Comparison of central masking versus monotic masking in non-simultaneous masking conditions

CENTRAL VERSUS MONOTIC MASKING IN NON-SIMULTANEOUS MASKING

CONDITIONS

DISSERTATION

Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy

in the Graduate School of The Ohio State University

By

Mahnaz Ahmadi

Graduate Program in Speech and Hearing Science

The Ohio State University

2010

Dissertation Committee:

Lawrence L. Feth, Advisor

Robert A. Fox

Kamran Barin

Copyright by

Mahnaz Ahmadi

2010

ii

ABSTRACT

Evidence based on physiological and psychophysical data suggests that the

efferent system, especially the medial olivocochlear bundle (MOCB), has a role in

protecting the auditory system from damaging sounds. It is also assumed that this system

may improve the detection of sound in noise, which in turn improves speech

intelligibility in noisy environments. Some have hypothesized that central masking is

mediated via the MOCB. Indeed, this notion is supported by the central masking effect

measured in psychoacoustic studies on animals. It has been demonstrated that central

masking was reduced, or eliminated when the MOCB was sectioned at the floor of the

fourth ventricle in macaque monkeys (Smith et al., 2000).

In a normal conversational environment, a listener is exposed to various acoustic

stimuli which are fluctuating in the time domain. These fluctuations do not occur

simultaneously. The time disparity between the signal and the noise will affect a

listener’s ability to detect a signal in a noisy environment. This effect can be studied in a

non-simultaneous masking paradigm. Comparing non-simultaneous central masking to

monotic masking may show the MOCB influence on our ability to detect a signal in

noise. The purpose of the present study was to compare the amount of masking as a

function of signal-to-noise time delay in dichotic versus monotic masking conditions.

Another aim was to compare on-frequency versus off-frequency masking, for forward

monotic and dichotic listening in time intervals of 0, 5, and 20 ms.

iii

Detection thresholds of four normal adult listeners were measured utilizing a

2AFC up-down adaptive-tracking procedure. Signal-to-masker time intervals were 0, 2,

5, 10, 20, and 50 ms. Brief sinusoidal signals at 0.5, 1, 2, and 4 kHz were masked by a

two-octave band of noise of 200 ms duration. The psychoacoustic study was conducted

running a computer based program coded in MATLAB, utilizing the psychoacoustic

software PsyLab 2.1. The masker was centered on and off the frequency of the signal.

The hearing thresholds were obtained in quiet and with ipsilateral and contralateral

maskers separately. Then, the hearing thresholds with noise were subtracted from the

threshold in quiet. This value represented the threshold shift and was used for further

statistical analysis.

The amount of masking decreased as a function of time interval in both monotic

and dichotic conditions. A non-simultaneous masking effect existed in shorter time

intervals. Backward central masking did not occur, even in the shortest intervals. High

frequency signals produced more central masking than low frequencies. However, signals

with lower frequencies were more effective in monotic masking. Central masking did not

clearly occur with an off-frequency masker in both simultaneous and non-simultaneous

masking conditions. The rate of growth of central masking was noticeably slower than

monotic masking for on-frequency maskers. Results of this study were consistent with

neurophysiologic findings on MOCB response characteristics, and also with

psychophysical findings in central masking. The present findings supported the idea that

central masking, either in simultaneous or non-simultaneous masking conditions, is

mediated by efferent fibers in humans.

iv

Dedicated to my parents, Parvindokht and Zolfaghar, and my brother, Ali, who instill in

me a love and appreciation of learning and their inspirations and support were main

reasons for all of my achievements.

v

ACKNOWLEDGMENTS

My deep gratitude goes to my advisor, Dr. Lawrence Feth, for his guidance

throughout the past few years. His profound knowledge in psychoacoustics shed more

light on my dissertation path, and his invaluable advice helped me clarify my ideas and

move to a more realistic and feasible project.

I also wish to thank Drs. Robert Fox, Kamran Barin, and Christina Roup for their

advice through various stages of my PhD education, especially during my Candidacy

exam and research proposal. They provided invaluable and timely feedback on my exam,

and helped to make it a wonderful learning event for me.

I am very grateful to Dr. Robert Fox, chair of the Department of Speech and

Hearing Science and my research supervisor, for providing me with the opportunity to

gain tremendous experience in the Speech Perception and Acoustics Labs. My sincere

thanks also go to Dr. Ewa Jacewicz, my research supervisor, for her continuous support

and priceless encouragement during my doctoral education.

Several people must be acknowledged for their continuous support during the

intense adventure of completing my dissertation. I am deeply grateful to Mohammad

Shakiba for his extraordinary support in coding the needed program. I would like to thank

to Dr. Evelyn Hoglund for her assistance and responsiveness to my information needs. I

vi

am also grateful to Jason Johnson and Yong Hee Oh for their excellent technological

support. I would like to thank all the individuals who participated in my research. My

research task would have been much more difficult without their superb listening skills

and their patience. Thanks are also due to John Acker for his invaluable editorial

feedback throughout my dissertation.

Special thanks go to my fellow research assistants and doctoral students at the

Department of Speech and Hearing Science who are traveling the doctoral road after me,

and who both listened and provided encouragement during tough moments.

Finally, I would like to thank to my family for their patience, support and

encouragements throughout my education.

vii

VITA

1985 ..................................... Apadana High School, Tehran, Iran

1991 .................................... B.Sc. Audiology, Iran University of Medical Sciences

1996 .................................... M.Sc. Audiology, Tehran University of Medical Sciences

1997 – 2005 ......................... Lecturer, Tehran University of Medical Sciences

2005 – present .................... Graduate Teaching and Research Associate,

Department of Speech and Hearing Sciences, The Ohio

State University

Publications

Abolfazli, R., Mokari, N., Bagheri, H., Ahmadi, M. (2004). “A study on the reliability of

Competing Sentence Test in patients with CVA”, J. College Med. Tehran Univ. Med. Sc., 2, 149-

156.

Ahmadi,M., Modarresi,Y, Erber, N.P., (2002). “Developing a speech perception test in

Farsi for 6 to 7 years old hearing-impaired children”, Kavosh in Audiology, 1,45-50,

Fields of Study

Major Field: Speech and Hearing Science.

viii

TABLE OF CONTENTS

Abstract .......................................................................................................................ii

Acknowledgments .......................................................................................................v

Vita ...........................................................................................................................vii

List of Tables ..............................................................................................................xi

List of Figures ..........................................................................................................xiii

Chapter 1: Introduction.................................................................................................1

1.1 Masking: Definition and Measuring Techniques ...............................................1

1.2 Central vs. Peripheral Masking ..........................................................................2

1.3 Importance and Objectives of the Study ............................................................4

Chapter 2: Literature Review ........................................................................................7

2.1 Efferent Fibers Classification ............................................................................8

2.2 Roles of the Efferent System in Hearing.............................................................9

2.2.1 Protection ................................................................................................10

2.2.2 Enhancement............................................................................................11

2.2.3 Improving Selective Attention..................................................................14

2.3 Methods of Studying Efferent System Activation in Humans ..........................16

2.4 Central Masking ..............................................................................................18

2.4.1 Psychophysical Results of Central Making Obtained with Normal Hearing

Listeners .........................................................................................................21

ix

2.4.1.1 Effects of Masker Onset and Duration ..............................................23

2.4.1.2 Effects of Masker Level....................................................................24

2.4.1.3 Effects of Signal Frequency and Noise Bandwidth ...........................25

2.4.2 Mechanisms Underlying Central Masking ...............................................28

2.5 Non-simultaneous Masking .............................................................................31

2.5.1 Psychophysical Results Obtained in Non-simultaneous Masking

Paradigm ..........................................................................................................32

2.5.1.1 Effects of Frequency.........................................................................32

2.5.1.2 Effects of Time interval ....................................................................35

2.5.1.3 Effects of Masker Bandwidth ...........................................................37

2.5.1.4 Effects of Duration of Stimuli...........................................................38

2.5.2 Mechanisms and Models Account for Non-simultaneous Masking ...........40

2.6 Non-simultaneous Central Masking Experiment ..............................................44

2.7 Summary ........................................................................................................45

Chapter 3: Experimental Methods ..............................................................................48

3.1 Introduction ....................................................................................................48

3.2 Variables .........................................................................................................49

3.3 Listeners .........................................................................................................50

3.4 Acoustic Stimuli and Tests Protocol ................................................................51

3.5 Psychoacoustical Procedure .............................................................................54

Chapter 4: Results.......................................................................................................56

4.1 Monotic Masking Findings Compare to Previous Study ..................................56

x

4.2 Effect of Signal-to-Noise Time Interval on Detection Threshold .....................57

4.3 Effect of Signal Frequency on Detection Threshold .........................................64

4.4 Monotic and Dichotic Masking in On- and Off-Frequency Masking

Conditions ............................................................................................................67

4.5 Summary of Results ........................................................................................72

Chapter 5: Discussion ................................................................................................75

5.1 General Discussion .........................................................................................75

5.1.1 Effects of Time Interval and Signal Frequency ........................................77

5.1.2 On-frequency versus Off-frequency Masking ..........................................81

5.2 Conclusions ....................................................................................................85

5.3 Implications for Future Research......................................................................86

List of References ......................................................................................................88

Appendix A: Individual Audiometric and Immittance Audiometric Results ............. 107

Appendix B: Individual Data for Threshold Shift as a Function of Time Interval .... 110

Appendix C: Average Data for Threshold Shift as a Function of Time Interval ....... 115

Appendix D: Individual Data for Growth of Masking with On-frequency and Off-

frequency Maskers.................................................................................................... 119

Appendix E: Average Data for Growth of Masking with On-frequency and Off-frequency

Maskers .................................................................................................................... 122

xi

LIST OF TABLES

Table 4.1 Pearson’s r for masking conditions and time intervals ....................................70

Table A.1 Audiometric and Immittance Audiometric Results for Subject 1..................108




Table C.1: Mean, standard deviation, and standard error of the data in simultaneous

masking condition .......................................................................................................116

Table C.2: Mean, standard deviation, and standard error of the data for 500 Hz signal

frequency in forward masking condition ......................................................................116


frequency in backward masking condition ...................................................................116





xii









Table E.1: Mean, standard deviation, and standard error of the data for monotic on- and

off-frequency masking condition in 0 ms ∆t.................................................................123




off-frequency masking condition in 20 ms ∆t...............................................................124

Table E.4: Mean, standard deviation, and standard error of the data for dichotic on- and





off-frequency masking condition in 20 ms ∆t...............................................................125

xiii

LIST OF FIGURES

Figure 2.1 Frequency distribution of Central Masking at Various Masker Intensity Levels

Obtained in Normal Hearing Listeners........................................................................26

Figure 2.2 Results of Monotic Backward and Forward Masking as a Function of Time

Interval and Frequency of theSsignal ..........................................................................35

Figure 2.3 Results of Dichotic Backward and Forward Masking as a Function of Time

Interval and Frequency of the Signal...........................................................................36

Figure 3.1 Schematic Diagram of Simultaneous and Forward Masking Conditions .....53

Figure 3.2 Schematic Diagram of Simultaneous and Backward Masking Conditions ..53

Figure 4.1 Forward versus Backward Monotic Masking .............................................57

Figure 4.2 Threshold shift as a Function of Masker Level for the Monotic Masking

Condition. ..................................................................................................................59

Figure 4.3 Threshold shift as a Function of Masker Level for the Dichotic Masking

Condition....................................................................................................................60

Figure 4.4: Threshold Shift as a Function of Time Interval at 500 Hz..........................61

Figure 4.5: Threshold Shift as a Function of Fime Interval at 1000 Hz........................62

Figure 4.6: Threshold Shift as a Function of Time Interval at 2000 Hz........................63

Figure 4.7: Threshold Shift as a Function of Time Interval at 4000 Hz........................64

Figure 4.8: Threshold Shift in Simultaneous Monotic and Dichotic Masking Condition at

Various Signal Frequencies ........................................................................................65

xiv

Figure 4.9: Threshold Shift as a Function of Masker Level for On-frequency and Off-

Frequency Monotic Masking Condition......................................................................68

Figure 4.10: Threshold Shift as a Function of Masker Level for On-frequency and Off-

frequency Dichotic Masking Condition.......................................................................69

Figure 4.11: Threshold Shift as a Function of Masker Level for Monotic On-frequency

and Off-frequency Masking Conditions ......................................................................71

Figure 4.12: Threshold Shift as a Function of Masker Level for Dichotic On-frequency

and Off-frequency Masking Conditions ......................................................................71

Figure B1: Threshold Shift as a Function of Time Interval for Monotic Masking for

Subject 1 .................................................................................................................. 111

Figure B2: Threshold Shift as a Function of Time Interval for Dichotic Masking for

Subject 1 .................................................................................................................. 111


Subject 2 .................................................................................................................. 112


Subject 2 .................................................................................................................. 112


Subject 3 .................................................................................................................. 113


Subject 3 .................................................................................................................. 113


Subject 4 .................................................................................................................. 114

xv


Subject 4 .................................................................................................................. 114

Figure D1: Growth of Masking with On-frequency and Off-frequency Maskers for

Subject 1................................................................................................................... 120


Subject 2................................................................................................................... 120


Subject 3................................................................................................................... 121


Subject 4................................................................................................................... 121

1

CHAPTER 1: INTRODUCTION

1.1 Masking: Definition and Measuring Techniques

Auditory sensitivity for an acoustic signal may be reduced by the presence of

another sound. This phenomenon, called masking, is one of the primary concepts in

psychoacoustics. Masking also refers to the amount in decibels (dB) by which the hearing

threshold is raised by the presence of another sound. In psychoacoustic experiments, the

test stimulus is called a probe or signal and the word masker is used to denote the sound

that infers with detection of the signal.

