAEs (Knudson et al.,

2014), which was proposed to be caused by additional top-down drive of the MOCS


96

from hyperactive central auditory structures. Therefore, the small elevations in HL seen

in the normal hearing group may be associated with a hyperactive, top-down activation

of the MOCS, which may have contributed to the increases in DPOAE suppression with

increasing HL. However, while this increase in MOCS activation may explain the

positive relationship between HL and DPOAE suppression, it is an unsatisfying

explanation for the loss of the low-frequency side of the attentional filter with

subclinical hearing losses. This is because the low-frequency side of the attentional

filter remained absent through-out the range of SNHL, which is highly likely to include

a reduction in MOCS action due to the loss of the MOCS efferent targets, at least. It

seems more plausible that the loss of the low-frequency side of the attentional filter was

due to the suggested auditory neuropathy, as the neuropathy may reduce the afferent

input to the MOCS (Furman et al., 2013). An auditory neuropathy reducing afferent

input to the MOCS explains the impairment to the filter in individuals with subclinical

levels of hearing loss, as well as mild to moderate SNHL. However, there was no

sensitive measurement of central auditory system activity, or of auditory neuropathy in

the present work, and so the potential effects of hidden hearing loss remain speculative

in the present work. In addition, it is unclear why the reduction in MOCS afferent drive

associated with hidden hearing losses would cause a frequency-specific loss of only the

low-frequency side of the attentional filter.

In chapter 3 it was discussed that the detection rate of the target tone was lower than the

estimated 79% threshold in the group of normal-hearing participants. This was

suggested to be due to the changes in procedure from the threshold estimation, which

required attention at a single frequency, compared with the attentional filter

measurement, which requires attention over a frequency range. In contrast to the

reduced detection rate of the target tone in the normal hearing individuals, the SNHL

group showed a mean detection rate of the target at 82%, which is very close to the 79%


97

threshold. It is important to remember that this does not represent an improved detection

ability in the SNHL participants, as the target tone was presented at a threshold that

estimated in each participant. Instead, the on-threshold detection rate of the target in the

SNHL group may represent the absence of the improvement to detection rate during the

threshold measurement that the normal hearing participants received. Therefore, the

thresholds for the SNHL group represent a more accurate threshold estimation, whereas

in the normal hearing group the thresholds are suggested to include an improvement to

the detection rate. The nature of this improvement cannot be addressed with the data

present in the current work.

The decrease in the depth of the attentional filter with SNHL is in line with previous

research that demonstrated a flattening of the attentional filter in two individuals with

moderately-severe SNHL (Moore et al., 1996), although the progressive loss of the filter

with increasing SNHL, and the initial loss of the low-frequency side of the filter at a

subclinical hearing level are novel findings. The results are not completely in agreement

with those from Scharf et al.‟s vestibular neurectomy studies, in which the participants

were reported to have completely lost, or at least greatly reduced, the MOCS efferent

connection with the cochlea, but as shown in the General Introduction with Figure 1.5,

some of Scharf‟s subjects retained a partial attentional filter (Scharf et al., 1997). In

addition, Scharf et al.‟s results do not show the frequency-specific loss of the attentional

filter found in the present work, with both sides of the filter remaining roughly equal in

depth after a vestibular neurectomy. However, only 2 of the 12 vestibular neurectomy

participants who were tested for the attentional filter used the same 2-kHz target

frequency used in the present work, and neither formed a typical attentional filter in

their healthy, contralateral ear. Comparing the attentional filters that were formed at

other frequencies may be inappropriate, as the MOCS has different tuning and effects at

different frequencies (Lilaonitkul and Guinan, 2009a; Lilaonitkul and Guinan, 2012).


98

There are two potential explanations for the presence of a residual attentional filter after

a vestibular neurectomy, but a completely flat filter with moderate SNHL. The first is

the possibility that Scharf‟s vestibular neurectomy patients did not have a complete

section of the vestibular nerve, and some MOCS efferent fibres were left intact that

were able to form the filter. However, Scharf et al. included extensive testing to confirm

a complete section, including visual confirmation by the surgeon during the operation

and later by the researchers on a micrograph taken during the operation, caloric tests

that confirmed a loss of vestibular function, and a loss of the suppression of click-

evoked OAEs. However, no direct anatomical confirmation was possible due to the

human subjects, and it remains possible that some efferent fibres remained (Scharf et

al., 1994; Scharf et al., 1997). The second potential explanation is that there is some

non-MOCS mechanism involved in the formation of the attentional filter that was not

active, or not detected, in the present work.

The failure of either of the two conductive hearing loss participants to form a normal

attentional filter may have important implications for the interpretation of the loss of the

filter in the individuals with SNHL. The conductive hearing loss participants were

included to test whether hearing loss alone would be sufficient to decrease the depth of

the attentional filter, which would imply that the MOCS was not the only mechanism

involved in the filters formation. However, there is an important caveat to the results

obtained with the conductive hearing loss participants. While these participants were

clinically classified as having a pure conductive hearing loss, they had a 15 dB SNHL

component at 2 kHz to their hearing loss that was higher than that of any of the

participants in the normal hearing group. The maximum of 10 dB HL present in the

normal hearing group was sufficient to decrease the depth of the low-frequency side of

the attentional filter, so the loss of the low-frequency side of the filter in the two

conductive hearing loss participants is consistent with the normal hearing results. On the


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high-frequency side of the attentional filter, one of the conductive hearing loss

participants detected the high-frequency probe at a lower rate than the target, and with

only two participants it is unclear exactly how the high-frequency side of the attentional

filter was affected by conductive hearing loss. If the attentional filter does decrease in

depth with conductive hearing loss, it suggests that the formation of the attentional filter

is impaired by hearing loss alone, and that the loss of the filter with SNHL may not

have been due to the loss of the MOCS efferent targets. However, only two participants,

who had a significant SNHL component to their hearing, are insufficient to determine

the effects of conductive hearing loss on the formation of the attentional filter.

Additional research requires the recruitment of a larger number of conductive hearing

loss participants with no SNHL component to their hearing loss, although the

recruitment of such participants proved impossible in the present work. This may be due

to the relatively simple amplification procedures available with conductive hearing

losses, which typically return normal auditory ability in their recipients (Hol et al.,

2004).

Overall, the present results support at least a partial role for the MOCS in the generation

of the attentional filter. A presumed impairment to the MOCS action on the cochlea,

due to a SNHL with a loss of detectable OAEs, was associated with a decrease in the

depth of the high-frequency side of the attentional filter, and the decrease in filter depth

occurred at levels of hearing loss that are physiologically relevant to the impairment of

the MOCS efferent targets. However, the low-frequency side of the attentional filter

reduced in depth at hearing levels that are not associated with appreciable impairments

to the MOCS efferent targets, but may be associated with increases in central auditory

system activity that result in an overactive MOCS acoustic reflex. The decreased depth

of the low-frequency side of the attentional filter over a range of auditory thresholds in


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the normal hearing group identifies a potentially important consequence of subclinical

hearing losses.

Chapter 5. Formation of the attentional filter in cochlear implant

recipients using acoustic presentation

Formation of the attentional filter in cochlear implant recipients using acoustic presentation

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5.1 Introduction

In the previous chapter it was reported that a presumed impairment to MOCS action on

the cochlea was correlated with a reduction of the depth of the attentional filter. SNHL

with a loss of measureable OAEs was used to indicate an impairment to the MOCS

efferent targets (Kim et al., 1996), and the filter was found to be completely lost at a

level of hearing loss consistent with a complete loss of function of the MOCS efferent

targets (Hamernik et al., 1989), which is consistent with previous research by Moore et

al. (1997). This result was also consistent with previous research that showed a

substantial reduction in the depth of the attentional filter after a surgical section of the

MOCS efferent fibres (Scharf et al., 1994; Scharf et al., 1997). A limitation of these

studies is that there could be no direct measurement of the integrity of the MOCS

efferent targets in the previous chapter, or of the MOCS efferent fibres in Scharf et al.‟s

studies. In the previous chapter it was acknowledged that the loss of measurable OAEs

can only indicate a relatively small impairment to the function of the MOCS efferent

targets, as a mild impairment of the MOCS efferent targets can render OAEs

unmeasurable (Attias et al., 1995). Similarly, the sections of the MOCS efferent fibres

in Scharf et al.‟s studies may have been incomplete. An appropriate section was

confirmed visually by the surgeon, and the loss of OAE suppression reported in the

studies indicates a degree of impairment to MOCS action on the cochlea, however some

doubt remains on the completeness of the section (Scharf et al., 1997). This chapter, and

chapter 6, address these concerns by measuring the attentional filter in cochlear implant

(CI) recipients, who are presumed to have no possible MOCS action on hearing.

The loss of MOCS action on hearing in CI recipients is due to the presumed complete or

near-complete loss of the MOCS efferent targets, the OHCs. Cochlear implant

recipients typically have severe to profound SNHL prior to implantation, which is

consistent with a near-complete loss of the MOCS efferent targets, the outer hair cells,


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in the frequency range tested in the present work (Stebbins et al., 1979; Hamernik et al.,

1989). Severe to profound SNHL, as indicated by at least 70 dB HL, is used as a

minimum level of hearing loss in the present study.

Cochlear implant recipients, therefore, are a group presumed to have no possible MOCS

action on the attentional filter measurement. This loss of MOCS action is expected in

the present work to eliminate the formation of the attentional filter in the CI recipients,

based on the loss of the attentional filter with moderate SNHL shown in chapter 4. In

the present chapter, the attentional filter is measured using acoustic presentation to a

commercial speech processor. In the next chapter, the measurement of the attentional

filter is repeated in CI recipients, but instead with a programmed, direct stimulation that

eliminates the acoustic stimulus and commercial speech processor.


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5.2 Methods

5.2.1 Participants

Seven postlingually deafened CI recipients, with hearing loss of various durations and

aetiologies, participated in this research. The durations and aetiologies of hearing loss

for the seven CI recipients are shown in Table 5.1. All participants used a Cochlear

CP810 speech processor and had at least one year’s experience with their current

processor. All participants had a bilateral severe to profound hearing loss prior to

implantation . Post implantation CUNY scores ranged from 90 to 100% (mode =

100%)(City University of New York sentences)(Boothroyd, 1985). Five participants were

implanted bilaterally, however the measurements in the present work were done

monotically, using the ear with the greatest dynamic range at electrode 11, where the

dynamic range is the range of amplitudes between the lowest detectable stimulus and

the highest stimulus that does not cause physical discomfort, reported by their

audiometric histories. All participants had severe or profound SNHL above 500 Hz in the

contralateral ear as reported in their audiometric histories. Participant CI#1 attended

only the preliminary study due to work commitments.


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Table 5.1. Hearing loss durations and aetiology for the CI recipients. Aetiologies are:

SO = Sudden Onset, NI = Noise induced, PG = Progressive congenital, PO =

Progressive onset as adult.

ID Age

(years) Sex Etiology

Approximate duration of severe to profound unaided HL (years) Implant Type

Duration with current CI (years)

Ear used

CI#1 40 M SO 1 CI 512 3 R

CI#2 68 M NI +SO 1 CI 422 (SRA) 1 R

CI#3 33 F SO 0.5 CI 24RE (CA) 1.5 R

CI#4 36 M PO + SO 1 CI 422 (SRA) 1 R

CI#5 68 F PO 4 to 5 CI 512 2 L

CI#6 66 M NI + SO 4 CI 512 2 R

CI#7 66 F PO 14 CI 512 2 R

Three additional participants, 1 male and 2 female ranging in age from 22 to 25 years

of age with normal hearing (< 20 dB HL from 250 Hz to 8 kHz, as tested with a Grason

Stadler GSI 61 Clinical Audiometer) were recruited as a control group.