The method of measuring a threshold shift by the presence of a masker is very

straightforward. First the detection threshold of the signal is determined in quiet (without

the masker). This threshold is considered as the baseline for further evaluations. Next, the

masker is presented either to the same ear (ipsilateral) or to the opposite ear

(contralateral). Then, the threshold for the signal is determined again. The threshold

shift, which may also be considered as the amount of masking, is described as the

difference in decibels between the signal threshold in quiet and the masked threshold.

Various listening conditions may produce different amounts of masking for a particular

signal and a certain masker. Two listening conditions, known as monotic and dichotic, are

generally used in masking experiments. In monotic listening, both the masker and the

signal are presented to the same ear. By contrast, dichotic listening represents the

listening condition where the signal is presented to one ear and the masker to the opposite

2

ear. The amount of masking obtained in these two listening conditions is typically

different. Evidence has shown that the amount of masking is greater when utilizing a

monotic technique (e.g. Elliot, 1962a). The amount of masking is also measured for

either simultaneous or non-simultaneous paradigms. Simultaneous masking refers to a

situation in which the signal and the masker are presented at the same time. Non-

simultaneous masking, however, indicates situations where a signal is presented either

after the masker offset or before the masker onset. The former phenomenon is called

forward masking (e.g., De Maré, 1940; Lüscher and Zwislocki, 1947) and the later is

called backward masking (e.g., Miller, 1947; Samoilova, 1959; Pickett, 1959). Other

terminologies have been used for non-simultaneous masking paradigms, such as “residual

masking” and “post-stimulatory threshold shift” for forward masking, and “precedent

masking” for backward masking (Elliot, 1962a,b). The delay between signal and masker

in non-simultaneous studies refers to the signal-to-masker time interval (∆t). A

considerable difference between threshold shifts as a function of time intervals has been

reported for backward versus forward and monotic versus dichotic presentations (Elliot,

1962a). The results are discussed in detail in the next chapter.

1.2 Central vs. Peripheral Masking

Regardless of the type, the amount of masking produced by a particular masker largely

depends on its intensity and spectrum. Raising the intensity of a masker will cause the

masker to interfere with detecting the signal. This results in an increase in signal

detection threshold. Ipsilateral or monaural masking can be attributed to the physical

overlapping of responses to both the masker and the signal in the auditory periphery. The

3

contralateral or binaural masking process is due to the amount of energy that crosses the

head and causes a transcranial physical stimulation that leads to the masking of the signal

in the opposite ear. This phenomenon is known as cross-hearing or the crossover of the

masker and is considered to be the main cause of contralateral masking with a masker at a

high intensity level. In 1924, Wegel and Lane documented two kinds of masking: central

and peripheral. If we consider crossover as a main cause for binaural peripheral masking,

then a neurally mediated phenomenon is referred to as ‘‘central masking’’ (Wegel and

Lane, 1924). Central masking effect occur when a contralateral masker is not intense

enough to shift the detection threshold in the test ear either by transcranial physical

stimulation (crossover) of the test ear or by activation of the acoustic reflex (Zwislocki et

al., 1968).

Central masking is one of the noninvasive methods of testing the medial

olivocochlear bundle (MOCB) function that can be applied in human participants with

normal auditory function. It has been hypothesized that central masking is mediated via

the central nervous system and reflects an interaction of the masker and signal (Zwislocki

et al., 1968). Based on the literature, this effect is mediated by the efferent pathways

(Lidén et al., 1959; Blegvad, 1967; Zwislocki et al., 1968) and especially by MOCB

(Smith et al., 2000). Other masking techniques, such as monaural masking where masker

and the signal are presented to one ear, do not reflect these neural interactions within the

central nervous system (e.g. Zwislocki, 1972, 1978). Indeed, this notion is supported by

the central masking effect measured in Smith et al.’s (2000) psychoacoustic study. They

demonstrated that in macaque monkeys, central masking was reduced or eliminated when

the MOCB was sectioned at the floor of the IVth ventricle.

4

1.3 Importance and Objectives of the Study

In a normal conversational environment, a listener is exposed to various acoustic

stimuli with rapid frequency and amplitude changes (e.g. speech sounds) in background

noise. Both the signal and masker are fluctuating in the time domain in a normal

acoustical environment. These fluctuations are often not simultaneously. The time

disparity between the signal and the noise will affect the listener’s ability to detect the

signal in a noisy environment. This effect can be studied in a non-simultaneous masking

paradigm.

Moreover, it is also hypothesized that the efferent system may improve the

detection of sound in noise (Dolan and Nuttall, 1988), which in turn improves speech

intelligibility in noisy environments (Cody & Johnstone, 1982). This effect has been

attributed to neural adaptation, where the inhibitory function of the MOCB can lead to an

improvement in the coding of signals in the presence of background noise. Several lines

of research also have shown that the efferent system has a role in protecting the auditory

system from damaging sounds (Liberman, 1991). These findings may be due to the fact

that the action of the MOCB system is suppressive in nature (Fex 1967).

The evidence based on the aforementioned physiological and psychophysical data

suggests various mechanisms by which the efferent system, especially the MOCB, may

play a role in hearing in noisy environments. Obviously, the ability to detect the signal in

background noise is essential for successful communication. Thus, it is important to

identify clearly the nature of changes in MOCB functioning that may result in a listener’s

ability to detect the signal. It is also important to measure to what extent a listener’s

hearing sensitivity may be affected by MOCB functioning. In order to extend the current

5

findings on the influences that MOCB may have in detecting a relevant signal in

background noise, it was aimed to design a non-simultaneous central masking

experiment. This research method was selected for two main reasons. First, a non-

simultaneous masking paradigm simulates the signal-in-noise listening situation that an

individual may encounter in an everyday listening environment. Second, based on the

literature, central masking is a noninvasive experimental method by which MOCB

functioning can be measured in human listeners.

The main purpose of this study was to compare the detection threshold shifts for

the target tone in a non-simultaneous central masking condition with that in a non-

simultaneous monotic condition. This comparison can reveal the masking effect

attributed to MOCB influence in human listeners with normal hearing. The first goal of

this research was to investigate the effect of the signal-to-noise time interval and the

signal frequency on detection thresholds when the masker is presented in either the test or

the opposite ear. In this attempt, it was assumed that a masking effect in a non-

simultaneous central masking experiment would represent the influence of efferent

system activation on intensity encoding when the masker and the signal do not occur

simultaneously. It was anticipated that threshold shifts as a function of signal frequency

in central masking would be different from monaural masking because these masking

effects are caused by two different mechanisms.

The second goal of this research was to investigate the growth of masking with

the masker centered on and off the frequency of the signal. The growth of masking was

compared in both simultaneous and non-simultaneous monotic versus dichotic masking

conditions. It was anticipated that in central masking condition, increasing the level of the

6

masker would not change the hearing sensitivity as a much as it does in monotic

condition. It has been demonstrated that central masking increases with increasing the

masker intensity (Zwislocki et. al., 1968; Dirks and Malmquist, 1965; Dirks and Norris,

1966). However, threshold changes are equal to 1 dB for each 10 dB of the masker and

noise (Zwislocki et. al., 1968). In previous studies, the masker level higher that 60 dB

SPL was not used to avoid the impact of crossover on the result. In the present study,

utilizing an insert ear phone, the influence of crossover was eliminated at masker levels

up to 90 dB at all test frequencies. It was anticipated that central masking effect would

not grow with increasing the masker level even at masker levels higher than 60 dB SPL.

However, it was assumed that the amount of masking would enhance significantly with

increasing the masker level in monotic masking condition.

Zwislocki and colleagues (1967, 1968) showed that the threshold shift produced

by a contralateral masker increased when the frequency of the masker approached the

frequency of the signal, and that the central masking effect was very narrow at masker

frequencies around the signal frequency, especially at low levels of maskers. For this

reason, it was assumed that in contrast to monotic masking conditions, off-frequency

maskers would not produce a clear central masking effect. As a result, it was anticipated

that the overall findings of this research would increase our knowledge about MOCB

influence on detecting a signal in noise and would provide new ideas for future studies in

this area.

7

CHAPTER 2: LITERATURE REVIEW

In 1924, Wegel and Lane proposed "two kinds of masking, central and

peripheral, the former being generally relatively small and resulting from the conflict of

sensations in the brain and the latter originating from overlapping of stimuli in the end

organ" (Wegel and Lane 1924, p. 66). Most discussions of masking phenomena deal with

the "end organ" events, where both masker and signal produce dynamic basilar

membrane patterns (von Bekesy traveling waves) that can overlap. When the masker

pattern becomes large relative to the signal pattern, the auditory nerve discharges driven

by the signal are believed to disappear, and so does the listener's perception of it. The

traditional view is that central masking occurs when the threshold of a signal in one ear is

increased in the presence of a masker in the opposite or contralateral ear (Zwislocki

1978). It is assumed that central masking is a phenomenon mediated by the efferent

system, especially by the medial olivocochlear bundle (MOCB). This notion is supported

by animal studies in which central masking was reduced or eliminated when the MOCB

was sectioned at the floor of the IVth ventricle in macaque monkeys (Smith et al., 2000).

The auditory end organs of all tetrapods (including mammals) receive an efferent

innervation (Roberts and Meredith 1977; Fritzsch 1992, 1997). In 1946, Grant

Rasmussen reported his discovery of the efferent system, also called the olivocochlear

bundle (OCB), and since then hearing scientists have been attempting to understand how

8

the system works. Utilizing noninvasive methods, such as central masking, can help us

better understand its role in humans.

2.1 Efferent Fibers Classification

It has been suggested that the olivocochlear system is a general feature of the

mammalian auditory system, which must have arisen 173 million years ago (Kumar and

Hedges 1998). Among mammals for which the anatomy is known, the majority (21 of 24

species) possess cochlear outer hair cells (OHCs) that receive medial olivocochlear

(MOC) innervation (Kirk & Smith 2003). Based on the available evidence, all

olivocochlear fibers pass through the vestibulocochlear anastomosis (VCA) (Liberman

1988). In terms of anatomy, Warr and Guinan (1979) and Warr, Guinan, and White

(1986) have outlined two separate segments to the efferent system in humans: the lateral

and medial olivocochlear systems. The MOC pathway originates from mid-brainstem, in

the medial, ventral, and anterior regions, within the superior olivary complex (SOC) on

both sides, and projects to the OHCs (Warr, 1975). This population of neurons contains a

crossed component, arising from cell bodies on the opposite side of the brainstem

(roughly 2/3 of the total), and an uncrossed component with ipsilateral cell bodies,

constituting the remaining 1/3 (Guinan et al. 1983). In contrast, the lateral olivocochlear

(LOC) pathway terminates in the afferent fibers of inner hair cells (IHCs) (Smith, 1961;

Kimura & Wersall, 1962; Warr & Guinan, 1979; Liberman, 1980; Guinan et al., 1983;

Brown, 1987). It has become clear that most, or perhaps all, MOC fibers are myelinated

and that most, or perhaps all, LOC fibers all unmyelinated, at least in cats ( Guinan et al.,

1983; Arnesen & Osen, 1984). Data from a wide variety of mammals (guinea pig, rat,

9

gerbil, cat, monkey, and man) are all consistent with a basic division of the cochlear

efferents into MOC and LOC systems (Strominger et al., 1981; White & Warr, 1983;

Altschuler et al., 1983; Adams, 1986; Liberman & Brown, 1986; Schwartz et al., 1986).

In particular, all of the data fit with the idea that MOC neurons supply both crossed and

uncrossed projections to OHCs.

2.2 Roles of the Efferent System in Hearing

Evidence based neural responses recorded from single fibers indicate that all

recordings from OCB were essentially from the MOCB (Robertson and Gummer, 1985;

Liberman and Brown, 1986; Brown, 1989). According to physiological studies, activation

of efferent system leads to: (a) an increase of cochlear microphonic amplitude (Fex,

1959; Mountain, 1980); (b) a reduction of whole-nerve action potential response

amplitude (Galambos, 1956; Brown & Nuttal, 1984; Liberman ,1989); (c) the suppression

of response in individual neurons (Wiedehold & Kiang, 1970; Buno ,1978); (d) an

alteration of threshold sensitivity and tuning characteristics of individual neurons

(Wiederhold & Kiang, 1970); and (e) the suppression of evoked and spontaneous

otoacoustic emissions (Harris & Glattke, 1992; Guinan, 1996).

Physiological data in the literature suggests various mechanisms by which the

MOCB might play a role in hearing. The inhibitory nature of the MOCB is more

significant than other roles proposed to account for MOCB activation. It is also

hypothesized that the MOCB may improve speech intelligibility in noisy environments

and may also influence selective attention to the target sound.

10

2.2.1 Protection

Physiological studies also show that, shortly after acoustic stimulation of the

contralateral ear, a suppression of the auditory responses to test sounds has been observed

in afferent neurons in single-fiber responses (Buno, 1978), in the compound action

potentials (Liberman,1989), and in N1 cortical responses (Salo et al., 2003). Based on

findings on the response properties of auditory-nerve units in cats, Liberman (1989) and

Mott et al. (1987) hypothesized that contralaterally activated efferent units can depress or

inhibit the activity in the ipsilateral cochlea. It has also been hypothesized, based on the

inhibitory effect of the efferent system, that this system may have a protective role in the

auditory system in response to loud or damaging stimulation (Cody & Johnstone, 1982;

Handrock & Zeisberg, 1982; Rajan, 1988a,b; Rajan & Johnstone, 1988; Rajan, 1996;

Liberman, 1991; Liberman & Gao, 1995; Rajan, 1995). This is possibe as a noise-

protective effect has been demonstrated in mammalian species, such as guinea pigs

(Rajan and Johnstone, 1988), cats (Liberman, 1988; Rajan, 1995, 1996), chinchillas

(Zheng et al., 2000), and mice (Yoshida, Liberman, 2000).

Handrock and Zeisberg (1982) studied the ability of octave-band noise centered at

4.0 kHz to elicit MOC protection in guinea pigs. In this study, the MOC system appeared

to reduce noise trauma at 125 dB SPL but not at 120 dB SPL exposure. Liberman and

Gao (1995) studied the effects of narrow band (500 Hz) noise centered at 10 kHz on

compound action potential thresholds in guinea pigs. Ears that had been surgically de-

efferented had greater threshold shifts than normal ears when exposed to 112 dB SPL

noise, but there was not any difference in threshold shifts when the ears were exposed to

109 dB SPL noise. Zheng et al. (1997) studied the effects of 105 dB SPL broadband noise

11

exposure, suggested to produce a flat threshold shift, in chinchillas with normal and with

surgically de-efferented ears. They concluded that the MOC system decreases the

susceptibility of the cochlea to intense noise (Zheng et al., 1997). Rajan (2001)

compared threshold shifts following noise exposure in both normal animals and animals

in which the different MOC subgroups had been lesioned. The comparisons showed a

complex pattern of responses where the MOC tracts could increase the threshold. The net

effect of the MOC action, however, was protective.

The explanation for the repeated protection findings can be due to the fact that the

action of the MOC system is suppressive in nature (Fex 1967; Konishi and Slepian 1970;

Wiederhold and Kiang 1970; Buno 1978; Mountain, 1980; Siegel and Kim 1982;

Liberman 1989; Warren and Liberman 1989a; Kawase and Liberman 1993; Kawase et al.

1993; Cazals and Huang 1996; Lima da Costa et al. 1997; Nuttall et al. 1997). The

magnitude of MOC-mediated suppression increases with the level of afferent neural

activity (Guinan and Stankovic 1996). Guinan and Stankovic (1996) have shown that

MOC activity can produce a reduction in single fiber discharge rate equivalent to a 50 dB

attenuation of the input stimulus at best frequency. As a result, MOC action might have

the net effect of reducing the level of the intense noise exposure, thereby reducing the

resulting damage.

2.2.2 Enhancement

As discussed earlier, the suppressive effect of OCB is demonstrable with a

contralateral acoustic stimulus or an electrical shock in quiet. However, if the ipsilateral

acoustic stimulus is in a continuous background noise, electrically evoked OCB can

12

increase the amplitude of auditory nerve response (Nieder and Nieder, 1970; Winslow

and Sachs, 1987; Dolan and Nuttall, 1988). Researchers called the later phenomenon a

“contralateral-sound enhancement,” which is also known as the antimasking effect of the

efferent system and was discussed above. This antimasking effect had been demonstrated

with shock evoked OCB activation (Nieder and Nieder, 1970; Winslow and Sacha, 1987;

Dolan and Nuttall, 1988). An enhancing effect demonstrated by shock-evoked OCB

activation was also shown with sound–evoked OCB activity (Kawase & Liberman,

1993). Kawase and Liberman (1993) studied the enhancing role of OCB. The elevation

of compound action potential thresholds was seen when a contralateral noise was added

to an ipsilateral signal presented with continuous noise. Kawase and Liberman (1993)

demonstrated that both the suppressive and enhancing effects of contralateral stimuli on

compound action potential disappeared when the entire OCB was cut at the floor of the

fourth ventricle.

The function of MOCB to enhance signals in noise encoding has been supported

by electrophysiological data (Liberman, 1989; Winslow and Sachs, 1987, 1988; Kawase

et al., 1993; Kawase & Liberman, 1993). The existence of such influence on enhancing

signals in background noise requires a combination of both physiological and

psychophysical or behavioral measurements. Such a combined approach has been used in

both animal (Dewson, 1968; Capps & Ades, 1968; Igarashi et al., 1979a,b; May &

McQuone, 1993, 1995; Heinz et al., 1998; Zennaro et al., 1998; Zheng, et al., 2000; May

et al., 2002; May et al. 2004) and human studies (Scharf et al., 1994; Ryan & Piron,

1994; Williams et al., 1994; Scharf et al., 1997; Zheng et al., 1999, Zheng et al., 2000;

Morlet et al., 2004). The enhancement role of the MOCB has also been inspired by

13

Russell and Muragasu’s study (1997) evidencing that OCB reduces cochlear

compression. Because cochlear compression reflects intensity encoding by the peripheral

auditory system, if cochlear functioning is altered by OCB activity, then intensity

perception is also likely to be affected.

The effects of MOC on hearing performance in humans have been examined in

several studies after vestibular neurectomy and neurotomy in patients with Meniere’s

disease. In this procedure, a significant amount of efferent fiber is cut. The unmasking

effect of OCB is also evidenced in human studies by the strong relationships between

detection and intensity discrimination thresholds of tones presented in binaural noise

(Zheng et al., 2000). They conducted behavioral studies in six patients who had

undergone a vestibular neurectomy procedure for vertigo. They demonstrated that a

significant reduction of the overshoot effect and degraded intensity discrimination in

noise in the surgery ear, including worsened intensity discrimination in noise in the

steady-state condition but not at the onset of the noise.

Costalupes et al. (1984), Smith (1978), and Young and Suchs (1973) suggested

that antimasking can occur because auditory nerve responses are adapted to the steady-

state noise. Therefore, an inhibitory function could lead to an improvement in the coding

of signals in the presence of noise. Moreover, it has been proposed that OCB activity

makes the encoding of the signals in noise backgrounds more accurate, leading to lower

(better) detection and discrimination thresholds in noise.

14

2.2.3 Improving Selective Attention

It has been hypothesized that OCB may play a role in selective attention, a theory

which is still controversial. This role has been also proposed as the Peripheral filter

model of attention (Hernandez-Peon, et al. 1956) based on data showing that responses to

clicks recorded at the dorsal cochlear nucleus in the auditory system of awake cats

changed given the direction of visual attention (Hernandez-Peon et al., 1956). The

peripheral filter model was supported by other investigations in late seventies. Oatman

and colleagues (Oatman, 1971, 1976; Oatman and Anderson, 1977, 1980) in a series of

experiments on awake cats demonstrated that cochlear responses recordered at round

window were reduced during visual attention. There has been a renewed interest in this

model after recent evidence that outer hair cells (OHCs) may play a role in altering the

cochlear mechanical responses to the acoustical stimulations within the cochlea (Brundin

and Russell, 1993). The efferent innervation of OHC would therefore provide a means by

which the descending modulation of the sensitivity of the cochlea may occur (LePage et

al., 1993)

Scharf and his colleagues (1994, and 1997) conducted extensive behavioral

studies on vestibular neurotomy and neurectomy patients. These studies have been

interpreted as showing evidence of support for the peripheral filter model of attention

which may be achieved by the action of efferent fibers (1997). In one case study, Scharf

and his colleagues (1994) measured the effects of neurotomy on the discrimination of

tones in noise on one patient. They found essentially no difference between the ear,

which underwent the surgery and the normal ear in detection of tones in noise. The only

abnormal finding was that the efferent-sectioned patient could no longer focus his

15

attention on a certain frequency region in an experiment requiring detection of expected

and unexpected tones. Scharf et al. (1997) were able to replicate these basic findings in

16 case studies. They showed that detection and discrimination performances, including

detection of tonal signals, intensity discrimination, frequency selectivity, loudness

adaptation, frequency discrimination within a tonal series, and lateralization, did not

change significantly for the same ear after the surgery. The sole clear change was that

most patients detected signals at unexpected frequencies better than before. Scharf et al.

(1997) suggested that this change suggests an impaired ability to focus attention in the

frequency domain.

Some evidence of modulation of MOCB activity due to both auditory and visual

attention has been reported in humans, as shown by the MOCB effect on evoked

otoacoustic emissions (EOAEs) (Froehlich et al., 1993; Meric et al., 1996; Giard et al.,

2000). Effects of auditory and visual attention on contralateral suppression of EOAEs

have also been reported. One previous study suggested that visual attention increases

suppression strength (Ferber-Viart et al., 1995) and another reported that suppression

disappeared with sleep onset (Froehlich et al., 1993). By contrast, in a study conducted by

de Boer and Thornton (2007) the tasks that engaged visual attention did not show a

difference in suppression strength relative to the passive awake condition. They

concluded that MOCB activity is inhibited when selective attention is focused on the

ipsilateral ear. These findings may suggest the possibility of top–down control of MOCB

activity, potentially mediating the effects of higher order processing (de Boer and

Thornton, 2007).

16

In summary, existing neurophysiologic data strongly suggest that the presence of

OCB reflex feedback should have no effect on behavioral detection thresholds measured

in quiet (e.g. Scharf et al. 1997). Thus, the elimination of OCB should not affect the

threshold that was reported in behavioral studies (e.g. Trahiotis and Elliot, 19762a,b).

However, the previous studies in patients after vestibular neurectomy have demonstrated

that some binaural psychophysical phenomena were affected when the intensity level of

contralateral stimulation was lower than that required to produce crossover (Collet et al.

1990; Veuillet et al., 1991; Zeng et al., 1991; Zeng and Shannon, 1995; Micheyl et al.