5.2.2 Stimulus Presentation

Acoustic presentation used the same standard Cochlear CP810 speech processor for all

participants with each participant‟s most recent personal MAP uploaded prior to the

experiment (a MAP is a range of settings unique to each CI recipient, including the

stimulation modes, active electrodes, and the threshold and comfort levels). This

processor was customized to only receive AUX input, and the user selectable sound-

processing strategies, Adaptive Dynamic Range Optimization and AutoSensitivity

Control, were disabled. The speech processor received AUX input from a Cochlear

Lapel Microphone (Z208299), which was fixed in place 1m in front of a GENELEC

8020A loudspeaker. The participants‟ hearing aids or CIs contralateral to the test ear

were switched off for the duration of the experiments.


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The 60 dB SPL(A) background broadband noise was calibrated with a Bruel and Kjaer

Type 2250 Sound Level Meter with a Type 4189 free-field microphone placed in lieu of

the lapel microphone. The to-be-detected pure tones were 300ms in length, as in

previous experiments; however, the frequencies were set at the central frequency of

electrodes on the speech processor using the frequency allocation table shown in

Appendix 8.3. The target frequency was 1.938 kHz, which equated to the central

frequency of electrode 11. The probes were separated from the target and each other by

one electrode, on electrodes 15, 13, 9, and 7, which equates to tones of 1.125, 1.438, 2.5

and 3.313 kHz.

5.2.3 Preliminary study: Simulation

The preliminary study was conducted first, to simulate the experiment and measure the

output of the speech processor in response to the noise and pure tones used during the

attentional filter measurement, and second, to test whether implant recipients would be

able to satisfactorily complete the threshold estimation detection task, and then detect

the tones at thresholds in the attentional filter measurement task.

An important consideration was whether it was appropriate to include cue tones in the

cochlear implant experiments. If the cue tone resulted in an activation of multiple

channels that were adjacent to the cued, target channel, this could result in a spread of

the cue-effect that might attenuate the attentional filter. The pattern of activation that

was generated in response to a pure tone presented at the target frequency and in

background noise was tested by measuring the output of a Cochlear CP810 speech

processor (with the same settings used in the subsequent experiments) attached to a

Cochlear Implant-in-a-box® by Dr. Peter Busby at Cochlear Ltd in Melbourne. This

measured the level of stimulation assigned to each electrode by the speech processor in

current level. Current level is an arbitrary unit of amplitude with a range of 1 to 255,


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that code for stimulation amplitude over a logarithmic range from 10 µA to 1.75 mA.

Representative stimuli were generated by mixing background noise wav files produced

by SoundForge XP, with to-be-detected tone wav files produced by the LabVIEW

program. These combined noise-tone stimuli were limited in duration due to memory

limitations with the hardware used. The specific structure of the stimulus is show in

Figure 5.1.

Figure 5.1. Structure of representative stimuli presented to a CochlearTM implant-in-a-

box®. The stimuli consisted of 900 ms background noise with a 300 ms pure tone

located in the centre of the noise.

CI recipients typically have normal or near-normal auditory thresholds, so the pure tone

was presented at an amplitude measured to produce a 79% detection rate in a normally

hearing participant. This was measured by running the threshold estimation procedure

described in chapter 2 on a normal hearing individual, with the loudspeaker used in the

subsequent tests with CI recipients. The simulations were run with this pure tone at -5

dB, +5 dB, +10 dB and +15 dB to this threshold. The five amplitudes of the pure tone

were presented to the simulation hardware twice, and the results were averaged. The

Implant-in-a-box® produced a database file with the exact current level presented to

each electrode on every stimulation cycle.


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5.2.4 Preliminary study: Threshold & attentional filter procedures

The psychophysical procedures used in the attentional filter measurement have not

previously been reported in CI recipients in the literature. Therefore, an additional

preliminary study was conducted to ensure that stable detection thresholds could be

obtained and that the tones presented at these thresholds would be detected at a

sufficient rate to measure the attentional filter. Two of the six CI recipients, CI#1 and

CI#2, and two normally hearing participants, were included in the preliminary study.

The preliminary study included four sessions which were held on separate days and not

more than one week apart. The sessions included initial threshold measurements at the

target frequency and each of the probe frequencies, which were run as described in

chapter 2, Section 2, in an order randomly assigned at the start of each session. The

amplitude of the tone changed in 5-dB steps throughout the threshold procedure in the

first session, but for the rest of the sessions an initial 5-dB step was used until the first

incorrect response, and then 1-dB steps. Following the threshold procedure, three runs

of the probe-target procedure were used to measure the attentional filter in each

participant. This procedure did not include a cue tone, due to concerns that the louder

cue tone might cause a spread of stimulation from the target electrode to the adjacent

electrodes, which was demonstrated to occur in the simulations. The probe-target

procedure used 75% presentation of the 1938 Hz target tone, with the remaining 25%

spread equally across the 1125, 1438, 2500 and 3313 Hz probes.

5.2.5 Primary Experiment: Measuring the attentional filter

The attentional filter measurements in CI recipients had three important differences

from the probe-target procedure described in chapter 2 and used in chapters 3 and 4.

First, at the beginning of each session, thresholds were measured at the target frequency

and each of the probe frequencies, with the frequency order randomised in each session.


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Second, no cue was used during the experiments to avoid the spread of stimulation from

the target electrode to adjacent electrodes. Third, detection rates of the target and probes

were also measured in an equal-likelihood condition. The equal-likelihood probe-target

procedure presented the target and each probe at the estimated 79% threshold, with the

target and each probe presented an equal number of times, and so participants were not

led to expect a tone at any frequency. This equal-likelihood procedure was run before

the attentional filter procedure so that the participants would not have prior experience

in a 75% target presentation procedure. The first session comprised a training run of the

threshold procedure at each frequency and two training runs of the probe-target

procedure, the second session the equal-likelihood experiment, and finally sessions 3, 4,

and 5 measured the attentional filters of each participant.

Due to the substantial differences in the procedure to those used in the previously

measured attentional filters in normal hearing individuals, including the above three

changes and the use of a monotic presentation, the modified procedure was repeated in

three normally hearing individuals who had participated in the experiments of chapter 3.

The normal-hearing participants followed the above, modified procedures used in the CI

recipients, although using monotic presentation through headphones, rather than the

loudspeaker.

5.2.6 Statistics

The relatively small sample size used in the present chapter required the use of statistics

to test whether individual participants showed the attentional filter. In the previous

chapters the filters in each participant were described using the mean detection rates

across three experimental sessions. This was sufficient, as these mean detection rates for

the target and each probe were pooled for each group, the fifteen normal-hearing

participants and the fourteen SNHL participants, to address whether the entire group


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was able to form the attentional filter, and measure variations across the groups. In the

present chapter, the attentional filter must be addressed in each individual participant. In

order to use the maximum amount of data available, the measurement was changed to

the proportion of correct responses across the three experimental sessions used to

measure the filter, although this is converted to percentage to be reported in the figures.

Pooling the attentional filter data is not expected to reduce any evidence of the

attentional filter, if it is present in these individuals, as the individuals with normal

hearing who showed the attentional filter did so consistently over the three experimental

sessions in chapter 3. Confidence intervals for the proportion of correct responses at

each frequency were calculated using the Newcombe-Wilson method without continuity

correction (Method 10 from (Newcombe, 1998), using the calculator supplied by

Herbert (2013) . Five confidence intervals were measured per participant, and so the

Bonferroni correction for multiple comparisons was applied, thus 99% confidence

intervals were used in each subject.


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5.3 Results

5.3.1 Preliminary study: Simulation results

The results of the simulations were separated into the average stimulation level and

number of stimulations for each 300ms time period prior to, during, and after the tone,

as shown in Figure 5.2. The targeted electrode 11 showed slightly higher current levels

and was stimulated more often during the tone relative to before and after the tone.

Figure 5.2. Mean amplitude, in current level (panel A) and number of stimulations

(panel B) on each electrode in response to noise, as measured prior to, during, and after

a near-threshold pure tone presented at the centre frequency of Electrode 11. Top panel

shows mean ± SD.


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Figure 5.3 shows the current level on electrode 11 and the surrounding electrodes in

response to different amplitudes of the probe tone during the simulations. In addition to

the increased stimulation on the target electrode 11, stimulation increased on the

adjacent electrode 10 with higher tone levels. This was apparent as an increase in the

number of stimulations on electrode 10 as well. This spread of stimulation was apparent

before the tone reached the typically used cue amplitude of +12 dB, demonstrating that

a cue tone would result in a spread of stimulation to adjacent electrodes. For this reason,

the cue was not included in the acoustic presentation experiment. It is important to note

that the simulation records the software-based current levels set by the speech

processor, and does not give an indication of any electrical current bleed in the cochlea.


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(panel B) during a pure tone, presented at the centre frequency of electrode 11 at an

amplitude estimated to result in a 79% detection threshold in a normal hearing

individual, and at -5, +5, +10 and +15 dB relative to this threshold on the electrodes

near to the target electrode. Top panel shows mean ± SD.

5.3.2 Preliminary study: Threshold & attentional filter procedures

Figure 5.4 shows the result of three runs of the threshold tracking procedure at the target

frequency for two normal-hearing participants and two CI recipients. The threshold

tracking procedure typically shows a rapid drop to the threshold, and then a near-flat

track around it. This pattern is present in both the normal-hearing participants and the

CI recipients.


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Figure 5.4. Amplitude of the to-be-detected signal in sound card units as a function of

trial number for two normal-hearing participants (NH#1 and NH#2) and two cochlear

implant recipients (CI#1 and CI#2). The tracking is shown for three sessions using a

1.938 kHz pure tone, with an initial 5-dB step size until the first incorrect response, and

a 1-dB step size thereafter.

The mean detection rates of the target and probes as a function of frequency for the two

CI recipients and the two normal-hearing participants, calculated from the attentional

filter measurement, are shown in Figure 5.5. Although slightly below the 79% threshold

estimate, the detection rates for the CI recipients are sufficiently above the 50% chance-

detection level to demonstrate that the CI recipients were able to detect the tones. The

normal-hearing participants had prior experience in the attentional filter task, and

showed the typical attentional filter shape, with an increase in detection rate at the target

frequency.


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Figure 5.5. The detection rates of the target and probes as a function of frequency for

the two CI recipients and the two NH participants in the pilot study. The error bars show

SEM, where the SEM is above 1%.

5.3.3 Primary experiment: Measuring the attentional filter

The estimated thresholds for the 1.938-kHz tone were averaged for each of the six CI

recipients and are reported in Table 5.2 in decibels relative to the estimated threshold

for a normal hearing individual. While all CI recipients required louder tones to reach

the threshold, CI#2 and CI#4 were within 5 dB of the normal hearing thresholds. CI#7

had the highest threshold, with a tone amplitude 11.8 dB higher than that of a normal

hearing individual. With a severe to profound hearing loss without the cochlear implant,


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this suggests that the tones will be too quiet to activate any residual hearing in the

profoundly deafened CI recipients.

Table 5.2. Estimated thresholds for a 79% detection rate of the 1.938-kHz target tone,

reported in decibels relative to the 79% detection threshold estimated for a normal

hearing participant.

CI Recipient Estimated threshold in

dB re: normal hearing

CI#2 0.9

CI#3 9.7

CI#4 3.7

CI#5 9.1

CI#6 6.8

CI#7 11.8

Attentional filters were measured with acoustic presentation in six CI recipients, and in

three individuals with normal hearing. Figure 5.6 shows the mean detection rates of the

target and the probes as a function of frequency in the CI group and the normal-hearing

group. The attentional filters in the normal-hearing group show an increase in detection

rate at the target frequency in the attentional filter condition compared to the detection

rate of the target in the equal-likelihood condition. These are important indications of

the typical attentional filter, and demonstrate that the filter can be formed using the

larger frequency separation, no cue tone, and monotic presentation in normal hearing

individuals. In contrast however, the CI recipients do not show a clear increase in the

detection rate of the target tone compared to that of the probe tones. Importantly, there

is no clear difference in detection rate between the attentional filter and equal-likelihood

conditions.