1997; Zheng et al., 2000). Activation of the OCB neurons by electrical or auditory

stimulation typically decreases the ear’s response to sound. This feedback system, as

discussed earlier, has been proposed as a mechanism for protection from acoustic

overexposure (Puel et al., 1988; Rajan, 1995; Liberman and Gao, 1995; Maison and

Liberman, 2000) and the reduction of masking (Winslow and Sachs, 1988; Kawase and

Liberman, 1993).

2.3 Methods of Studying Efferent System Activation in Humans

Despite the thorough description of the efferent anatomy, the functional role of

the efferent fibers is poorly understood and is still a matter of debate in human studies.

One major cause of this issue might be various surgical procedures that have been used in

patients who underwent vestibular neurectomy and neurotomy, as well as the different

causes that led to these surgeries. Thus, the findings related to the role of OCB in human

psychoacoustic abilities, which have been reported in patients who had undergone

surgical procedures, should be interpreted cautiously. In other words, patients who have

17

undergone either vestibular neurotomy or neurectomy may not be good models for

studying the role of the efferent system in humans because the result might be

contaminated by other confounding factors such as surgical procedures or the number of

efferent fibers that might remain intact after sectioning the vestibular nerve. Even if the

whole vestibular nerve is sectioned, some doubt may remain about whether all the

efferent fibers are also cut.

Physiological assessments of OCB function have relied almost exclusively on

peripheral response measures that include otoacoustic emissions (Mott et al., 1989;

Kujawa et al., 1993), compound action potentials (Galambos, 1956; Liberman, 1989;

Puria et al., 1996), and the discharge rates of auditory-nerve fibers (Wiederhold, 1970;

Gifford and Guinan, 1987; Winslow and Sachs, 1987). However, psychophysical

experiments, such as binaural masking studies, have mainly measured binaural

interactions by activating the physiological pathway between the two ears. It has long

been known, for example, that the threshold of audibility of a tone presented to one ear is

increased by presentation of stimuli to the contralateral ear, despite virtually complete

acoustic isolation of the two ears (Wegel & Lane, 1924). A centrally mediated

phenomenon has been extensively used in psychophysical studies on human to show the

effect of OCB activation.

This phenomenon has been studied by several groups of investigators, and has

been referred to as “central masking” because it was thought to result from interactions

within the central nervous system (Zwislocki et al., 1967). The finding that contralateral

sound may suppress the sound-driven activity of single auditory-nerve fibers suggests

that the phenomenon of central masking may have a peripheral component mediated by

18

olivocochlear efferent neurons. Our previous discussions may account for how a system

which has shown basically similar functions in physiological studies in animal and

humans may show different effects in behavioral studies of the same species (i.e. human).

As discussed earlier, the different findings in behavioral studies on humans have resulted

from the impact of several confounding factors related to listeners’ conditions after

surgery. Thus, behavioral studies on listeners with a normal hearing condition can show

the influence of OCB activation more properly and constantly.

Based on the physiological and behavioral findings in humans (e.g. Kawase &

Liberman, and 1993 Zheng et al., 2000) indicating the effect of efferent system on

forward masking, and considering the fact that the central masking effect shows a

phenomenon mediated by MOCB (Smith et al., 2000), we expect that findings of a non-

simultaneous central masking experiment may provide insight into the functional

properties of the efferent system and its influence on detecting a signal in a noisy

environment. How can we measure the central masking effect in normal hearing

listeners? And, how can this effect be measured in a non-simultaneous masking

condition? In the next sections we will answer these two questions, and will review the

effects of the acoustic characteristics of stimuli on central masking and also on non-

simultaneous masking conditions.

2.4 Central Masking

Wegal and Lane (1924) were probably the first scientists to provide a modern

description of a centrally mediated phenomenon that was later referred to as central

masking. Central masking is a phenomenon that occurs when the threshold of a signal in

19

one ear is increased in the presence of a masker in the contralateral ear (Zwislocki, 1978).

In other words, we need to increase intensity in the ipsilateral ear in order to maintain an

audible signal when a contralateral masker (noise) is presented to the opposite ear. The

important point in this condition of masking is that a contralateral masker is not intense

enough to shift the detection threshold in the test ear, either by transcranial physical

stimulation (crossover) of the test ear or by activation of the acoustic reflex. In other

words, to qualify as a central masking rather than monaural or peripheral masking, two

experimental conditions must be assured. The first is that the level of the masker must be

below the threshold of the acoustic reflex. In most species, the acoustic reflex can be

elicited by both ipsilateral and contralateral acoustic stimuli higher than 70 dB SPL (Pang

and Peake, 1986). Thus, in studies of central masking, the level of the masker must be

less than about 70–75 dB SPL. The second requirement is that the masker does not cross

from one ear to the other, either by air or bone conduction. For this reason, in central

masking studies interaural attenuation must be maintained by the use of appropriate insert

earphones. As a result, in central masking studies it is important to present a contralateral

masker at the levels of the listener’s acoustic reflex threshold, and to enhance interaural

attenuation by using appropriate earphones.

Wegel and Lane (1924) indicated that central masking was relatively small and

resulted from “the conflict of sensations in the brain,” but they hypothesized that

peripheral masking originates from the “overlapping of stimuli in the end organ” (Wegel

and Lane, 1924, p. 66). It has been hypothesized that central masking is mediated via the

central nervous system and reflects an interaction of the masker and signal (Zwislocki et

al., 1968). Other masking techniques, such as monotic masking where the masker and the

20

signal are presented to one ear, do not reflect these neural interactions within the central

nervous system (e.g. Zwislocki, 1972, 1978). Lidén et al. (1959) and Blegvad (1967)

suggested that the central masking effect is a peripheral phenomenon and is mediated by

the efferent pathways. Indeed, this notion is supported by the central masking effect

measured in Smith et al.’s (2000) psychoacoustic study. They demonstrated that central

masking was reduced, or eliminated, when the MOCB was sectioned at the floor of the

IVth ventricle in macaque monkeys.

Several studies on the central masking phenomenon were conducted to evaluate

the amount of threshold shift and also the influence of various parameters such as

frequency and the intensity of the signal and the masker (e.g. Hughes, 1940; Ingham,

1957; Dirks and Malmquist, 1965; Dirks and Norris 1966; Zwislocki et al., 1968).

Results of the central masking effect have been reported using different psychoacoustic

methods such as Békésy tracking (e.g. Zwislocki et al., 1968, Smith et al., 2000), a

modified method of limits using ascending procedure (e.g Synder, 1973), and a two-

interval forced-choice adaptive (2IFC) and single interval of Yes-No adaptive methods

(e.g. Mills et al., 1996). In the Békésy tracking method, the examinee adjusts the probe

tone intensity level using an attenuator to maintain the probe’s audibility when a

contralateral masker is presented to the opposite ear. The attenuator increases or

decreases the probe intensity at a certain rate that is defined in dB per second. The

averages of the midpoints of pen excursions are accepted as a measure of the thresholds.

In the 2IFC method, the signal threshold is determined by the presence of a

contralateral masker. Each run consisted of a certain number of trials (e.g 50, 100, or 200

trials). By contrast, in the Yes-No adaptive procedure used in Mills and colleagues’

21

(1996) study, a single trial was used. For each trial in the forced-choice methods, one

interval contains the noise alone and the other contains the noise plus a signal. The

interval containing the signal is selected randomly on each trial of 2IFC procedure. In the

Yes-No procedure the examinee is supposed to indicate whether there is a signal or not.

After a certain number of first reversals (e.g two or three), the step size may be reduced.

Feedback is normally provided after each trial for the examinee. The threshold for each

run is calculated as the average of the last x numbers of reversals (e.g. five to seven

reversals). Regardless of the method used for determining the threshold, the central

masking effect is calculated by subtracting the hearing threshold with masking from the

threshold obtained without masking or in quiet. This effect is commonly introduced in

dB.

2.4.1 Psychophysical Results of Central Masking Obtained with Normal Hearing

Listeners

The first classic report of central masking was published by Wegel and Lane

(1924), which indicated a contralateral masking effect of about 3 dB. Hughes (1940)

found an effect of 4–10 dB, which was confirmed by Ingham (1957) when the frequency

of the signal and the masker were nearly identical. Modern efforts to discover any

contributions of neural activity to central masking effect may originate with Zwislocki

(Zwislocki et el., 1967). He and his colleagues (1967, 1971) argued that central masking

is best measured under stimulus conditions where the onset of the target signal coincides

with the onset of the contralateral masker; under these conditions thresholds are elevated

by as much as 12 dB or more, depending on the masker level. He also observed a 3- to

22

18-dB threshold shift due to central masking in his later psychophysical study of

contralateral masking (Zwislocki, 1972). The results shown by Mills et al (1996)

confirmed Zwislocki et al. (1967) findings: the threshold of a pulsed signal in one ear was

elevated by 12 dB when a pulsed, moderate-level masker was presented to the opposite

ear. Other studies showed that when the onset of the contralateral masker precedes the

onset of the signal by more than 60–100 ms, allowing for adequate binaural neural

conduction times, or with continuous contralateral maskers, the magnitude of

contralateral suppression due to central masking effect ranges between 2 and 6 dB,

depending on the contralateral noise level (Ingham, 1959; Lidén et al., 1959; Dirks and

Norris, 1966; Blegvad, 1967; Snyder, 1973; Benton and Sheeley, 1987, Kawase et al.,

2000).

The effects of contralateral noise on ipsilateral thresholds have also been recorded

in the clinical literature. When measuring thresholds in an impaired ear with more than a

40–60 dB threshold shift, it is suggested that presenting a masking noise in the

contralateral (or more sensitive) ear prevents the detection of the intense test signal via

transcranial conduction (Palva, 1954; Lidén et al., 1959; Studebaker, 1964, 1967; Price,

1971; Martin et al., 1962; Dirks and Malmquist, 1965; Snyder, 1973). In general, this

literature suggests that, as a practical issue in clinical measurements, a corrective factor

of 5–15 dB should be subtracted from threshold shifts measured with the contralateral

noise, to compensate for increases in the threshold due to ‘‘central masking’’. For

instance, Studebaker (1964), Price (1971), and Martin (1972) suggested an approximate

5-dB threshold shift, while Lidén et al. (1959) demonstrated that the effect is 5 to 15 dB

and remained relatively constant as the masker level increased. Palva (1954) stated that

23

the threshold changes resulting from the central masking effect would be less than 10 dB

in general.

2.4.1.1 Effects of Masker Onset and Duration

Zwislocki and his colleagues (1968) demonstrated that near the masker onset,

threshold shift was almost 15 dB. They showed that this shift was reduced to about 4 dB

within 150 ms after the masker onset, and a slow decay of about one to two dB occurred

over several minutes delay (Zwislocki et al, 1968). They indicated that, near the masker

onset, the threshold shift increases with the masker intensity then, after a sufficient time

delay of around 200 ms, threshold shift gradually decays and reaches a steady state level

(Zwislocki et al, 1968). The amount of the decay appears to be directly related to the

threshold shift at the masker onset (Zwislocki et al., 1968). The greater this shift, the

more pronounced the decay would be. They concluded that that the masking decays

fastest where it is initially the largest (Zwislocki et al., 1968). Importantly, they

demonstrated that the rate of decay did not depend on either the masker frequency or the

frequency difference between the masking and test tones: it was only dependent on the

amount of initial threshold shift, and time-decay functions were similar whenever the

initial amounts of masking were the same (Zwislocki et al., 1968).

This phenomenon has been also shown by numerous physiological studies using

recordings of single unit activity in the 8th nerve and the cochlear nucleus (Kiang et al.,

1965; Goldberg and Greenwood, 1966). Zwislocki (1971) later compared the results of

physiological and psychoacoustic studies mentioned below, and proposed a theory of

central masking (1972, 1978) which was based on the psychophysical data and

24

neurophysiological observations from the auditory central nervous system. He stated that

with progressive increases in the delay between the onset of the masker and target signal,

the magnitude of the threshold shift decreases to a steady state, with an intensity-

dependent level, of 2–6 dB by 60–120 ms. Lima da Costa et al. (1997) showed that this

steady-state suppression can be maintained for minutes or even for hours.