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Figure 5.6. Average detection rates of the target and probe tones for the 3 normal-

hearing participants and the 6 cochlear implant recipients. Two conditions were

included, the attentional filter condition with a target at 1.938 kHz, and probes at 1.125,

1.438, 2.5 and 3.313 kHz, and an equal-likelihood condition, with the same target and

probe frequencies, but all tones were presented in equal number. The error bars show

SEM, where the SEM is higher than 1%.

Figure 5.7 shows the mean detection rates of the target and probes for the individual CI

recipients in the attentional filter and equal-likelihood conditions. CI#5, CI#6 and CI#7

do not show clear differences in detection rate between the attentional filter and equal-

likelihood conditions. CI#4 shows a higher detection rate of the target tone compared to

that of the 1.125-, 2.5- and 3.313-kHz probes in the attentional filter condition, and the

target‟s detection rate is higher in the attentional filter condition relative to the equal-

likelihood condition. Thus, CI#4 shows an increased detection rate for the more-

frequently presented target tone which was only present at this frequency when the

target was presented more frequently than the probes, which is consistent with the

normal formation of the attentional filter. CI#2 shows a peak of detection rates at the

target frequency in the attentional filter condition, apparently consistent with the normal

formation of the filter, however this pattern of result is present in the equal-likelihood

condition. This suggests that the apparent attentional filter shown in CI#2 is not due to


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the more frequent presentations of the target tone, and therefore not truly representative

of the presence of the attentional filter. However, this is the only participant to attend

the previous, preliminary study, which included an attentional filter measurement task

with a 75% presentation rate of the 1.938-kHz target frequency. CI#3 demonstrated a

higher detection rate of the two high frequency probes in the attentional filter condition

than in the equal-likelihood condition, whereas detection rates of the target and low-

frequency probes were the same in the two conditions. Thus, the more-frequent

presentations of the target tone failed to increase its detection rate but may have

enhanced the detection rates of higher-frequency tones.


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Figure 5.7. Mean detection rate of the target and probes for the individual CI recipients.

Two conditions are included, the attentional filter condition (solid lines and filled

circles) with a target at 1.938 kHz, and probes at 1.125, 1.438, 2.5 and 3.313 kHz, as

well as an equal-likelihood condition (dashed lines, and open circles), with the same

target and probe frequencies, but all tones were presented in equal number. The error

bars show 99% CIs and * indicates a significant difference in detection rate from that

probe compared to the target tone in only the attentional filter condition.


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5.4 Discussion

The present chapter investigated the attentional filter in six CI recipients, all of whom

had profound SNHL prior to implantation and were presumed to have no remaining

MOCS action on hearing, due to the loss of the MOCS efferent targets (Stebbins et al.,

1979; Hamernik et al., 1989). To support the presence of the attentional filter, the CI

recipients would have to show both a clear increase in the detection rate of the target

tone in the attentional filter condition, and an increased detection rate of the target in the

attentional filter condition compared to its detection rate in the equiprobable condition.

Five of the six CI recipients failed to meet these criteria, and so failed to show the

attentional filter. This result is consistent with the results of chapter 4, and reaffirms the

dependence of the attentional filter on the normal function of MOCS action on hearing.

However, in contrast to the absence of the filter in these participants, CI#4 shows a clear

increase in the detection rate of the target tone compared to the detection rate of the

probes in the attentional filter condition, and an increase in the target‟s detection rate in

the attentional filter condition compared to the equal-likelihood condition. Therefore,

CI#4 fulfils the typical features of the attentional filter, and demonstrates the filter‟s

formation in an individual presumed to have no possible MOCS action on hearing.

Thus, there are two major results in the present chapter. First is the absence of the

attentional filter in five of the six tested CI recipients, which is consistent with the

results of chapter 4 and with previous research by Scharf et al. (1994, 1997) and Moore

et al. (1997). Second is the apparent formation of the attentional filter in CI#4, which

suggests the presence of an alternative mechanism able to form the attentional filter in

some CI recipients.

The absence of the attentional filter in five of the six CI recipients is consistent with

previous research on the formation of the filter in individuals with reduced function of

the MOCS. However, is it possible that the formation of the attentional filter was


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eliminated by the function of the cochlear implant, rather than the impairment to MOCS

function, such as the current spread associated with the cochlear implant? Firstly, is it

possible that the settings of the cochlear implant affected the filter's formation? During

the task, each CI recipient used their individual MAP, and the available dynamic range

on each electrode (i.e. the difference between the comfort level and the threshold level)

varied across the participants. However, to avoid an effect of varying dynamic ranges,

the detection thresholds were estimated for the target and each of the probes, which

prevents inter-subject MAP differences from altering the detection thresholds.

Secondly, current spread may affect the experiment, and there were two types of current

spread that may have been involved. The first is a software-based spread of electrode

activation based on the workings of the speech processor, and the second is an

intracochlear spread of current from the electrodes. The effect of software-based spread

of electrode activation was estimated in the simulations prior to running the full

experiment, with the conclusion that a spread of activation existed towards the

numerically lower or more basal electrodes with increasing stimulus amplitude. This

software-based spread was limited to the electrode immediately adjacent to the targeted

electrode, from the target electrode 11 onto the adjacent electrode 10, and did not occur

on the other tested electrodes, electrodes 9, 12, or 13. Therefore, the software-based

current spread did not affect the electrodes responsible for the to-be-detected tones in

the attentional filter measurement, for the 2.5 kHz tone on electrode 9 or the 1.48 kHz

tone on electrode 13. This was true for simulations of up to +15 dB to an estimated

normal hearing individual‟s threshold, and the CI recipients‟ thresholds did not exceed

+12 dB above the threshold, and so the simulations remain valid. However, no direct

measurement of the stimulation patterns could be made in the individual CI recipients.

It remains possible that the speech processor caused a wider spread of activation during

the attentional filter measurement, as the processor regularly received five different pure


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tones, the target and four probes, which were presented at the centre frequencies of 5

different implant channels. This condition was not tested by the simulations, during

which only one tone was presented in the background noise, and so it is not clear

whether there was a software-based spread of stimulation during the attentional filter

measurement. The second type of current spread is an intracochlear spread due to the

electrodes being immersed in conductive perilymph. This intracochlear current spread

has been shown in previous research to travel preferentially towards the basal side of the

cochlea, and may be substantial with the monopolar stimulation used in the present

work (Cohen et al., 2003), although there is evidence that other stimulation modes, like

the commonly used bipolar stimulation, cause similar levels of spread during a signal-

in-noise task, and so changing stimulation modes would not have addressed this concern

(Kwon and van den Honert, 2006; Snyder et al., 2008). The present work was unable to

measure this intracochlear current spread, and the spread is likely to vary between CI

recipients, as it increases with a roughly linear relationship with stimulus amplitude

(Cohen et al., 2003). If this intracochlear current spread was sufficient to prevent the CI

recipients from discriminating the target and probes, it may have eliminated the

attentional filter. However, this level of current bleed would be detectable as an increase

in the frequency difference limens, and, as discussed below, individuals with cochlear

implants typically have difference limens that are typically much smaller than the

frequency range used in to measure the attentional filter.

A second potential cause of the loss of the attentional filter, which is unrelated to the

loss of MOCS action on hearing, is the reduced peripheral bandwidth caused by

decreased frequency discriminability in implant users. If a decrease in frequency

discrimination was sufficient to make the target and probes indistinguishable, it may

prevent the formation of the attentional filter, similar to the spread of intracochlear

current discussed above. A prior study measured the frequency difference limens for a


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group of CI recipients, of which twenty-one out of forty-nine had CochlearTM Nucleus

CI22M or CI24M implants that are comparable to those used by the CI recipients in the

present work (Gfeller et al., 2002b). At 2 kHz, the median just noticeable difference for

the forty-nine CI recipients was 134 Hz, with a maximum of 314 Hz. This result

suggests that the probes nearest the target in the present work, at 500 Hz below and 562

Hz above the target frequency will be distinguishable from the target. Although this

places the probes nearest the target within 200 Hz of the just noticeable difference, there

are still the probes distant to the target, at 813 Hz below and 1375 Hz above the target

frequency. These more distant probes were outside the just noticeable limits and so

would be expected to be discriminable from the target tone, and thus show the presence

of the attentional filter, if formed in these CI recipients. Thus, although it is possible

that an inability to discriminate the target and the probes nearest the target affects the

worst performers in the present work, this is unlikely to render the target and distant

probes indistinguishable, and therefore is not expected to cause the absence of the

attentional filter in the CI recipients.

CI#2 showed one of the two conditions required for the presence of the attentional filter,

the increase in the detection rate of the target compared to that of the probes in the

attentional filter condition; however, this bias towards the target frequency was also

present in the equal-likelihood condition. This may have happened due to the variations

in detection rate in the equal-likelihood condition that were present in all CI recipients.

These variations in detection rate occurred even though each tone was presented at an

amplitude measured to be detectable on 79% of all presentations for each participant.

An alternative explanation for the apparent bias towards the target frequency in CI#2 is

the prior experience this participant had in an attentional filter measurement task. CI#2

attended the preliminary study, which included three runs of the attentional filter

condition and was held prior to running the equal-likelihood condition. This prior


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training may have caused the participant to form the shape of the attentional filter

during the very similar equal-likelihood condition, and CI#2 was the only participant

included in both the preliminary study as well as the primary experiment. However,

there is no direct evidence to support this interpretation, and so the participant is

considered to show no formation of the attentional filter in the present chapter.

CI#3 showed an off-target enhancement of the high-frequency probes in the attentional

filter condition compared with the equal-likelihood condition, and no change in

detection rate of the target tone. This off-target increase in detectability of the high-

frequency probes may be due to a mismatch between the cochlear region stimulated by

the 1.938-kHz target tone and the non-MOCS mechanism that may have been

responsible for forming the attentional filter in CI#4, discussed below. There is

precedent for such a mismatch, as the electrode array typically stimulates regions of the

cochlea at a more basal location of the normal pitch-place map in the cochlea, due to

limitations in fitting an electrode array in the cochlear spiral (Ketten et al., 1998). As a

result, the electrode-array stimulates at locations on the cochlea typically associated

with a higher pitch percept than the speech processor assigns. Over one to two years, the

pitch brought about by activating each electrode shifts, from a relatively high-frequency

pitch that is reflective of the pitch-place map, to a lower frequency pitch that reflects the

pitches assigned by the speech processor (Reiss et al., 2007). The results of Reiss et al.

(2007) were observed with relatively short electrode arrays, with the Iowa/Nucleus

hybrid implant, that is implanted only in the basal regions of the cochlea. This result is

not seen with all cochlear implants, for example the effect was a non-significant trend in

research that used a longer 31-mm FLEXSOFT MED-EL electrode, perhaps due to the

smaller difference between the pitch-place and assigned frequency on each electrode

with the longer electrode (Vermeire et al., 2015). CI#3‟s abnormal filter may be a result

of this frequency mismatch between the pitch-place regions of the cochlea stimulated by


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the implant and the central cochleotopic map, which may be in the process of

undergoing a plastic adaptation to better reflect the higher-than-expected stimulation

from the cochlear implant.

CI#4 shows the typical signs of the attentional filter, with a detection bias towards the

target over the probes, and an enhancement of the target in the attentional filter

condition compared with its detection rate in the equal-likelihood condition. CI#4 was,

therefore, able to bias sensitivity towards specific frequencies in noise based only on the

history of presentation, to form a normal attentional filter. This participant had a severe

SNHL prior to receiving the cochlear implant, and had a detection threshold at 1.938

kHz that was 5.8 dB higher than a normal hearing individual, and so the to-be-detected

target tone would not be detectable with the participant‟s residual hearing. Thus, CI#4

would not be expected to have any MOCS efferent action on hearing during the

experiment. It is unclear what enables CI#4 to form the filter, but not the other CI

recipients. CI#4 did not have the shortest duration of profound deafness (longer than

CI#3 and equal to CI#2), nor did he have the longest duration of experience with his

current CI. The apparent formation of filter in CI#4 suggests the presence of an

alternative mechanism that is able to form the attentional filter in at least one CI

recipient, and this mechanism must be unrelated to MOCS efferent control of the

cochlear amplifier. Potential sources for the alternative mechanism will be discussed in

chapter 6.

The formation of the attentional filter in the present work may have been affected by the

speech processor. All user-selectable noise-processing strategies were switched off for

the duration of the experiment, and to limit any hardware or software related variations

in the processing of the stimuli the same speech-processor was used for each participant.

However, it is unclear whether the pattern of stimulation in response to the tones was

consistent, both between individual participants and between participants‟ sessions. Any


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variability in the presentation of the stimuli may have resulted in, or prevented, the

appearance of the attentional filter. Thus, the results obtained in the present chapter are

limited by the unknown and potentially unwanted effects of the speech processor used

to receive the acoustic presentation.

The results of this chapter showed the loss of the attentional filter in five of the six

tested CI recipients, all of whom were presumed to have no remaining MOCS action on

the cochlea. This finding is consistent with the results of chapter 4, and supports a role

for the MOCS in generating the attentional filter. However, CI#4 showed the apparent

formation of a normal attentional filter, which suggests the presence of an alternative

mechanism that is able to form the filter in some CI recipients. As yet, it is unclear

whether this mechanism is unique to CI recipients, or if it functions in the normal

formation of the attentional filter. No evidence of the alternative mechanism was found

in chapter 4, with all individuals with at least moderate SNHL showing a substantial

loss of the attentional filter. However, the use of acoustic presentation and a commercial

speech processor in the present chapter may have caused or prevented the formation of

the attentional filter in the present experiments. The next chapter, chapter 6, describes a

similar set of experiments, but using a programmed, direct stimulation mode that uses

no acoustic presentation and a known stimulation pattern, to complement the results

obtained with the acoustic presentation in the present chapter.

Chapter 6. Formation of the attentional filter in cochlear implant

recipients using programmed, direct stimulation

Formation of the attentional filter in cochlear implant recipients using programmed, direct stimulation

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6.1 Introduction

The attentional filter has been shown to be impaired in conditions presumed to reduce

the MOCS action on the cochlea in previous research (Moore et al., 1996; Scharf et al.,

1997), and in chapters 4 and 5 of this thesis. Consistent with these studies, the results of

chapter 5 showed the absence of the attentional filter in five of six tested CI recipients.

One CI recipient, however, showed a normal attentional filter. The presence of the filter

in this CI recipient, who would not be expected to have any remaining MOCS efferent

targets (Stebbins et al., 1979; Hamernik et al., 1989), suggests the presence of an

alternative, non-MOCS mechanism that is able to form an attentional filter. However,

the experiments described in chapter 5 may have included unknown effects of the

commercial CP810 speech processor which was used during the experiments. While all

user-selectable sound processing strategies were disabled (e.g. Adaptive Dynamic

Range Optimization and AutoSensitivity Control), the effect of the speech processor on

the reception of the signals is unknown. Therefore, it is unclear whether the results of

chapter 5 were physiological phenomena or due to the effects of the speech processor.

In the present chapter, attentional filters were again measured in CI recipients; however,

the stimulation on each electrode was directly programmed during the procedure, and

presented to the participant using the Cochlear Ltd. Nucleus Implant Communicator™

software and an L34 research processor. The L34 research processor differs

significantly from the commercially available CP810 speech processor used in the

previous chapter. The software-based speech processing can be disabled on the L34

research processor, and a known pattern of stimuli can be programmed to be presented

to the electrode array. This eliminates the potentially unwanted, unknown effects of the

speech processor which may have been present in chapter 5. Therefore, the experiments

of the present chapter complement those of the previous chapter, as the attentional filter

is measured in a group presumed to have no possible MOCS action on the reception of


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the signals, with the additional elimination of the potentially unwanted effects of the

commercial speech processor.


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6.2 Methods

6.2.1 Participants

Four of the six CI recipients that had participated in the experiments of chapter 5, CI#2,

CI#3, CI4 and CI#5, participated in the direct stimulation experiments. The durations

and aetiologies of each subject‟s hearing loss are stated in Table 5.1. The CI recipients

used a Cochlear CP810 speech processor in day-to-day living, and had at least one

year’s experience with their current processor. Each of the CI recipients had bilateral

implants, however only the ear with the greatest dynamic range at electrode 11 was

used. All of the CI recipients had severe to profound hearing loss prior to implantation

with pre-operative CUNY (spoken sentences in quiet) scores of 0%. Post implantation

CUNY scores ranged from 90 to 100% (mode = 100%).

6.2.2 Constructing the stimuli

There were no acoustic signals used in the experiments described in the present chapter;

all stimuli were presented directly through the L34 body-worn research processor which

had its microphones disabled for the duration of the experiments. The stimuli were

programmed using the Python programming language (Rossum, 2007) and presented to

the implants using the Cochlear™ Nucleus Implant Communicator (NIC) software and

a Cochlear™ L34 body-worn research processor. By programming the stimuli, the

software-based spread of stimulation that was produced by the speech processor in

response to the cue tone (that was identified as a concern in chapter 5) was avoided,

allowing the use of a cue tone in this experiment.

The construction of the stimuli followed the ACE processing strategy used day-to-day

by the CI recipients (Patrick et al., 2006). According to this strategy the Cochlear™

implants used by the participants in this chapter stimulate on one electrode at a time,

with a biphasic pulse using a 25 µs pulse width and an 8 µs interphase gap. The


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stimulation rate is variable among CI recipients, but a 900 Hz rate per electrode, the

default setting, was used by all participants in the present experiment. The ACE

processing strategy chooses 8 maxima, based on the frequency ranges with the most

acoustic energy, and stimulates on 8 corresponding electrodes in a sequential, ascending

pattern. These 8 electrode cycles must contain 8 non-repeated electrodes. An important

consideration is each CI recipient‟s comfort level on each electrode, as any stimulation

above this level can cause physical discomfort. If, at any point, a desired current level

exceeded the recipient‟s comfort level for that electrode the program stopped before

sending this to the implant, and aborted the test.

All stimuli were programmed on-the-fly; however, a hardware memory limitation

restricted the length of the stimuli to 2.7 seconds. This prevented the use of a continuous

background noise as used in the previous experiments. Instead, the stimuli were

constructed to be equivalent to a 2.7 second noise stimulus, with a 300 ms cue stimulus

beginning 500 ms after the beginning of the noise, and a 300 ms to-be-detected stimulus

in one of two intervals either 300 or 600 ms after the end of the cue stimulus.

Programming the noise was done by stimulating randomly selected electrodes

throughout the noise period. To follow the ACE processing strategy, the noise was

programmed by stimulating 8 randomly selected electrodes during each cycle, from

electrodes 3 to 19. An initial current level at an equivalent of 25% of each electrode‟s

dynamic range was used, with an additional jitter of plus or minus up to 3 current levels

using a Gaussian distribution. The noise was calibrated in amplitude and low to high

frequency balance at the beginning of each experiment as described in Figure 6.1 below.

To insert a cue, target, or probe stimulus, a stimulation of the desired electrode was

substituted into the existing noise array on the 8-electrode cycles. To do this, one of the

electrodes that had been chosen to present noise on one cycle was randomly chosen to

be substituted with stimulation on the desired cue, target, or probe electrode. This was


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done for each cycle over the desired length of stimulation. The target and probes were

presented at the current level previously estimated for a 79% detection threshold, while

the cue was presented at +5 current levels relative to this threshold. An outline of the

structure with an example is shown below in Figure 6.1.

Figure 6.1. Structure of the Python program used to construct the 2.7 second stimuli,

including both the noise and the tone, for the direct stimulation research, including an

example of the program‟s output for a single cycle.

6.2.3 Measuring the attentional filter

Before measuring the attentional filter, the background noise was calibrated to produce

equal loudness from the low to the high frequency electrodes. To achieve this, the

participants were given controls in a graphical user interface to increase or decrease the

amplitude of the stimulus or to replay it. The participants were then presented with a 1

second noise stimulus in the structure described in section 2.2 above, with the amplitude


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on each electrode set at 25% of each electrode‟s dynamic range, the range of amplitudes

between the lowest detectable stimulus and the highest stimulus that does not cause

physical discomfort. Participants were asked to make the stimulus of comparable

loudness to a comfortably spoken conversation. Once this level was reached, the low to

high frequency balance of the noise was calibrated. Using the same graphical user

interface, the participants were able to increase or decrease the amplitude of the “Low”

(electrodes 12, 13, 14, 15, 16, 17, 18, and 19) or the “High” (electrodes 4, 5, 6, 7, 8, 9,

10 and 11) frequencies. The participants were asked to equalise any low or high

frequency imbalances, so that the noise sounded equally loud across the electrode array.

Any response changed the amplitude in current level increments equal to 5% of the

dynamic range on each electrode, and the participants were free to make as many

changes as they saw fit. In practice, very few participants altered the balance of the

noise after setting it to a comfortable loudness. The noise was described by the

participants as a “Hiss”, “Fuzz”, or a “TV set to the wrong channel”.

The threshold measuring procedure followed the same structure as used in the previous

experiments, with an initial change in stimulus amplitude of 5 current levels until the

first incorrect response, after which 1 current level steps were used. Thresholds were

measured at the beginning of each session for the target electrode 11 and each of the

probe electrodes, with the order randomized on each session. All thresholds were

measured in the presence of the previously adjusted background noise stimulation.

The attentional filter measurement procedure used the same structure described in

chapter 2, Section 2, except for the use of 2.7 second long bursts of noise stimuli, rather

than a continuous background noise. The cue stimulus was presented at +5 current

levels relative to the threshold on the target electrode 11, which made it clearly audible,

and the probe stimuli were presented on electrodes 9, 10, 12 and 13. The target was

presented on 75% of all trials, with the remaining 25% equally spread across the probes.


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Participants‟ hearing aids or cochlear implants contralateral to the test ear were switched

off for the duration of the experiment.

6.2.4 Shifted target experiments

A second experiment was conducted using the attentional filter measurement procedure

described above, but the cue and target were shifted to electrode 14. Electrode 14 was

chosen as it was outside the electrode range used in the previous attentional filter

measurement task (electrodes 9 to 13). Therefore, the detectability of the new target

electrode 14 would not have been affected by prior experience, which the results of

chapter 5, and specifically the apparent target bias in CI#2 suggested may affect the

formation of the filter. The probe electrodes were 12, 13, 15 and 16. Only CI#2 and

CI#4 were able to participate in the shifted target experiment.

6.2.5 Statistics

As in the previous chapter, detection rates are reported as a proportion across the three

experimental sessions used to measure the filter, although this is converted to

percentage to be reported in the figures. The confidence intervals for the proportion of

correct responses at each frequency were calculated using the Newcombe-Wilson

method without continuity correction (Method 10 from (Newcombe, 1998), calculated

using Herbert (2013). The Bonferroni correction for multiple comparisons was applied,

and as a result, 99% confidence intervals were used in each subject.


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6.3 Results

6.3.1 Stimulation details

Figure 6.2 shows an example stimulation pattern for participant CI#4 before, during and

after the 300-ms „tone‟ stimulus. These results show a close similarity to those in Figure

5.2, which were a result of simulations for the acoustic stimuli.