Sherrick and Albernez (1961), Dirks and Malmquist (1965), and Billing and

Stokinger (1977) showed that contralateral masking effects were largest when the masker

and signal were either continuous or simultaneously pulsed, and they were smallest when

the masker was continuous and the signal was pulsed. Indeed, the masking effect was

smallest when the temporal characteristics of the masker differed from that of the signal.

Zwislocki and his colleagues (1967, 1968) also reported that gated maskers produced

more threshold shift than continuous maskers, and that intersubject variability was large,

with a masking effect ranging from 3 to 18 dB. Smith et al. (2000) suggested that the

relatively large threshold shifts seen with masker-signal onset delays of 20 ms or less

might be attributed to other mechanisms, such as what they called ‘‘confusion.’’

2.4.1.2 Effects of Masker Level

With the development of insert earphones, Zwislocki et al. (1968), Dirks and

Malmquist (1965), and Dirks and Norris (1966) demonstrated that the central masking

effect increased with increased masker intensity. This effect reached a maximum value

when the signal onset was delayed relative to masker onset by 10–20 ms (Zwislocki et

al., 1967, 1968), and reduced to a relatively stable amount of signal threshold shift after

about 200 ms from the onset of the masker. Zwislocki et al. (1968) also investigated the

25

effect of the masker sensation level on the central masking effect using the method of

Békésy tracking. The masker and test tone were both presented in bursts of 250 and 10

ms, respectively. The probe tone was presented with various time delays with respect to

the masker onset. They also varied the frequency of the masker while maintaining that of

the test tone at 1000 Hz. Using a masker at sensation levels from 20 to 70 dB SL, they

showed that the masker SL affects both the amount and the distribution of the threshold

shift, and therefore changes the frequency distribution curves of central masking. These

curves showed the threshold shift of a 1000-Hz probe tone as a function of masker

frequency at various intensity levels of the masker. At higher masker levels (e.g. 40 dB

SL), both the width and the height of these curves were increased. At lower levels, the

main peak of these curves gradually decreased. A local minimum appeared at frequencies

below and above the main peak, and became more noticeable at low masker levels. As

the masker level increases, the low-frequency minimum moved away from the main peak

so that at higher levels, the low-frequency maximum and minimum became gradually

flatter (Figure 2.1).

2.4.1.3 Effects of Signal Frequency and Noise Bandwidth

Zwislocki and colleagues (1967, 1968) showed that the threshold shift produced

by the contralateral masker increased when the frequency of the masker approached the

frequency of the signal. Mills et al. (1996) confirmed the results presented by Zwislocki

and his colleagues (1967, 1968). That is, the threshold of a pulsed signal in one ear was

elevated when a pulsed, moderate-level masker was presented to the opposite ear. The

masking observed was greatest when the frequency of the masker was equal to the

26

Figure 2.1. Frequency distribution of central masking at various masker intensity levels

obtained in normal hearing listeners ( Zwislocki, et al., 1968, p. 1270).

frequency of the signal (Mills et al., 1996). Other investigators reported the effect of

signal frequency on central masking (Ingham, 1959; Sherrick and AIbernaz, 1961; Dirks

and Malmquist, 1965). Ingham (1959) and Dirks and Malmquist (1965) used pure tones

and single narrow-band maskers as stimuli. They investigated an increment in the central

masking effect with an increase in the test tone frequency. Sherrick and Albernaz (1961)

also found the similar results using pulsed stimuli.

A similar effect was demonstrated in physiological studies of MOC fibers. It has

been shown that MOC physiological suppression is greatest at frequencies of 1.0 to 10.0

kHz (Guinan and Gifford, 1988a; Warren and Liberman, 1989a), with the magnitude of

the suppression increasing in an intensity dependent manner. This frequency distribution

corresponds to the areas of the basilar membrane which contain the highest density of

MOC innervation (Guinan et al., 1984; Liberman et al., 1990; Sato et al., 1997). In all of

these studies, the effects of the MOC activation are eliminated when the MOC tracts are

27

interrupted. In an attempt to investigate the frequency distribution of central masking,

Zwislocki et al. (1968) used bursts of maskers in various frequencies in small discrete

steps, from 300 to 2000 Hz, while the probe tone was kept constant at 1000 Hz. Data

reported by Zwislocki et al. (1968) revealed that the maximum threshold shift occurred at

a masking frequency of 1000 Hz, or slightly lower when the signal was a 1000-Hz burst.

They concluded that the frequency distribution of central masking indicates a complex

nonlinear process with three possible peaks, and it likely reflects interactions between

neural excitation and inhibition (Zwislocki et al., 1968).

In a study on normal hearing listeners, Synder (1973) demonstrated that masker

bandwidth can also influence the central masking effect. He tested forty normal hearing

listeners using pure tones at 0.5, 1, 2, and 4 kHz. Wide and narrow-bands of noise served

as contralateral maskers. The hearing threshold was measured with and without a

contralateral masker in a modified method of limits, with ascending procedure. The

masker level (40 dB HL) used in this study was not intense enough to activate bilateral

acoustic reflexes or produce any crosstalk, so the threshold shift more likely resulted

from a centrally mediated mechanism. Each narrow-band masker centered at signal test

frequencies, and was presented for threshold estimation of the corresponding frequency.

Results of this study indicated that central masking effect increases in terms of dB when

the frequency of the signal increases (Synder, 1973). Central masking was roughly 5 dB

greater at 4 kHz compare to the other test frequencies. Results also implied that the

central masking effect was greater with narrow-band noises than with wide-noise. The

amount of central masking increased from 4.6 dB for a narrow-band noise to 6.6 dB

28

using a wide-band noise at 4 kHz (Synder, 1973). He concluded that using a narrow-

band masker enhances the central masking effect by 10 to 15 dB.

2.4.2 Mechanisms Underlying Central Masking

The term central masking, in contrast to peripheral masking, implies that the

interaction of the masker and test signal occurs somewhere in the central nervous system,

or that the masker is mediated via the central nervous system though the interaction may

take place in the contralateral peripheral system. Numerous studies, mentioned earlier,

have measured changes in pure-tone thresholds with various contralateral stimuli, in

order to characterize the phenomenon of central masking (Ingham, 1959; Lidén et al.,

1959; Dirks and Norris, 1966; Blegvad, 1967; Zwislocki et al., 1967, 1968; Zwislocki,

1971; Snyder, 1973; Benton and Sheeley, 1987). The central masking effect was

attributed to central processes by some of the investigators (e.g. Ingham, 1957; Lidén et

al., 1959; Snyder, 1973), because it was suggested that these data may reflect the effects

of the efferent system in an auditory psychophysical phenomena (i.e. central masking).

Importantly, the first evidence of the central masking effect was established before the

characterizations of the role of the medial olivocochlear (MOC) system in the physiology

of peripheral auditory system function. For instance, several years after the first literature

on the central masking effect (e.g Wegel and Lane, 1924; Hughes, 1940), physiological

studies showed that the activation of efferent system resulted in an increase of cochlear

microphonic amplitude (Fex, 1959; Mountain et al., 1980), a reduction of whole-nerve

action potential response amplitude (Galambos, 1956; Brown & Nuttal, 1984; Liberman

,1989), a suppression of the response from individual neurons (Wiedehold & Kiang,

29

1970; Buno ,1978), an alteration of threshold sensitivity and tuning characteristics of

individual neurons (Wiederhold & Kiang, 1970), and a suppression of stimulated and

spontaneous otoacoustic emissions (Harris & Glattke, 1992; Guinan, 1996). Similarities

between the patterns of threshold shift in central masking with the pattern of firing rate

recorded from single auditory neurons (Zwislocki, 1971) revealed the fact that a central

rather than a peripheral mechanism accounts for the central masking effect.

The similarities seen in the suppressive effects of a continuous contralateral

stimulus on behavioral thresholds in humans and animals, and on compound action

potentials, single afferent fiber responses, and otoacoustic emissions, suggests a common

mechanism. The repeated physiological demonstration that this suppression is greatly

reduced or eliminated following interruption of the MOC tracts suggests that at least

some aspects of central masking might be efferent mediated peripheral processes. Indeed,

several investigators have previously suggested that central masking is an efferent

process (Lidén et al., 1959; Blegvad, 1967; Winslow and Sachs, 1987; Warren and

Liberman, 1989a). Smith et al. (2000) performed a psychophysical study of central

masking in nonhuman primates. The goal of the research was to demonstrate the role of

the MOCB in changing hearing sensitivity, comparable to that played in contralateral

efferent suppression, in central masking. At contralateral noise levels of 30 dB SPL and

above, thresholds were increased or suppressed, relative to those measured in quiet, in a

manner that was both frequency and intensity dependent (Smith et al., 2000). To

determine if threshold increases measured in the presence of continuous contralateral

noise were dependent on MOC activation, one subject underwent a surgical sectioning of

the MOC on the floor of the IVth ventricle. Following surgery, the increases in thresholds

30

seen with higher contralateral noise levels were substantially reduced or eliminated

(Smith et al., 2000). The changes in psychophysical thresholds produced by contralateral

noise in Smith et al.’s (2000) study were similar to the results of contralateral

physiological suppression in the physiological literatures, which were known to be

related to the sectioning or direct electrical stimulation of the MOC (Fex 1967; Konishi

and Slepian 1970; Wiederhold and Kiang 1970; Buno 1978; Mountain 1980; Siegel and

Kim 1982; Gifford and Guinan, 1987; Liberman 1989; Warren and Liberman 1989a;

Kawase and Liberman 1993; Kawase et al. 1993; Cazals and Huang 1996; Lima da Costa

et al. 1997; Nuttall et al. 1997). These findings, therefore, indicate that the central

masking effect produced by dichotic masking conditions are mediated by peripheral

MOC efferent mechanisms.

Studies of the electrophysiological responses recorded in humans have also

revealed that central masking may be due to binaural interaction of the signal and masker

at lower levels of the auditory system. Galambos and Makeig (1992) studied the central

masking effect with recording steady-state responses. When the noise was turned off, the

response amplitude promptly returned to its baseline value. Auditory steady-state

response (SSR) amplitude changes with a low Intensity level of a contralateral masker

(45 dB), which replicates the masking condition in central masking studies, and

significant changes in SSR amplitude at this low masker level are similar to the threshold

shifts occurring in the central masking effect. As a result, the reduction in SSR with a 45-

dB masker implies an interaction within the auditory nervous system, which in turn

highlights the possible role of this system in the central masking effect.

31

2.5 Non-simultaneous Masking

Non-simultaneous masking refers to situations where a signal is presented either

after the masker offset or before the masker onset. The former phenomenon is called

forward masking (e.g., De Maré, 1940; Lüscher and Zwislocki, 1947) and the latter is

called backward masking (e.g., Miller, 1947; Samoilova, 1959; Pickett, 1959). Other

terminologies have been used for non-simultaneous masking paradigms, such as “residual

masking” and “post-stimulatory threshold shift” for forward masking, and “precedent

masking” for backward masking (Elliot, 1962a). The delay between signal and masker in

non-simultaneous studies refers to the time interval (∆t) between the signal and the

masker. Non-simultaneous masking paradigms have been extensively studied in terms of

time masker-signal interval, and the phenomenon has been more significant in a certain

range of time interval.

Conducting a non-simultaneous masking experiment is the same as a

simultaneous masking experiment. First, the unmasked threshold of the test stimulus is

determined in quiet (without masker noise). This threshold is considered as a baseline for

further evaluations. Next, the masker is presented either ipsilaterally or contralaterally

and the signal is presented simultaneously or non-simultaneously (in forward and

backward masking) with the masker. The threshold for the signal is determined again.

The amount of masking is described as the difference in decibels between the signal

threshold in quiet (baseline) and masked threshold. Different psychoacoustic methods,

such as adaptive procedures or classical methods can also be used in masking studies.

Non-simultaneous masking experiments can be performed in monotic and dichotic

conditions. In a monotic condition both the signal and the masker are presented in the

32

same ear. However, in a dichotic condition, the signal is presented to one ear and the

masker is presented to the opposite ear. The amount of masking obtained in these two

listening conditions is not typically the same.