(panel B) during the programmed, direct stimulation of the experimental stimulus. Top

panel shows mean ± SD.


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6.3.2 Attentional Filter measurements

Figure 6.3 shows the mean detection rates of the target and each of the probes with 99%

CIs. In a similar result to chapter 5, CI#4 shows an increase in the detection rate of the

target compared to the probes, although only significant between the target and the

probes on electrodes 9 and 13. CI#2 shows a similar, apparently normal attentional filter

shape of detection rates, with the detection rate of the target significantly higher than

that of the probes. CI#3 shows no significant differences in detection rate across the

tested frequency range, consistent with showing an absence of an attentional filter. CI#5

showed a detection rate of the target near 50%, which suggests that this participant did

not detect the target, or the probes on electrodes 12 and 13. However, CI#5 was able to

complete the task, supported by a consistent detection of the probe on electrode 9

throughout the task.

It is also interesting to note that the detection rate of the target stimulus was greater than

the estimated 79% detection threshold for CI#4, elevated to approximately 84%, and for

CI#2, greatly elevated to near-to 100%. In CI#4 there was a decrease of the detection

rate of the probe on electrode 9 from its 79% detection threshold, whereas CI#2 had a

detection rate of all probes near to the 79% threshold. This result may represent an

underestimation of the target‟s threshold in CI#2.


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Figure 6.3. Detection rate of the target, on electrode 11, and the probe stimuli on

electrodes 9, 10, 12 and 13. Electrodes arrayed in descending order, as a higher

electrode equates to a lower frequency percept. Error bars show the 99% CIs and *

indicates a significant difference in detection rate from that of the target tone.

The results of the present chapter can be compared with those of the previous chapter, in

which the attentional filter was measured in the same participants, but without a cue and

using acoustic presentation. To make this comparison possible, the pure tones used as

the target and probe stimuli in the previous chapter can be converted to electrode

numbers using the standard frequency allocation table (see Appendix 8.3).

Figure 6.4 shows the detection rates of the acoustically presented pure tone target and

probes from chapter 5 as well as the detection rates of the programmed, direct stimuli

used in the present chapter. Overall, a relatively close match was found for the detection


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rates between the two stimulation modes, which was most notable for CI#2 and CI#4.

CI#2 consistently showed an increase in detection rates of the target tone compared to

that of the probes, consistent with the presence of the attentional filter. However, CI#2

showed a substantial increase in the detection rate of the target stimulus, from a mean

detection rate of 81% with acoustic presentation to a mean of 98% with programmed,

direct presentation. Similarly, CI#4 showed a consistent bias towards the target

frequency over the detection rate of the probes, although there were no apparent

differences in the detection rates between the stimulation modes. CI#3 showed small

changes in detection rates using programmed, direct stimulation compared with acoustic

stimulation, although both results were generally consistent with a flat detection rate

across the tested frequency range. CI#5 had a substantial change in detection rates with

programmed, direct presentation compared to acoustic presentation. With acoustic

presentation, CI#5 showed relatively high detection rates of the target electrode and the

nearby low-frequency probe. With programmed, direct stimulation however, the

detection rates of the target electrode and both electrodes programmed for lower

frequencies were near to 50%, which is consistent with the participant guessing for the

majority of these presentations.


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Figure 6.4. The detection rates of the target and the probes as a function of electrode for

both the present chapter, with programmed, direct stimulation, and the previous chapter,

with acoustic presentation. The centre frequencies are used to convert the target and

probe frequencies with acoustic presentation to electrode number, using the standard

FAT shown in the appendix 8.3. Error bars show the 99% CIs.

An additional “Shifted Target” experiment was performed with CI#2 and CI#4, to test

whether the formation of the filter was a physiological phenomenon, or due to a chance

bias towards the detection of stimulation of the target electrode. In this experiment, the

target and cue electrode was shifted to electrode 14, and the probe electrodes were


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shifted to 12, 13, 15 and 16. Figure 6.5 shows the detection rates of the new shifted

target and probes in CI#2 and CI#4, in comparison with their earlier results. As in the

previous experiments, CI#2 and CI#4 showed a higher detection rate of the target

electrode compared to the probe electrodes, although the new, shifted filter was reduced

in depth compared with the previous filter with a target at electrode 11.

Figure 6.5. The detection rates of the target, on electrode 14, and of the probes on each

electrode in a shifted target experiment, with a comparison to the previous experiment

using a target on electrode 11. Electrodes are arrayed in descending order, as a higher

electrode equates to a lower frequency percept. The error bars show 99% CIs, and *

indicates significant differences in the shifted target experiment, relative to the target

electrode 14.


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6.4 Discussion

Previous work has consistently shown reduced depth of the attentional filter in

conditions presumed to impair the MOCS action on the cochlea, as shown in chapter 4

of the present thesis, and in previous research by Scharf et al. (1997) and Moore et al.

(1999). The results of the chapter 5 were broadly consistent with these findings, as the

filter was absent in five of six tested CI recipients who were presumed to have no

appreciable function of the MOCS efferent targets, the outer hair cells, because of their

severe to profound SNHL (Hamernik et al., 1989). However, in contrast to the earlier

findings, CI#4 satisfied both conditions required to support the presence of the

attentional filter, with an enhanced detection rate of the target frequency over the probe

frequencies that was not present in an equal-likelihood condition. A possible

explanation for the presence of the attentional filter in CI#4 was the use of acoustic

presentation to a commercial speech processor, as the output of the speech processor

was unknown, and may have affected the detectability of particular frequencies. To

address this potential issue, the present chapter used programmed, direct stimulation

which allowed a known, controlled set of stimuli to be presented to the participants.

With the programmed, direct stimulation, two of the four participants, CI#3 and CI#5,

did not show an attentional filter, which was consistent with their results in chapter 5,

and supports the loss of the attentional filter in conditions presumed to impair MOCS

action on hearing. However, two participants, CI#2 and CI#4, showed a higher

detection rate of the target compared with the probes, which was consistent with the

formation of the attentional filter. Importantly, when the target was shifted to a different

electrode, the formation of the attentional filter was replicated at this new target, which

supports a physiological mechanism forming the attentional filter. The presence of a

second, shifted attentional filter mirrors what would be expected in a normal hearing

participant, in whom filters can be shown at multiple frequencies, for example Dai et al.


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(1991) showed the filters formation at five different target frequencies from 0.25 to 4

kHz. This result demonstrates the formation of the attentional filter in two CI recipients,

in a condition with no possible effect of the MOCS efferent control of the cochlear

amplifier on the reception of the signals, and with no influence of the commercial

speech processor that was present in chapter 5.

The absence of the attentional filter in CI#3 and CI#5 supports the results of chapters 4

and 5 in the present work, by the absence of the filter in conditions presumed to have no

MOCS action on the cochlea. In the previous chapters, there was a concern that the

filter was not present due to the reduced peripheral bandwidth associated with SNHL or

a cochlear implant, rather than specifically the loss of MOCS action. This reduction in

frequency discrimination is of considerable concern in the present chapter, as the CI

recipients were tasked with discriminating between the target electrode and electrodes

that were either adjacent or separated by only one other electrode. In previous research

including 9 CI recipients, only 2 were able to perfectly discriminate every electrode,

although these recipients used a different electrode type to those used by those in the

present work (Zwolan et al., 1997). This may have rendered the target and probes

indistinguishable when using programmed, direct stimulation, which would have

prevented the formation of the attentional filter. However, CI#3 and CI#5 showed no

evidence of the attentional filter in chapter 5 with acoustic presentation, in which the

distant probes were well outside the maximum frequency difference limens reported for

forty-nine CI recipients (Gfeller et al., 2002a). In addition, the CI recipients used in the

present work had excellent speech recognition in quiet, which would not be expected of

CI recipients unable to discriminate over 8 electrodes. Taken together, the absence of

the attentional filter in CI#3 and CI#5 with acoustic presentation as well as with

programmed, direct stimulation demonstrates that this absence was not due to the

effects of the speech processor, and suggests that the absence of the filters with direct


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stimulation was not due to reduced frequency discrimination. The replicable absence of

the filter in these CI recipients is consistent with the dependence of the filter on the

normal function of MOCS action on hearing.

CI#4 demonstrated the normal formation of an attentional filter in chapter 5 with

acoustic presentation and in the present chapter with programmed, direct stimulation.

There was no indication that CI#4 has remaining MOCS function, or was otherwise

substantially different from the other CI recipients. CI#4 had severe SNHL prior to

implantation, which is consistent with a total loss of function of the MOCS efferent

targets (Hamernik et al., 1989). CI#4 did not have an unusual duration of severe SNHL

prior to implantation, as his duration was matched by CI#2, longer than that of CI#3,

but shorter than CI#5, nor did CI#4 have an extended experience with his implant

compared with the other CI recipients. Indeed, the formation of the attentional filter in

the present chapter demonstrates the filter‟s presence in response to purely electric

signals, as no acoustic signals were used in the programmed, direct stimulation.

Therefore, the cochlear amplifier could not have affected the reception of the stimuli, if

there were remaining MOCS efferent targets, which conclusively eliminates the efferent

output of the MOCS as a possible cause for the formation of the attentional filter in this

experiment. This consistent, replicable formation of the filter in CI#4, without the

influence of the MOCS action or the commercial speech processor used in chapter 5,

supports the presence of an alternative mechanism that is able to form the attentional

filter in some CI recipients.

The second participant to show the attentional filter in the present chapter, CI#2, did not

satisfy the conditions for the filter‟s presence in chapter 5, because the enhancement of

the target was also present in an equal-likelihood condition. In chapter 5, it was

suggested that this enhancement was due to the participant‟s prior training in the

attentional filter condition, during the preliminary study. In these sessions, the target


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frequency was presented on 75% of all trials, and these sessions were held before

running the equal-likelihood condition. This prior experience may have created a

persistent attentional bias towards the more-frequently presented target frequency, and

this bias may have affected his performance in the equal-likelihood procedure, which

used the same probe frequencies. The formation of the attentional filter with the shifted

target in the present chapter supports the real formation of the attentional filter in CI#2,

although it remains possible that the participant had a chance bias towards the target

electrodes, which would have caused the apparent formation of the filter. In retrospect,

it would have been useful to run a shifted target experiment that included the previous

target stimulus, but presented rarely as a probe stimulus. This method may have shown

a reduction in the previous target‟s detection rate, which would have provided stronger

support for the physiological presence of the attentional filter.

The source of the alternative mechanism that formed the attentional filter in CI#4, and

perhaps in CI#2, is not necessarily independent of the MOCS, although it cannot

involve the MOCS efferent control of the cochlear amplifier. The MOCS has another

output, as collateral fibres that project to the cochlear nucleus (Rasmussen, 1960;

Rasmussen, 1967; White and Warr, 1983; Brown et al., 1988; Winter et al., 1989). The

MOCS collaterals have been shown to have both excitatory and inhibitory effects on

cochlear nucleus neurons‟ spontaneous firing rates and responses to sound (Mulders et

al., 2002; Mulders et al., 2003). The function of these collaterals is unclear, although

they have been proposed to compensate for the MOCS‟ inhibitory effect on the cochlear

amplifier (Benson and Brown, 1990; Kim et al., 1995). It may be that the collaterals can

have a role in the formation of the attentional filter in some CI recipients, although this

role is speculative.