2.5.1 Psychophysical Results Obtained in Non-simultaneous Masking Paradigms

The amount of masking has been determined by the manipulation of a number of

acoustic characteristics of the masker and the signal, such as masker and signal

frequency, masker and signal duration, masker level, and the temporal separation of

masker and signal in non-simultaneous masking. The details of these factors’ interactions

are poorly understood. Most studies have reported data for several values of one or two

factors, with all of the remaining factors held constant. The specific values of the

remaining factors may have a strong influence on the results, but that influence cannot be

determined from the data in any given experiment. Differences in stimuli, test

procedures, and listeners make comparisons across studies difficult. Thus, any

discrepancies seen in the results of masking studies are a result of different methods of

data analysis, and possibly the various procedures of data collection that have been used

in different studies. The effects of some of the important factors on masking studies are

discussed below.

2.5.1.1 Effects of Frequency

In non-simultaneous studies, temporal separation of the masker and the signal can

influence on the effect of frequency on masking. This complicates the interpretation of

the frequency effect in a non-simultaneous masking paradigm. Thus, it is important to

33

know whether the effect of frequency is due to a change in the slope of non-simultaneous

function masking as a function of frequency, or to a change in the time required to

recover from a given amount of masking. To understand the possibilities, we need to

review the evidence about non-simultaneous masking as a function of these two major

factors.

A number of studies have reported forward-masking data obtained at different

frequencies (Rawdon-Smith, 1934; Bronstein and Churilova, 1936; Lüscher and

Zwislocki, 1949; Harris et al., 1951; Harris and Rawnsley, 1953; Harris et al., 1958,

Elliott, 1962a,b; Ehmer and Ehmer, 1969). The majority of these studies have concluded

that there is greater forward masking at higher frequencies (2000 to 8000 Hz),

particularly given relatively long signal delays. In general, these results disagree with the

results obtained in backward masking in terms of the effect of frequency on the amount

of masking (Samoilova,1956; Duifhuis,1973; Dolan and Small, 1984). Jesteadt et al.

(1982) showed that more forward masking occurs at very low frequencies than at high

frequencies with maskers at equal sensation levels. This result is inconsistent with

previous studies (e.g., Lüscher and Zwislocki, 1949; Harris et al., 1951) which have

shown greater forward masking at high frequencies for equal-SL maskers. The difference

could be due to the use of forced-choice procedures in the later study, compared to use of

the method of constant stimuli or method of limits in the earlier works. This may have

resulted in lower quiet thresholds for the lower frequencies in Jesteadt et al’s (1982)

study, and hence, greater amounts of masking. Quiet thresholds were not published in the

earlier studies, so no comparisons are possible. Dolan and Small (1984) attempted to

remove the frequency effects related to simultaneous masking by normalizing their data

34

in backward masking study. The normalized data in this study showed a tendency of

reduced masking with increasing probe frequency. This finding was consistent with those

reported earlier by Duifhuis (1973) and Samoilova (1959). Elliot (1962b) studied the

effect of signal frequency in backward and forward masking and compared the results in

monoitc and dichotic conditions. In her study, a 90-dB SPL white noise with 50 ms

duration served as the masker. Tones of 0.5, 1, and 4 kHz with 7 ms duration were

employed as signals. Figure 2.2 shows the results of backward and forward masking in

monotic condition reported by Elliot (1962b).

In backward masking condition her results confirmed Sherrick and Albernaz’s

(1961) results in simultaneous masking, indicating greater masking at 4 kHz, while this

effect was not maintained at longer intervals. However, in forward masking conditions,

Elliot (1962b) observed less masking at 4 kHz at shorter intervals. This finding was

confirmed in the Jesteadt et al.’s (1982) experiment. Elliot’s (1962b) results in dichotic

conditions with the same signals and the masker showed that there was less forward

masking than backward masking at all frequencies (Elliot, 1962b). The results are shown

in Figure 2.3. She concluded that in dichotic conditions the frequency effect was not as it

was anticipated from simultaneous masking studies (Elliot, 1962b), but masking was

greater for low frequency of the signal at lower time intervals in both backward and

forward masking conditions. Results of the later studies confirmed her findings in both

forward (Jesteadt et al., 1982) and backward (Dolan and Small, 1984; Duifhuis, 1973)

masking paradigms.

35

Figure. 2.2 Results of monotic backward and forward masking as a function of time

interval and frequency of the signal (Elliot, 1962b).

2.5.1.2 Effects of Time Interval

The interval separating masker and signal has been studied extensively by several

investigators (e.g. Zwislocki et al., 1959; Fastl, 1979; Widin and Viemeister,1979). All

studies reported that the amount of masking decreased linearly in time. Similar functions

have been reported in studies using broader bandwidth maskers or signals (Smiarowski

and Carhart, 1975; Fastl, 1976; Weber and Moore, 1981). Samoilova (1956) reported a

series of backward-masking experiments where a brief, sinusoidal probe tone was

followed, after a silent interval, by a 300-ms masking tone. The threshold for hearing the

probe tone was studied as a function of the durations of the probe tone and the silent

interval. The amount of backward masking increased from 10 to 70 dB as the probe-tone

duration decreased from 100 to 20 ms (probe tone 1300 cps; masking tone 1000 cps, 80

dB; silent interval 2 ms). Under similar conditions of frequency and intensity, the

backward masking upon a 20-ms probe tone increased from 3 to 60 dB as the silent

interval decreased from 100 to 1 ms. Finally, with a masking tone of 500 Hz, backward

masking was found over a frequency range of probe tones from 260 to 3800 Hz. The

36

Figure. 2.3 Results of dichotic backward and forward masking as a function of time

interval and frequency of the signal (Elliot, 1962b).

maximum backward masking occurred with probe tones of 550 and 1400 cycles,

respectively, and for the 500-cycle and 1000-cycle masking tones. Results indicated that

greater backward masking occurred at low signal frequencies and shorter time intervals.

The backward masking curves tended to show two distinct segments that were

similarly shaped in various studies (Pickett, 1959; Elliott, 1962a, b; Fastl, 1976),

including an initial steep portion for shorter intervals and a much more gradually sloped

portion for longer intervals. Comparing the shapes of the curves for backward and

forward masking in Elliot’s study (1962b), a considerable difference is noted. The

monotic forward masking curve has a gradual and relatively constant slope up to 50 ms

time intervals, where it becomes flat in longer intervals (Figure 2.2). However, the

backward masking curves appear to be composed of two distinct functions. The slope

from 50 to 15 ms is considerably less than that from 15 to 0 ms (Figure 2.2). For the

dichotic condition, the slope of forward masking is nearly constant for low frequency

signals up to 50 ms intervals, and the slope of backward masking curve is slightly greater

than zero from 50 to 15 ms (Figure 2.3). Thus, for both monotic and dichotic backward

37

and forward masking conditions, the change in slope occurred at approximately the same

place on the time scale in Elliot’s (1962b) study. Picket (1959), in a study of backward

masking, showed that with tone durations of 5 and 10 ms, large threshold increases

appear at silent intervals of less than 25 ms. He concluded that the duration of tone has

little effect on masking relative to the large effects of the tone-noise interval. The relation

between the signal threshold and noise-burst level appeared to be a linear one, confirming

the form of relation found by Samoilova (1959).

Besides pure tone and burst stimuli, impulsive stimuli have been used as either

probe or masker in several studies (Guttman et al., 1960; Raab, 1961; Babkoff and

Sutton, 1968; Ronken, 1970; Feth and O'Malley, 1977). Despite differences in the pulse

width and earphones used, the results with transients show several common features: for

most delays between the times of presentation of the masker and the probe pulse, forward

masking had a greater effect than backward masking (Raab, 1961; Babkoff and Sutton,

1968; Ronken, 1970; Feth and O'Malley, 1977). These results are not in agreement with

Elliot’s (1962b) study using white noise as masker and pure tones as signals. In spite of

the differences between Elliot’s (1962b) study and the other aforementioned studies, the

phenomenon is known as the asymmetry of non-simultaneous masking (Gaskell and

Henning, 1999), which refers to asymmetrical masking curves produced in forward

versus backward masking conditions.

2.5.1.3 Effects of Masker Bandwidth

Neurophysiological studies have shown that rate-level functions for single

neurons increases in slope with increasing noise bandwidth (Greenwood and Goldberg,

38

1970; Gilbert and Pickles, 1980; Sehalk and Sachs, 1980). The psychophysical data in

terms of the effect of bandwidth are not as straightforward as the physiological data.

Houtgast (1972) measured pulsation thresholds for a sinusoidal signal alternating with a

noise centered at the signal frequency, with a fixed spectrum level and variable

bandwidth. He found that the pulsation threshold at first increased with increasing

bandwidth and then decreased. He also found that whereas for the narrowest noise

bandwidth the pulsation threshold increased roughly 10 dB for each 10-dB increase in

masker level, at the widest noise bandwidth the increase was only about 7 dB per 10-dB

increase in the masker. This appears to show that the masking strength for a broadband

noise increases less than a narrow-band noise with an increasing level. Weber and Green

(1978) performed a similar experiment in forward masking and showed that the change in

threshold with the noise spectrum level was almost independent of bandwidth. Based on

the evidence, the difference in slope for the sinusoidal and noise maskers decreases with

the time interval and at the longest delay the slope for the sinusoid is significantly steeper

than that for the noise (Moore and Glasberg, 1983).

2.5.1.4 Effects of Duration of Stimuli

Zwislocki et al. (1959) reported masking functions for 1- kHz maskers and probes

for masker durations ranging from 4 to 1000 ms in a simultaneous masking condition.

They found that there was little effect of varying duration of masker. In a non-

simultaneous masking experiment, Elliott (1962a) used a broadband noise forward

masker, and compared thresholds for 5- and 10-ms sinusoidal signals (gated with 1-ms

ramps) at 2 kHz. She concluded that her results were consistent with Zwislocki et al.’s

39

(1959) hypothesis that thresholds did not depend on signal duration. However, as only

two short signal durations were tested, it is difficult to draw strong conclusions from her

results.

In contrast, other studies have suggested that signal duration may affect thresholds

in forward masking, even when the offset–offset interval is held constant. Thornton

(1972), using a 1170-Hz forward masker and a 1753-Hz signal, found that signal

thresholds decreased with increasing duration for durations between 10 and 20 ms in

roughly the same way as they did in quiet. Fastl (1979), using himself as the only

observer, found a decrease in threshold with increasing signal duration, except in the case

of the 4-kHz pure-tone masker when the signal was at the same frequency as the masker,

which he also ascribed to a ‘‘confusion’’ effect (Neff, 1985).

Oxenham (2001) studied the effects of signal duration in forward masking using

an adaptive forced-choice procedure. Signal thresholds in the presence of a broadband

forward masker were measured as a function of signal duration, with the time interval

between the masker offset and the signal offset (offset–offset interval) held constant at a

value between 4 and 102 ms. The results showed that the mean thresholds decreased by

nearly 14 dB as the signal duration increased from 2 to 7 ms. The experiment showed that

the mean thresholds decreased substantially when the signal duration increased between 2

and 20 ms. This finding was consistent with the previous studies (Thornton,1972).

Kidd and Feth (1982) described the effects of varying the duration of pure-tone

maskers in a forward masking paradigm. They studied the effect of masker duration on

forward masking and found that masking increased with increasing masker duration for

the range of durations used (35 to 500 ms). The rate of growth of forward masking as a

40

function of masker duration was greatest for relatively high masker levels and

frequencies. Their findings were in disagreement with the results reported by Fastl (1979)

and similar to those of Weber and Green (1978). They suggested that the inconsistency

might be due to the very brief duration probe that Fastl (1979) used.

In summary, according to the literature, the duration of masker and signal had

opposite effects on thresholds; detection thresholds decreased when the signal duration

increased (Oxenham, 2001; Thornton, 1972) and it increased with increasing masker

duration (Kidd and Feth, 1982; Weber and Green, 1978).

2.5.2 Mechanisms and Models Account for Non-simultaneous Masking

A number of physiological processes have been considered as possible

contributors to forward masking. These include reduced sensitivity (Duifhuis, 1973),

adaptation in the auditory nerve (e.g. Smith, 1977, 1979), efferent inhibitory processes

(e.g. Strickland, 2001), and the persistence of neural activity (Plomp, 1964; Moore et al.,

1988). None of these mechanisms has dominated the others, and scientists have decided

not to select one among these alternatives because all the mechanisms are likely to make

some contribution. Duifhuis (1973) argued that the response of the basilar membrane to

a masker takes a certain time to decay. Thus, in shorter time intervals between signal and

masker in forward masking, this may lead to a reduction in sensitivity of the signal.

Adaptation in the auditory nerve has been also proposed as a candidate for the neural site

of forward masking (Smith, 1977, 1979). Based on this assumption, the response of an

auditory nerve fiber declines or adapts during the time in which a relatively long duration

stimulus such as the masker (Bacon et al., 2002) is presented, whereas the response to a

41

brief increment in level does not adapt (Smith and Zwislocki, 1975; Smith, 1979).

Consequently, the neural signal-to-masker ratio increases as the signal is delayed from

the masker onset. Thus, this assumption may clearly describe a decrease in detecting

threshold of the signal at long time intervals in non-simultaneous masking.

Eventually, a number of aspects of auditory nerve adaptation resemble

psychophysical forward masking. For instance, the growth of adaptation with an

increasing stimulus level is nonlinear and eventually saturates, just as the growth of

forward masking is generally nonlinear, with signal threshold often increasing only

slowly as a function of masker level (Jesteadt et al., 1982; Moore and Glasberg, 1983).

Such resemblances have led many psychophysicists to refer to forward masking in terms

of neural adaptation (Duifhuis, 1973; Kidd and Feth, 1981; Jesteadt et al., 1982; Bacon,

1996; Nelson and Swain, 1996). However, some of the studies of forward masking in the

auditory nerve have demonstrated much less masking in individual auditory-nerve fibers

than is measured psychophysically (Relkin and Turner, 1988). Data obtained from

physiological studies of forward masking (Smith, 1977, 1979; Abbas, 1979; Harris and

Dallos, 1979) suggest that the physiological mechanism underlying forward masking can

also be an adaptation process in the hair cells or at the synapses between the hair cells

and neurons in the eighth nerve (Abbas, 1979; Smith, 1979). However, the fact that

cochlear implant patients show forward masking over a similar time scale as normal-

hearing listeners (Shannon, 1990) suggests that forward masking occurs at a higher stage

of processing than the inner hair cells.

One of the possible assumptions for the forward masking mechanism is based on

the function of the efferent system. One explanation is that the change in tuning with time

42

reflects the influence of the efferent system on the outer hair cells (OHCs) in the cochlea.

It has been suggested by several investigators that the OHCs may be involved in the

temporal effect of masking (Kimberley et al., 1989; McFadden and Champlin, 1990; von

Klitzing and Kohlrausch, 1994; Bacon and Liu, 2000; Strickland, 2001). In some of the

literature about psychophysical tuning, curves have used to clarify the mechanism

involving forward masking. A common finding in this literature was that forward

masking studies provided sharper tuning curves than those described for simultaneous

masking (Moore et al., 1984; Houtgast, 1972; Lutfi, 1984). Consistent with this

possibility are the findings that the temporal effect is reduced or absent in individuals

with either a temporary (Champlin and McFadden, 1989; McFadden and Champlin,

1990; Bacon and Hicks, 2000) or permanent (Kimberley et al., 1989; Bacon and

Takahashi, 1992; Turner and Doherty, 1997) cochlear hearing loss. Although the OHCs

themselves are not thought to change their response properties as a function of time, their

effectiveness may be modified by efferent neurons from the medial olivo-cochlear

system. These neurons synapse with OHCs, and as noted by Strickland (2001), the

sharpening of frequency selectivity with time can be caused by feedback from the

efferent system to the OHCs.

Another alternative view of forward masking mechanisms is that it is due to a

continuation, or persistence, of neural activity after the physical offset of the masker

(Plomp, 1964; Penner, 1974; Zwicker, 1984; Moore et al., 1988; Oxenham and Moore,

1994). The site of such masking is hypothesized to be higher than the auditory nerve, but

no specific mechanisms have been proposed. In summary, a number of peripherally or

centrally located contributors in the auditory system have been proposed to account for

43

forward masking. Oxenham (2001) has argued that it is difficult to separate the relative

contributions of these mechanisms experimentally. The mechanisms of forward masking

have not been fully understood, and they are still a matter of debate in the literature.

There are mainly two theoretical views of the backward masking mechanism.

The first assumption is that short term backward masking is mainly central in origin

(Samoilova, 1959; Raab, 1961; Elliott, 1962a, b; Deatherage &Evans, 1969) or that both

central and peripheral factors may contribute to backward masking (Dolan and Small,

1984). Evidence that backward masking can be observed with dichotic as well as monotic

presentations has been interpreted as indicating a central component of backward

masking (Elliott, 1962a, b). Dolan and Small (1984) suggested that the steeply sloping

initial portion of the function may be mediated by peripheral factors, while the more

gradually sloping later portion may reflect central factors. However, the proposal that the

initial and final portions of backward masking recovery functions can be attributed to

different mechanisms (peripheral and central, respectively) has remained untested.

Based on the second assumption, which is the most explicit theory of backward

masking, backward masking has a peripheral origin and occurs when the marker is

presented before the signal has been completely processed within the auditory nervous

system (Duifhuis, 1973). Duifhuis (1973) proposed that backward masking is mainly due

to an interaction of probe and masker excitation patterns in the cochlea. His theory

regarding the mechanical response at different points along the basilar membrane is

analogous to the responses of a set of linear band-pass filters (the concept of auditory

filters was discussed earlier in this section). Duifhuis (1973) suggested that the

44

overlapping of filter responses and consequent mutual interference is the primary basis

for backward masking.

2.6 Non-simultaneous Central Masking Experiment

As it was mentioned earlier in section 2.4, central making effect is measurable

with a binaural masking technique in a dichotic listening condition. In principle, in a

dichotic masking condition contralateral noise increases the hearing threshold in the

ipsilateral ear by at least three different mechanisms. These physiologic mechanisms

consist of (a) direct masking via acoustic crosstalk (crossover) (Caird et al., 1980;

Gibson, 1982), (b) an acoustic reflex due to contraction of the middle-ear muscles reflex

when the activator level exceeds 80 dB SPL at high intensity levels (Borg et al., 1984),

and (c) suppression of auditory nerve responses by moderate-level contralateral sound

that is mediated by MOC neurons (Fex, 1962; Wiederhold & Kiang, 1970; Warren and

Liberman, 1988). A contralateral masking effect at low levels of the masker cannot be

explained by crosstalk or attributed to the transcranial transfer (Micheyl et al. 1997;

Collet et al. 1990; Veuillet et al., 1991). The masker level is also lower than the level

required to produce a bilateral acoustic reflex. Lines of evidence have shown that at low

levels of the masker, the OCB effect can be obtained in subjects without acoustic reflex

(Veuillet et al., 1991; Moulin et al., 1993; Berlin et al., 1993). These findings indicate

that a contralateral masker below the levels at which acoustic reflex is elicited, can affect

detection thresholds via the third mechanism that is attributed to the activation of MOC.

The main requirements in central masking experiments is to present contralateral masker

at levels lower than the listener’s acoustic reflex threshold, and also to enhance interaural

45

attenuation by using insert earphones. In contrast to the traditional central masking

experiment, in a non-simultaneous making experiment the signal either precedes or lags

behind the masker. Results of the central masking effect have been reported using

different psychoacoustic methods, such as Békésy tracking (e.g. Zwislocki et al., 1968,

Smith et al., 2000), a modified method of limiting using ascending procedure (e.g Synder,

1973), and 2IFC adaptive methods (e.g. Mills et al., 1996). Regardless of the method

used for determining the threshold, a non-simultaneous central masking effect is

calculated by the following formula:

Amount of central masking = Detection threshold in quiet – Detection threshold with

contralateral masking.

2.7 Summary

In order to understand sensory processes, knowledge based on

psychophysiological findings of a given sensory phenomenon is necessary. This is due to

the fact that neurophysiological methods themselves are inadequate to determine the

nature of a phenomenon that is influenced by psychophysical parameters. As a result,

psychophysical methods, especially in higher animals and humans, appear more attractive

because factors measured by these methods determine the function of groups of many

neurons whose outputs are integrated in an undetermined fashion. Since central masking

is a psychophysical phenomenon, the neural function studied by this phenomenon can

reflect the kind of neural integration that is psychophysically meaningful. In this case,

central masking would become a useful bridge between psychoacoustic and

neurophysiological findings.

46

With the development of interest in the function of the efferent auditory system,

especially the OCB, a scientific issue has been raised regarding the influence of the

efferent system on central masking, and indeed, on many of the auditory tasks which

involve both ears (e.g. Warren and Liberman, 1989a; Micheyl et al., 1995; Puria et al.,

1996). As was mentioned earlier, central masking is one of the noninvasive methods of

testing OCB function that can be applied in human participants with normal auditory

function. It is assumed that the central masking effect and other binaural phenomena truly

reflect an interaction of the masker and signal in the auditory central nervous system, as

hypothesized by Zwislocki (1972, 1978), and it has been widely accepted that the central

masking effect is attributable to the activity of the efferent auditory system (e.g. Smiths et

al., 2000). Considering the fact that neural activation in the MOCB results in threshold

shifts in a central masking condition (Smith et al., 2000), comparing masking effect in

central masking versus monotic masking may show the MOCB’s influence on our ability

to detect a signal in noise. This comparison can be made in terms of signal frequency,

time disparity between signal and masker, and growth of masking.

It has been hypothesized that non-simultaneous masking is established more centrally

within central neural pathways (Zwicker, 1983). A non-simultaneous central masking effect

has not yet been reported in the literature. This condition indicates a situation where (a) the

intensity level of the noise is not high enough to produce crossover of sound energy (e.g.

Zwislocki et al., 1968), and (b) a signal is presented either after masker offset or before the

masker onset. The time disparity between the signal and the noise will affect the listener’s

ability to detect a signal in a noisy environment where both signal and masker are non-

simultaneously fluctuating in the time domain. This effect can be studied in a non-

47

simultaneous masking paradigm. The function of the efferent system under non-simultaneous

masking conditions has not been discussed in the literature. Thus, this study will provide a

better understanding of the function of the efferent system and can increase our knowledge of

efferent system function in humans.

In this study, the aim was to measure detection threshold shifts for the target tone in

human listeners with normal hearing, in non-simultaneous central masking and non-

simultaneous monotic conditions. Also, the purpose of the present study was to compare

threshold changes as a function of signal-to-noise time delay in a wide range of signal

frequencies, from low to high and at various masker levels. The aim was also to test the

growth of masking in both on-frequency and off-frequency masking in monotic and dichotic

listening conditions. Based on the results of the proposed study, further psychoacoustic and

speech perception experiments can be conducted utilizing speech stimuli. The findings can

provide the evidence of the influence of OCB on auditory perception and speech recognition

in noise. Results of the present study may be used in developing diagnostic tests for

evaluating patients with auditory processing disorders. Findings can also be used in further

neurophysiologic animal studies to reveal the response characteristics of a single efferent

fiber in a non-simultaneous masking condition.

48

CHAPTER 3: EXPERIMENTAL METHODS

3.1 Introduction

The efferent system may contribute to binaural signal processing in noisy environments.

This role has been identified by neurophysiologic studies on animals whose efferent

fibers, especially MOCB, were sectioned at the floor of the fourth ventricle (e.g. Kawase

and Berlin, 1993). In order to better understand the influence of MOCB on signal

detection in humans, it is essential to measure the phenomenon that is influenced by

activation of the efferent fibers. This phenomenon is called the central masking effect,

and can be measured by a noninvasive psychoacoustic method. Central masking, as a

psychophysical phenomenon, can reveal any modulation of sensitivity that can occur in

the cochlea by activation of the MOCB.

This study aimed to reveal (a) the threshold changes as a function of time

disparity between the signal and the masker in various signal frequencies, and (b) the

growth of masking as a function of the masker level in both on-frequency and off-

frequency conditions. These goals were addressed by comparing detection threshold

shifts, in dB, in dichotic versus monotic listening conditions. For the dichotic masking

condition, the experimental design was based on the conditions required for measuring

central masking. This condition indicates a situation where (a) the intensity level of the

noise is not high enough to produce crossover of sound energy (e.g. Zwislocki et al.,

1968) and (b) a signal is presented either after the masker offset or before the masker

49

onset. Acoustic characteristics of the stimuli for monotic masking were the same as for

dichotic conditions.