An alternative mechanism for the filter‟s formation may be located in central auditory

structures. Previous research has demonstrated that auditory cortical activity correlates


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with performance in a speech recognition in noise task, which was argued to

demonstrate a selective coding of speech in noise mediated by the auditory cortex (Ding

and Simon, 2013). This central auditory attention may be sufficient to form the

attentional filter in the CI recipients. In support of a centrally located mechanism, the

only CI recipients who showed evidence for the filter‟s presence had relatively short

durations of profound SNHL prior to receiving their cochlear implants, with 1 year each

for CI#4 and CI#2, compared to 4 years for CI#5. A prolonged duration of profound

deafness prior to implantation is well documented to have negative effects on CI

outcomes (Dowell et al., 1985; Dorman et al., 1989; Blamey et al., 2013; Holden et al.,

2013). These poor outcomes are typically attributed to both the degeneration of

peripheral auditory structures, including the spiral ganglion cells that cochlear implants

are thought to communicate with (Nadol et al., 1989; Miura et al., 2002), as well as

central plasticity related to the degeneration of central auditory structures, which causes

the degradation of the fine cochleotopic maps (Robertson and Irvine, 1989; Raggio and

Schreiner, 1999) and/or the invasion of cross-modal plasticity (Rebillard and Rebillard,

1980; Lee et al., 2001). The relationship between deafness-induced plasticity and poor

speech perception outcomes in CI recipients is consistent with a role for central auditory

structures in the forming attentional filter, if the presumed role for the filter in

improving the detectability of signals in noise is true. However, no specific

measurement has been made on the filter‟s formation in relation to deafness-induced

plasticity in CI recipients in the present work or in previous research.

If the central auditory system is the basis for the alternative mechanism forming the

filter in CI#4, how might this mechanism function? Previous research by Moore et al.

(1996) suggested a role for central template matching, as described by Dau et al. (1996),

in forming the attentional filter. The template-matching mechanism is consistent with

some of the known features of the attentional filter, as prior research found that


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providing a more effective template improves detection rates in a manner consistent

with the formation of the attentional filter, such as the benefit provided by imaginary

cues (Borra et al., 2013), as well as the increased detection rates of probes when they

match a cue in duration (Wright and Dai, 1994). Thus, the attentional filter in CI#4 may

have been formed, at least partially, by an effective template-matching mechanism

which may have remained or emerged in this participant due to his relatively short

duration of profound deafness prior to implantation.

In summary, the present chapter replicated the formation of the attentional filter in

CI#4, both without the influence of the speech processor, or any possible effect of the

MOCS control of the cochlear amplifier on the reception of the electrical stimuli.

Therefore, CI#4 has demonstrated a consistent and replicable formation of the filter in

this thesis. This finding supports the presence of an alternative mechanism that is able to

form the filter in some CI recipients. In contrast, participants CI#3 and CI#5

demonstrate a consistent absence of the filter in conditions with impaired MOCS action

on hearing, which is consistent with the MOCS role in the normal formation of the

attentional filter and previous research described above. However, with a combined

total of 6 CI recipients in chapters 5 and 6, further studies are needed to elucidate why

CI#4 was the only participant to consistently show the formation of the attentional filter.


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Chapter 7. General Discussion

General Discussion

149

The main aim of this thesis was to better understand the mechanisms that underlie the

formation of the attentional filter, with a focus on the role of the MOCS. The effect of

MOCS function on the formation of the attentional filter was measured in four sets of

experiments. The first set of experiments, in chapter 3, measured the effect of the

strength of the MOCS acoustic reflex using the suppression of OAEs in normal-hearing

participants. The second set of experiments, in chapter 4, investigated the effect of

reduced MOCS action on the cochlea in individuals with SNHL and no detectable

OAEs. The third and fourth sets of experiments measured the attentional filter in CI

recipients, as a group presumed to have no remaining MOCS action on the cochlea. In

CI recipients, the attentional filter was initially measured using acoustic presentation in

chapter 5, and then with programmed, direct stimulation in chapter 6. The findings of

the present thesis suggest a complex relationship between the MOCS and the attentional

filter, in which the typical formation of the attentional filter requires the normal function

of the MOCS action on the cochlea. However, the results also indicate the presence of

an alternative mechanism that is able to form the filter in some CI recipients, which

does not involve the MOCS efferent control of the cochlear amplifier.

In the normal hearing subjects of chapter 3, the strength of a single process of the

MOCS, the MOCS acoustic reflex, was measured using the suppression of OAEs by

contralateral broadband noise. This index of MOCS strength was then correlated with

the depth of the attentional filter. A positive correlation between the strength of the

MOCS acoustic reflex and the depth of the attentional filter would have supported a role

for the reflex in the filter‟s formation. No evidence for this relationship was found,

indeed, a stronger reflex correlated with reduced depth of the filter, and specifically

with a small elevation in the detection rate of the probes on the low-frequency side of

the filter. This result does not support a role for the MOCS acoustic reflex in forming

the attentional filter, although the absence of the expected relationship may have been

General Discussion

150

due to an unsuitable temporal separation between the OAE measurement and the

attentional filter measurement.

The index of the MOCS acoustic reflex‟s strength used in chapter 3 was measured on a

separate session to the measurement of the attentional filter, and this may limit the

index‟s suitability for assessing the MOCS role in forming the attentional filter. The

magnitude of OAE suppression by a contralateral broadband noise has been shown in

previous research to be altered by the task conditions used during the measurement,

which was first shown in a comparison between an auditory-task and a visual-task (Puel

et al., 1988). More relevant to conditions used to measure the attentional filter is

research that showed that the OAE suppression can be increased during a task that

requires focused auditory attention, and that this increase is located specifically at the

frequencies that are under focused attention (Maison et al., 2001). In addition, recent

research has suggested that OAE suppression associated with an auditory task alters

systematically with attention and experience in the task (de Boer and Thornton, 2008;

de Boer et al., 2012). Taken together, these studies suggest that a single measurement of

OAE suppression by contralateral broadband noise that is taken separately from the task

of interest may not be an appropriate measurement of MOCS activity during the task.

Indeed, the studies suggest that an effective measurement of MOCS activity may

require OAE suppression to be measured both during each session with the task

(Maison et al., 2001), as well as across multiple sessions as a subject trains with the task

(de Boer and Thornton, 2008). Therefore, the OAE suppression results in the present

work may not have captured the MOCS activity relevant to the system‟s role in forming

the attentional filter, if such activity exists.

Although the measurement of OAE suppression used in this thesis may not have been

appropriate to test the MOCS role in forming the filter, the measurement may be

informative of the effect of the MOCS acoustic reflex on the reception of near-threshold

General Discussion

151

tones in noise. The magnitude of DPOAE suppression showed consistent, although

weak, positive correlations with the detection rate of the probe tones on the low-

frequency side of the attentional filter, which suggests a role for the MOCS in

enhancing the detectability of transient tones in noise at specific frequencies. The

frequency-tuning of this enhancement is consistent with previous research that

measured the frequency-tuning of the MOCS acoustic reflex. This previous research

used stimulus frequency OAEs, a type of highly frequency specific OAE that uses a

single pure tone probe (Lilaonitkul and Guinan, 2009b, Lilaonitkul and Guinan, 2009a),

or spontaneous OAEs (Zhao and Dhar, 2012), and correlated the magnitude of OAE

suppression with the type and bandwidth of various MOCS elicitors. Lilaonitkul and

Guinan (2009a) demonstrated that the magnitude of OAE suppression elicited by a

narrow-band noise increased with the elicitor‟s bandwidth, and that broadband noise

was a highly effective MOCS elicitor. However, the suppression of the cochlear

amplifier elicited by the broadband noise was not uniform in magnitude across the

frequencies tested (Lilaonitkul and Guinan, 2009a). The maximum suppression of the

cochlear amplifier by broadband noise was located at 1 kHz; with the minimum

suppression located at 4 kHz (2 kHz was not tested). While this is a poor frequency

resolution, it suggests that the broadband noise used in the experiments of chapter 3

would maximally suppress the cochlear amplifier below the 2-kHz target frequency.

The increased suppression of the cochlear amplifier can lead to improvements in the

detectability of transient tones in noise by antimasking, in which the auditory system‟s

adaptation to a sustained noise is suppressed, which leads to an increase in dynamic

firing ranges and improvements in auditory thresholds (Winslow and Sachs, 1987;

Mulders and Robertson, 2000a). In the results of chapter 3, the increased detection rate

of the low-frequency probes is consistent with an antimasking effect, and this increase

occurred for probes located at the frequencies which would receive the maximum

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suppression by the MOCS acoustic reflex, at least as activated by broadband noise.

Thus, the positive correlation between the detection rates of the low-frequency probes

with DPOAE suppression may have been due to an antimasking benefit provided by the

activation of the MOCS by broadband noise.

It is important to note that the enhancement of the low-frequency probes was consistent

with the activation of the MOCS by the broadband noise, and not by the 2-kHz cue

tone. The studies listed above suggested that a pure tone MOCS elicitor at 2 kHz would

result in the maximum suppression of the cochlear amplifier at frequencies up to half an

octave higher than 2 kHz (Lilaonitkul and Guinan, 2009b). This frequency tuning

suggests that the activation of the reflex by the cue tone was not involved in the increase

in detection rates of the low-frequency probe tones. Any contribution of the cue tone to

changes in detection rates may not be included in the estimation of MOCS strength,

because the suppression of OAEs used to estimate the strength of the MOCS used

contralateral suppression in a separate task to the measurement of the attentional filter.

As discussed in the previous paragraph, the methods of chapter 3 were best placed to

capture the effects of tonic activation of the MOCS acoustic reflex by broadband noise,

as these were the conditions used to suppress the OAEs. Overall, the results of chapter 3

do not support a role for the MOCS acoustic reflex in forming the attentional filter,

although they are consistent with the reflex enhancing the detectability of near-threshold

tones in an unrelated manner.

In chapter 3 the index of MOCS function was limited to the action of the MOCS

acoustic reflex as activated by a contralateral broadband noise, and on a separate session

to the measurement of the attentional filter. This index may only include a subset of

MOCS action, and may not have captured the system‟s activity relating to its suggested

role in forming the attentional filter. In chapter 4 this concern was addressed, by

measuring the attentional filter in individuals with a presumed reduction in MOCS

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function due to a loss of the MOCs efferent targets, the OHCs, that was association with

SNHL and a loss of detectable OAEs. In these participants the MOCS action on the

cochlea is thought to be impaired, which would affect the actions of the MOCS as a

whole, rather than a subset of the system‟s action. Thus, the results of chapter 4 may be

more representative of the function of the MOCS as a whole, and will include any

effects of the system on the formation of the attentional filter.

The results of chapter 4 demonstrated reduced depth of the attentional filter with

increasing SNHL, and a complete loss of the filter in individuals with at least a

moderate SNHL. This reduction in filter depth, which was associated with impaired

MOCS function, is consistent with previous research into the filter‟s formation in

similar conditions (Scharf et al., 1994; Moore et al., 1996; Scharf et al., 1997), although

the relationship in the present work was more complex than expected, perhaps due to

the considerably larger sample size (n = 14 in the present work, n = 2 for Moore et al.

1996) and range of HLs included. This earlier research included individuals with either

a section of the MOCS efferent fibres that was presumed to be complete (Scharf et al.,

1997) or with a SNHL consistent with a total loss of the MOCS efferent targets (Moore

et al., 1996), and both studies demonstrated reductions in filter depth that were either

incomplete but generally symmetric, or showed a complete absence of the filter. In

contrast, the present results demonstrated an asymmetric reduction in filter depth as a

function of the magnitude of SNHL. The low-frequency side of the filter was found to

be highly sensitive to hearing loss, with this side of the filter reduced in depth at

subclinical hearing levels. On the other hand, the high-frequency side of the attentional

filter reduced in depth beginning with mild SNHL, and continued in a graded manner

with increasing hearing loss at levels of SNHL that are physiologically relevant to

reduced function of the MOCS efferent targets. This graded reduction in the depth of

the high-frequency side of the attentional filter, which occurred in line with presumed

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reduction of MOCS efferent target function, supports a role for the MOCS in the

generation of the filter.

In chapter 4 it was also shown that the low-frequency side of the attentional filter

reduced in depth with increasing HL in the normal hearing group. This was the same set

of participants that showed a reduction in the depth of the filter on its low-frequency

side with increasing DPOAE suppression in chapter 3. As discussed above, in chapter 3

the decrease in filter depth was attributed to an increase in the strength of the MOCS

acoustic reflex, as activated by broadband noise. Can this conclusion be reconciled with

the apparently similar relationship for decreasing filter depth with increasing HL? As

discussed in chapter 4, there was some evidence that the relationships were linked, with

a near-significant positive correlation between the magnitude of DPOAE suppression

and HL. This potential relationship may have been due to elevations in central auditory

system activity shown to occur after hearing loss, as a plastic response to the decreased

afferent input (Schaette and McAlpine, 2011; Hébert et al., 2013). The increased

activity may have subsequently increased the efferent drive of the MOCS through its

top-down inputs (Knudson et al., 2014), and caused a positive relationship between

subclinical hearing losses and the magnitude of DPOAE suppression. However, this is

an unsatisfying explanation for the reduction in depth of the low-frequency side of the

attentional filter, as this impairment remained through-out the SNHL group, who were

likely to have significant impairments to MOCS action on the cochlea. Instead, the loss

of the low-frequency side of the filter may have been due to an auditory neuropathy

associated with hidden hearing losses (Kujawa and Liberman, 2009; Schaette and

McAlpine, 2011), which are selective for the fibres that form the afferent input to the

MOCS (Furman et al., 2013). This reduction in MOCS afferent drive may have

eliminated the formation of the low-frequency side of the attentional filter, and explains

the initial loss with subclinical hearing losses, and continued absence of the low-

General Discussion

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frequency side of the filter with SNHL. However, the present work does not include a

measurement of central auditory structure activity, or a sensitive measurement of

auditory neuropathy, and so this interpretation remains speculative.

Overall, chapter 4 presents an argument that the attentional filter is at least partially

formed by MOCS action on the cochlea, as the filter reduced in depth at HLs that are

physiologically relevant to reduced function of the MOCS efferent targets. The

progressive loss of the high-frequency side of the attentional filter with increasing HL

has not been previously reported. Similarly, the loss of the low-frequency side of the

attentional filter at subclinical hearing levels has not been previously reported, and

demonstrates a sensitivity to hearing loss that may have negative effects on an

individual‟s ability to process signals in noise before a clinical level of hearing loss is

reached.

The results of Chapter 4, and the conclusions drawn from them, rely on presumed

impairments to the MOCS due to the loss or damage of its efferent targets, for which no

direct measurement could be made. While a SNHL and the loss of detectable OAEs is

strongly associated with impairment to OHC function (Abdala, 2000, Kim et al., 1996),

the loss of OAEs cannot be used to grade the severity of this impairment. Otoacoustic

emissions are lost with a relatively small impairment to OHC function (Attias et al.,

1995, Kim et al., 1996). Thus, an increasing impairment to MOCS function must be

inferred from the increasing SNHL, a conclusion which is supported by research that

shows that the percentage of damaged or lost OHCs increases with increasing hearing

loss, at least in guinea pigs (Stebbins et al., 1979; Hamernik et al., 1989). However,

SNHL can also be caused by the loss or damage of IHCs or auditory neuropathy, neither

of which would directly reduce MOCS action on the cochlea. The present work also has

no direct or indirect measurements of how IHC damage or auditory neuropathy may

have contributed to each individual‟s hearing loss. Therefore, while a SNHL and a loss

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of detectable OAEs is associated with reduced MOCS function, and this reduction is

likely to scale with increasing hearing impairment, it is possible that other causes of

SNHL were present that have no relationship with MOCS function. This potential issue

was addressed in chapters 5 and 6, by measuring the attentional filter in individuals in

whom MOCS action on the cochlea was presumed to be impossible, rather than

suffering a degree of impairment.

In chapter 5 the attentional filter was measured in six CI recipients using acoustic

presentation to a commercial CP810 speech processor. The CI recipients had profound

SNHL prior to implantation, and so would not be expected to have a significant inner or

outer hair cell function remaining (Stebbins et al., 1979; Hamernik et al., 1989). In

addition to the presumed loss of hair cell function, the acoustic stimuli were presented at

an amplitude that was within 12 dB of a normal hearing listener‟s threshold, and so

would be too quiet to be affect any remaining OHC function in the severe to profoundly

deafened CI recipients. The attentional filter was measured using comparisons between

detection rates in an equal-likelihood condition, in which the to-be-detected tones were

presented with equal probability, and in an attentional filter condition, which used a

75% presentation rate of the target tone. To support the presence of the attention filter,

there would have to be a clear preference for the target tone that occurred only in the

attentional filter condition, which was demonstrated in a group of normal hearing

individuals. The results showed five of six CI recipients did not detect the target at a

higher rate in only the attentional filter condition, which demonstrates an inability to

bias sensitivity towards specific frequencies based on the history of occurrence, and

suggests a total loss of the attentional filter. The majority of CI recipients, therefore,

showed a result consistent with the results of chapter 4, with the loss of the attentional

filter in a condition presumed to remove possible MOCS action on the cochlea.

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In contrast to the apparent absence of the filter in five of the six tested CI recipients,

CI#4 showed a clear enhancement of the detection rate of the target above the probes

that was only present in the attentional filter condition, and not the equal-likelihood

condition. Thus, CI#4 satisfied both conditions required to support the presence of the

attentional filter, and this occurred in an individual presumed to have no remaining

MOCS action on the cochlea. This result suggests the existence of an alternative

mechanism, which does not involve the MOCS control of the cochlear amplifier, and is

able to form the attentional filter in at least one CI recipient.

The validity of the results in chapter 5 may be limited due to the use of acoustic

presentation to a commercial speech processor. While every effort was made to disable

the speech processor‟s noise processing strategies (such as Adaptive Dynamic Range

Optimization and AutoSensitivity Control), the processor introduces unknowns which

may have caused or prevented the formation of the attentional filters in chapter 5.

The experiments described in chapter 6 eliminated the potentially unwanted effects of

the speech processor by using programmed, direct stimulation. This programmed, direct

stimulation did not use an acoustic stimulus, which ensures that there would be no way

for the MOCS efferent control of the cochlear amplifier to influence the reception of the

target and probes. The results showed a lack of formation of the attentional filter in two

out of four CI recipients, CI#3 and CI#5, who had shown the absence of the filter in

chapter 5. However, CI#2 and CI#4 had significantly increased detection rates of the

target stimulus over the probe tones. Importantly, the increased detection rate of the

target stimulus was repeated when the target electrode was shifted from electrode 11 to

electrode 14 in both of these CI recipients. These results support those of chapter 5, with

the loss of the attentional filter in some CI recipients, but there was evidence for the

formation of the filter in others. CI#4 in particular, demonstrated the consistent,

replicable formation of the attentional filter in every relevant test of the present work.

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Thus, the results of chapter 6 support the loss of the attentional filter in conditions of

impaired MOCS action on hearing; however, there is additional support for an

alternative mechanism that is able to form the filter in some CI recipients.

The alternative mechanism responsible for the formation of the attentional filter in CI#4

may be located in central auditory structures. Moore et al. (1996) suggested that

template-matching in central auditory structures aids in the formation of the attentional

filter, based on earlier work by Dau et al. (1996) which has been recently updated

(Jepsen and Dau, 2011). A role for central template-matching in, at least partially,

forming the attentional filter is consistent with the filter‟s formation in response to

complex cues. Previous research has demonstrated the filter‟s formation in response to

cues that require complex frequency extraction (Ebata et al., 2001), harmonic

complexes, or even when the cue was imagined (Borra et al., 2013). The formation of

the attentional filter in response to complex cues may rely on the production of an

effective template in central auditory structures. Template-matching may by the method

used by some of the individuals with sectioned MOCS efferent fibres to form partial

attentional filters in Scharf et al.‟s vestibular neurectomy studies (1994, 1997).

However, if a template-matching mechanism is able to form the attentional filter, it is

unclear why CI#4 was able to use this mechanism, but the other five CI recipients were

not, and it is unclear why the mechanism was not engaged in the SNHL participants

included in chapter 4. Recent research has demonstrated that the model proposed by

Dau et al. (1996) is still unable to successfully predict the deficits in signal-in-noise

detection in some SNHL participants, and it may be that an impaired template-matching

ability is involved in this deficit (Jepsen and Dau, 2011).

What conclusions can be made on the overarching research question, on whether the

MOCS is responsible for the formation of the attentional filter? The attentional filter

was reduced in depth in individuals with SNHL, and was not present in the majority of

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CI recipients, which supports and extends previous research that demonstrates the

dependence of the attentional filter on the normal function of MOCS action on hearing.

These findings are consistent with a major role for the MOCS in forming the attentional

filter, as there is evidence of a complete loss of the filter with a presumed complete loss

of MOCS action on the cochlea. However, the constant requirement for presumed loss

of MOCS action on the cochlea, both in the present work and in previous research due

to the lack of a direct measurement of the function of the MOCS, requires a cautious

interpretation of the results. In addition, the failure to demonstrate a connection between

the normal function of the MOCS and the formation of the attentional filter in the

normal hearing individuals of chapter 3 prevents a stronger conclusion for the role of

the MOCS in forming the filter. Finally, the consistent, replicable formation of the filter

in CI#4 demonstrates the presence of an alternative mechanism that is able to form the

attentional filter, but it unrelated to the MOCS efferent control of the cochlear amplifier.

Nonetheless, some aspects of the present work are consistent with a role for the MOCS

in the normal formation of the attentional filter.

7.1 Implications & Future Directions

The present thesis provides some support for the involvement of the MOCS in the

formation of the attentional filter, with evidence of an additional mechanism that is

unrelated to the MOCS‟ efferent output. There are three major research questions still to

be addressed, which are pertinent to the main research question, as well as the

implications raised by the results of the thesis. First is the formation of the attentional

filter in normal hearing individuals, both in relation to the absence of the expected

positive relationship between the estimated strength of the MOCS and the depth of the

filter, as well as the apparent deficits in filter depth with subclinical elevations in

auditory thresholds. Second is the apparent deficit in the attentional filter in the two

individuals with a clinically-pure conductive hearing loss in chapter 4. Third is the

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suggestion of an alternative mechanism that was able to form the attentional filter in at

least one CI recipient in chapters 5 and 6.

7.1.1 Formation of the filter in normal hearing individuals

In chapter 3, the effect of MOCS strength on the depth of the attentional filter was

measured using the suppression of OAEs in a separate session to the measurement of

the attentional filter. This measurement of the strength of the MOCS acoustic reflex

may have been inappropriate to test the system‟s suggested relationship with the

attentional filter due to the temporal separation between the measurement of OAE

suppression and that of the attentional filter. As discussed earlier, research has

demonstrated substantial changes in the magnitude of OAE suppression depending on

the task conditions and throughout training with a single task (Puel et al., 1988; Maison

et al., 2001; de Boer and Thornton, 2008), and so the MOCS action relevant to the

measure of the attentional filter may not have been measured in the experiments of

chapter 3. Further research must include the potentially task-relevant top-down MOCS

action, by eliminating the temporal separation between the measurement of OAE

suppression and the attentional filter. Ideally, this would take place using a

measurement of OAE suppression that occurred during the attentional filter task,

although this task would have to overcome the standard use of continuous broadband

noise during the attentional filter measurements.

The results of chapter 3 revealed substantial variations in the depth of the attentional

filter in the normal hearing group, although this variation was not substantially different

from that reported in the first study of the attentional filter (Greenberg and Larkin,

1968). In chapter 4 it was shown that the variation in the present work was better

explained by hearing loss rather than OAE suppression. Thus, subclinical elevations in

hearing levels may represent an important confounding factor when measuring the

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effect of MOCS strength on the filter, and further research into the formation of the

attentional filter in normal hearing individuals must control for slight hearing losses.

Importantly, elevations in pure-tone audiometric thresholds may not be a sufficient

indicator for these hearing losses. As discussed in chapter 4, these levels of hearing loss

are not associated with appreciable losses of function of the MOCS efferent targets, but

may instead be associated with „hidden‟ hearing losses that have been linked with

auditory neuropathy (Kujawa and Liberman, 2009). No sensitive measurement of

auditory neuropathy was included in the present work. Future work could employ the

evoked auditory brainstem response as a sensitive measurement of auditory neuropathy.

A strong correlation between the magnitude of the auditory brainstem response and the

population of surviving auditory nerve fibres has been demonstrated in animal models

(Goldstein and Kiang, 1958; Hall, 1990). On the basis of this animal research, the

brainstem response has been used in humans to estimate the surviving population of

spiral ganglion neurons (Fifer and Novak, 1991); however the relationship between the

response magnitude and the surviving neuronal population has not been directly

confirmed in humans (Miller et al., 2008). In support of the proposed relationship, the

auditory brainstem response has been successfully used to predict CI outcomes (e.g.

(Walton et al., 2008)), and it is known that these outcomes are heavily influenced by

surviving spiral ganglion neuron counts (Khan et al., 2005). Recent studies have

proposed a rapid testing procedure to measure the response in humans (Bharadwaj and

Shinn-Cunningham, 2014), and this measure has been used to correlate the estimate of

„hidden‟ hearing loss with various auditory performance measures, such as detection

thresholds for frequency-modulated tones in noise (Bharadwaj et al., 2014). Therefore,

the auditory brainstem response may be used to test for hearing impairment that would

not be detected with pure-tone audiometry, and could then be used to control for

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potential auditory neuropathy prior to experiments that aim to correlate OAE

suppression with features of the attentional filter.

The deficit in the attentional filter that was identified in individuals with normal hearing

indicates a diminished ability to bias auditory sensitivity towards expected or cued

signals in noise. This may result in an elevation of speech reception thresholds in noise

in individuals with clinically normal hearing. Presently, speech reception thresholds in

noise have not been correlated with elevations in subclinical hearing levels, nor with

direct measurements of hidden hearing losses that may be related to these impairments,

such as the evoked brainstem response discussed above. However, previous research

has indirectly linked impaired speech reception in noise thresholds in individuals who

would be expected to have subclinical elevations in HL or hidden hearing losses. These

hearing impairments are associated with temporary threshold shifts brought on by noise

exposure (Alvord, 1983; Kujawa and Liberman, 2009). Previous research has shown

that human subjects with a history of noise exposure, but with normal pure-tone

thresholds, do have the predicted deficit in speech reception thresholds in noise when

compared with individuals with the same pure-tone thresholds but no history of noise

exposure (Alvord, 1983; Kujala et al., 2004; Kumar et al., 2012). It is currently unclear

whether the impairment of the attentional filter plays a role in these deficits, or whether

they are due more simply to the reduction in afferent input associated with auditory

neuropathy. Future work could link auditory neuropathy in individuals with normal

pure-tone thresholds, using the evoked auditory brainstem response, discussed above,

with a reduction in the depth of the attentional filter, and then correlate the impairment

of the attentional filter with any deficits in speech reception in noise. This would first

identify whether the attentional filter is impaired specifically by the auditory neuropathy

associated with hidden hearing losses, and second, quantify the effects of impairment to

the attentional filter on speech reception in noise thresholds.

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7.1.2 Formation of the attentional filter with conductive hearing loss

An important follow up to the present work is a measurement of the attentional filter in

a larger sample of individuals with conductive hearing loss. Chapter 4 included a

measurement of the filter in two individuals with a clinically pure conductive hearing

loss, however there was a subclinical sensorineural component to their hearing loss that

may have contributed to their apparent lack of the attentional filter. The absence of the

filter in the conductive hearing loss participants is significant, as it suggests that hearing

loss alone can eliminate the formation of the attentional filter. This might indicate that

the loss of the attentional filter in the SNHL participants was due to hearing loss, rather

than a specific impairment to the MOCS efferent targets. Only two conductive hearing

loss participants were included in the present work, as the recruitment of individuals

with a pure conductive hearing loss and no sensorineural component to this loss was

difficult. While a large number of individuals with appropriate conductive hearing

losses were contacted, there was an extremely low rate of reply. It was speculated that

this unwillingness to attend the research was prompted by the restoration of near-normal

auditory perception by a hearing aid that is possible with a conductive hearing loss, but

individuals with SNHL still suffer considerable difficulties in noisy environments (Hol

et al., 2004). If this is correct, and the conductive hearing loss individuals who refused

to attend the research have effectively normal hearing, then there is a greater issue of

selection bias for the two conductive hearing loss participants who attended the

research, as these participants were not able to form the attentional filter and so may be

expected to have difficulty hearing in noise. Still, whether the attentional filter is

impaired by a general hearing loss, rather than a specific impairment to the MOCS

efferent targets is a significant question.

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7.1.3 An alternative mechanism able to form the attentional filter

The implications for the hearing impaired group, both for individuals with mild SNHL

up to profound SNHL and those with a cochlear implant, rest on the apparent formation

of the attentional filter in an individual presumed to have no possible MOCS efferent

action on hearing. This result suggests the presence of an alternative mechanism that is

able to form a typical attentional filter in individuals with reduced MOCS action on

hearing. Presently, the source of this alternative mechanism is not known, but there is

no clear reason to suspect that CI#4, who showed the filter, is unique among all

individuals with reduced MOCS action on hearing in possessing the alternative

mechanism. Thus, depending on the mechanism, it may be possible to activate or train

the alternative mechanism to form the attentional filter, at least in some individuals.

This may be significant, as speech reception thresholds in noise are impaired in

individuals with even a mild SNHL, and considerably impaired in CI recipients. The

formation of the attentional filter represents an ability to bias sensitivity towards certain

frequencies, such as the frequency components of a speaker‟s voice, and away from

unwanted noise that may distract from attending to the speaker. Therefore, the

formation of the attentional filter may improve speech reception thresholds in noise, and

the identification of the alternative mechanism may enable a method for improving

speech reception thresholds in some hearing impaired individuals.

In chapter 6 it was suggested that a central, template-matching, or perceptual object

encoding mechanism may have been an alternative mechanism able to form the

attentional filter. The focus of the present work was the efferent control of peripheral

auditory structures, as a potential source of the attentional filter. However, there is a

great deal of auditory processing in central auditory structures, which forms the basis of

auditory scene analysis (Bregman, 1990), which this thesis has not directly addressed. It

is likely that this central processing has a role in forming the attentional filter in

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normally hearing individuals, for example recent research has demonstrated a benefit

from an informative speech cue on following a single speaker with competing speech

signals (Woods and McDermott, 2015), and these mechanisms, particularly stream

segregation (Noorden, 1975; Moore and Gockel, 2012), may be involved in forming the

filter in the absence of MOCS action on the cochlea. Indeed, the presence of the

attentional filter in individuals with cochlear implants strongly suggests that central

auditory structures can form the entirety of the attentional filter in certain conditions.

7.2 Conclusions

The expected relationship for increasing depth of the attentional filter with increasing

strength of the MOCS was not found. Instead, a consistent finding was that even small

reductions in auditory sensitivity reduce the formation of the attentional filter. In

participants with SNHL, the filter reduced in depth at levels of hearing loss that are

associated with a loss of the function of the MOCS efferent targets, which supports the

notion that the MOCS in involved in the formation of the filter. However, there was a

reduction in the depth of the filter even in normal hearing individuals at subclinical

levels of hearing loss, and it is unclear whether this reduction in depth is associated with

MOCS action. Finally, the formation of the attentional filter in at least one cochlear

implant recipient demonstrates that the attentional filter can be formed with a restoration

of auditory sensitivity, even with a complete absence of MOCS action on the cochlea.

This result strongly suggests the presence of central mechanisms in the formation of the

attentional filter, however it is unclear why this restoration of the filter was only present

in cochlear implant recipients, and not in individuals with aided SNHL, nor is it clear to

what degree these central mechanisms may be involved in the filter‟s formation in

normal hearing individuals.

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Appendix

Chapter 8. Appendix

8.1 Depth of the attentional filter as a function of OAE suppression

In chapter 3 the detection rates of the target and probes were correlated with both

TEOAE suppression and DPOAE suppression. Below, instead of the detection rates of

the target and probes, OAE suppression is correlated with the depth of the attentional

filter as measured by subtracting each probes‟ detection rate from the target detection

rate.

8.1.1 TEOAE suppression

The relationships between the depth of the attentional filter at each probe frequency,

calculated by subtracting the mean of each probe‟s detection rate from the mean target

detection rate, is shown in Figure 8.1. Slight trends for increasing filter depth at the

distant probe frequencies existed, however these trends did not near significance, as

shown in Table 8.1.

Appendix

176

Figure 8.1. The relationship between the suppression of TEOAEs and the depth of the

attentional filter at each of the probes (N = 14).

Table 8.1. The correlation coefficients and associated statistics for the detection rate of

the target and probes as a function of the suppression of TEOAEs (N = 14). No

correction for multiple comparisons was made.

r 95% CI

1.8-kHz probe .02 (-.72, .26)

1.92-kHz probe .26 (-.32, .69)

2.08-kHz probe .01 (-.31, .70)

2.2-kHz probe .30 (-.72, .26)

Appendix

8.1.2 DPOAE suppression

The relationship between the depth of the each of the probes tones relative to the target

as a function of the suppression of the L1 = 55 dB DPOAEs, and from 13 participants

for the suppression of the L1 = 55 dB DPOAEs in Figure 8.2A-B, with the statistics of

the relationships shown in Table 8.2. No significant correlations were present.

Figure 8.2. A, the relationship between the suppression of the L1 = 45 dB DPOAEs and

the detection rate of the target and probes. B, the same relationship for the suppression

of L1 = 55 dB DPOAEs. (N = 13 for L1 = 45 dB DPOAEs, n = 15 for L1 = 55 dB

DPOAEs).

Appendix

178


between the detection rate of the target and probes and the suppression of the L1 = 45

dB, and L1 = 55 dB DPOAEs (N = 13 for L1 = 45 dB DPOAEs, n = 15 for L1 = 55 dB

DPOAEs).

L1 r 95% CI

1.8-kHz probe 45 .28 (-.31, .72)

55 -.01 (-.52, .50)

1.92-kHz probe 45 .29 (-.31, .73)

55 .26 (-.29, .68)

2.08-kHz probe 45 .14 (-.64, .44)

55 .01 (-.50, .52)

2.2-kHz probe 45 .44 (-.80, .14)

55 -.29 (-.70, .26)

Appendix

Figure 8.3. Frequency allocation table (FAT) for Cochlear™ implants. This table shows

the default frequency ranges that, after being received and processed by the speech

processor, are allocated to each electrode along the implanted electrode array. The

values shown are the defaults, and they can be modified to suit individual cochlear

implant recipients. The implant recipients included in chapters 5 and 6 all used these

default values. Taken from a screenshot of the Cochlear™ implant program. UF: Upper

frequency. LF: Lower frequency. BW: Bandwidth. AE: Active electrode. SM/IE:

Simulation mode.

Appendix

180

Figure 8.4. Companion figure to Figure 4.1, showing the audiograms for the ears with

worse thresholds at 2 kHz for the SNHL group. This includes air conduction thresholds

(solid lines) and bone conduction thresholds (dashed lines).

Documents

Mechanisms of auditory attention in normal and hearing impaired listeners