In the first part of the experiment, both non-simultaneous central masking and

non-simultaneous monotic masking were measured as a function of the time interval

between the signal and the masker, utilizing signal frequencies from low to high. In the

second part of the experiment, the growth of masking was measured in non-simultaneous

central masking and monotic masking conditions, utilizing a masker centered on and off

the frequency of the signal.

Regardless of the masking condition, the unmasked threshold of the signal or test

stimulus was first determined in quiet (without masker noise). This threshold was

considered as a baseline for further evaluations. Next, the masker was presented either

ipsilaterally (i.e. monotic masking) or contralaterally (i.e. central masking), and the signal

was presented simultaneously or non-simultaneously (i.e. forward and backward

masking) with the masker. The threshold for the signal was determined again. The

amount of masking was described as the difference in decibels between the signal

threshold in quiet (baseline) and masked threshold.

3.2 Variables

In the first experiment the aim was to compare detection threshold shifts in

dichotic masking versus monotic non-simultaneous masking conditions. The amount of

masking as a function of time delay was measured in a range of signal frequencies from

low to high. The detection threshold changes with the masker were considered as the

amount of masking in dB at each test condition. Thus, the detection threshold shift was

50

the dependent variable and signal-to-noise time interval was the independent variable.

Dichotic and monotic masking conditions also were considered as independent variables.

All variables were within-subject factors. Thresholds shift was measured across time

intervals equal to 0, 2, 5, 10, 20, and 50 ms. Threshold shift was also measured at signal

frequencies equal to 500, 1000, 2000, and 4000 Hz... The goal of the second experiment

was to compare the growth of masking in on- and off-frequency masking conditions.

Detection threshold shifts were measured with a masker centered at either 4000 Hz (on-

frequency) or 1000 Hz (off-frequency) in both simultaneous and non-simultaneous

masking conditions. The threshold shift was the dependent variable and the masker level

from 50 to 80 dB SPL, masker frequency, and signal to noise time delay of 0, 5, and 20

ms served as independent variables. Listening conditions, including monotic versus

dichotic, masking conditions, including simultaneous versus non-simultaneous were

independent variable in this experiment.

3.3 Listeners

Four female adults (22, 27, 35, and 41 years old) participated in the experiment.

The rationale for testing young adults was to avoid any threshold changes caused by

aging. Participants were selected from the student community at The Ohio State

University. None of the participants had a history of hearing impairment.

The participants were given the hearing screening test after informed consent to

was obtained. Otoscopic observation, immittance measurement, and hearing screening

audiometry were conducted in both ears of the listeners to verify normal hearing and

middle ear condition. All subjects had hearing thresholds less (better) than 15 dB at

51

audiometric octave frequencies between 250 to 8000 Hz. No air-bone gap more than 10

dB was shown between 250 to 4000 test frequencies in any subject. Immittance

measurements were obtained using an impedance audiometer (GSI TymoStar). Middle

ear pressure and static admittance for all listeners were within normal limits (Jerger et al.,

1974), which indicated normal middle ear function in all listeners. Contralateral acoustic

reflexes were present at a level equal to or higher than 85 dB HL. The maximum level of

the maskers was set at least 5 dB below the levels required for deriving acoustic reflexes,

which verified that threshold shifts resulted from contralateral masking were not

contaminated by the shift due to acoustic reflexes. All participants’ audiometric and

immittance measures are shown in Appendix A

Listeners who met all the aforementioned inclusion criteria were recruited into

this experiment following an approved Ohio State University Institutional Review Board

(IRB) protocol 2005B0234. All participants were informed about the details of the

experiment and were trained to perform the tasks. They were given a chance to ask

questions before starting the psychoacoustic experiment.

3.4 Acoustic Stimuli and Test Protocol

Acoustic stimuli, including the signal and the masker, were generated in

MATLAB, utilizing psychoacoustic software PsyLab version 2.1. The signal was a pure

tone at 500, 1000, 2000, and 4000 Hz with a total duration of 10 ms. The masker was a

two octave-band noise centered at the frequency of the signal with a total duration of 200

ms. The duration of both signal and masker was chosen based on the pilot data, so that

the greatest masking effect would be produced in both monotic and dichotic masking. In

52

off-frequency masking, a masker with the same duration was centered at 1000 Hz. The

signal frequency in off-frequency masking was 4000 Hz, which produced the greatest

central masking effect in the pilot study.

The hearing threshold was measured when, in separate trials, a signal was

centered at the noise envelope (i.e. simultaneous masking), after the masker offset (i.e.

forward masking), or before the masker onset (i.e. backward masking). The delay

between the signal and the masker in forward and backward masking refers to the signal-

to-masker time interval (∆t). Signal thresholds were measured for five signal to maker

intervals: 2, 5, 10, 20, and 50 ms. Figure 3.1 and 3.2 are schematic representations of the

simultaneous (∆t=0) and non-simultaneous (∆t = 2, 5, 10, 20, and 50 ms) masking

paradigms in this experiment.

The digitally generated stimuli, a sampling rate of 44.1 kHz, were passed through

a Digital Audio Corporation CARDELUXE digital-analog converter and programmable

attenuators Tucker Davis System PA4 (TDS PA4) before being combined by a custom

built mixer and presented via Ear Tone 3A insert earphones. Acoustic calibration was

performed before measuring masked and quiet thresholds. A Larson Davis sound level

meter (SLM) model 824 with a half inch microphone was used. The SLM was set to 1/3

octave filtering when calibrating masker levels. The stimulus levels were calibrated in a

2cc coupler.

53

Figure 3.1 Schematic diagram of simultaneous and forward masking conditions.

Figure 3.2 Schematic diagram of simultaneous and backward masking conditions.

Masker CONTRALATERAL EAR

IPSILATERAL EAR

(10 ms signal)

∆t=0

∆t=2

∆t=5

∆t=10

∆t=20

∆t=50

Masker CONTRALATERAL EAR

IPSILATERAL EAR

(10 ms Signal)

∆t=0

∆t=2

∆t=5

∆t=10

∆t=20

∆t=50

54

3.5 Psychoacoustical Procedure

All testing levels completed in the Psychoacoustics Lab in the Department of

Speech and Hearing Science at The Ohio State University. Signal detection thresholds

were measured using a 2IFC two-down one-up adaptive procedure that estimated 70.7%

on the psychometric function (Levitt, 1971). Each run consisted of 50 to 60 trials. Each

trial included two intervals. Both intervals contained the masker, and one interval also

contained the signal. Listeners were required to select the interval containing the signal.

The interval containing the signal was selected randomly on each trial. There was a 500-

ms delay between the two intervals in each trial and a 1-s delay between trials. For each

threshold determination, the starting level of the signal was set at 90 dB SPL for all

signals, as measured on a sound level meter prior to starting the experiment.

Listeners were seated in a sound-treated booth wearing insert earphones.

Participants faced a monitor showing two boxes that represent response choices. They

learned to respond to the tone presented in the test ear and ignore the noise in either the

opposite or the same ear. They were asked to choose the box that contains the target tone

by pushing a button on a PC mouse. They learned the correct response via visual

feedback presented after each of the trials.

The masker level was fixed in all tests and the level of the signal was changed

based on the subject’s responses. The signal level varied in a transformed-up-down

procedure (Levitt, 1971) and its direction of change depended on the listener’s responses.

The direction alternated back and forth between down and up. The direction change from

an local maxima to the next local minima was considered as one reversal. The signal

was reduced by 8-dB step sizes in the initial reversal. After each reversal, the step size

55

was halved until the minimum step size of 2 dB was reached. The run was terminated

after four reversals occurred with the minimum step size. Threshold was defined as the

mean level at the last four reversals. For each listener, threshold estimates were made

once for each condition and the mean and standard deviation of estimates were recorded.

Unmasked thresholds for the 10-ms signal were obtained using identical procedures and

equipment without the masker. Participants were asked to indicate which interval they

thought contained the signal. Signal thresholds in quiet were measured twice, and the

final threshold was the average of the two trials. The averaged values were used as a

reference for further threshold shift calculations.

Testing order for the different signal masker delays was determined randomly for

each participant. The thresholds were discarded and remeasured if the standard deviation

of the averaged responses was equal to or more than 2 dB. The configuration of the

responses in each trial was also checked for all subject responses. The configurations

with unusual peaks or hollows were discarded, and thresholds were remeasured until the

estimates met the criteria.

56

CHAPTER 4: RESULTS

This study aimed to compare central masking with monotic masking conditions,

in both simultaneous and non-simultaneous masking paradigms. The first part of the

results described below compares this study to a previous study (Elliot, 1962b) in terms

of monotic forward and backward masking as a function of signal-to-masker time

interval. The second part of the results compares the growth of masking with on-

frequency and off-frequency masker for monotic versus dichotic conditions.

4.1 Monotic Masking Findings Compare to Previous Study

Given the purpose of this study in comparing data for dichotic versus monotic

masking, the first objective was to replicate some of Elliot’s observations using non-

simultaneous masking paradigms. In 1962, Elliot measured monotic forward and

backward masking conditions utilizing three signals of 500, 1000, and 4000 Hz each with

a 7ms duration. The masker was a broad band white noise at 90 dB SPL. The measures of

threshold shifts in the present study are compared with Elliot’s findings in Figure 4.1.

The results shown in this Figure replicate previous findings. That is, the threshold of a

brief tone in one ear was elevated when a masker was presented to the same ear. The

masking observed was greater at short intervals between the masker and the signal.

Threshold shifts decreased in a non-linear manner when the delay between the masker

and the signal increased. Backward masking traces showed a steeper decrease than

57

Figure 4.1: Forward versus backward monotic masking. Threshold shifts averaged

across subjects and are shown in dB as a function of time interval in ms. Solid lines

represent Elliot’s (1962b) findings and dash-dotted lines represent the findings of present

study. Signal frequencies are shown in different colors. Data plotted at 0 ms time interval

is related to the signal centered at noise envelope.

forward masking traces at time intervals shorter than 10ms, and the threshold did not

change greatly at time intervals longer than 10 ms. Forward masking traces were flatter

than backward masking at shorter time intervals, and a threshold shift was observed from

0 to 20 ms in forward masking. Given this agreement between the findings of this

investigation with Elliot’s (1962b) study, dichotic masking measures were compared with

monotic measures in order to answer the questions addressed in the present study.

4.2 Effect of Signal-to-Noise Time Interval on Detection Threshold

The purpose of this part of the study was to quantify non-simultaneous masking in

monotic and dichotic masking conditions. Threshold shift was plotted as a function of the

58

time interval between the masker and the signal. The averaged data in both forward and

backward masking from four listeners are in shown Figure 4.2 for monotic and in Figure

4.3 for dichotic masking conditions. Data for individual participants and tables of

average data are included in Appendices B and C, respectively. Two zero points represent

simultaneous masking, which were included for both forward and backward masking.

The configuration and slope of the curves in monotic conditions were compared with


The amount of masking as a function of time interval was compared in forward

versus backward masking at various frequencies. Average responses for all signal

frequencies in the monotic masking condition revealed that greater threshold shifts

occurred for shorter intervals (Figure 4.2). The greatest monotic masking occurred at 500

Hz for both forward and backward masking conditions. A threshold shift of more than 10

dB occurred at time intervals shorter than 20 ms with 500 Hz signal frequency for

monotic forward masking. The monotic forward masking curve consisted of two distinct

portions, with a knee at 20ms. The initial part of the curves, from 2 to 20 ms, was steeper

than that from 20 to 50 ms. For monotic backward masking, however, detection

thresholds changed gradually from a 2 to 50 ms interval. The range of threshold changes

was limited to 2 to 4 dB from 2 to 20 ms in monotic backward masking.

For dichotic forward masking, the greatest threshold shift occurred for a signal

frequency of 4000 Hz (Figure 4.3). The initial part of curve at intervals shorter than 10

ms at this frequency was steeper than that at intervals longer than 10 ms. The shape of the

curves in dichotic backward masking did not show any clear masking effect from 2 to 50

ms .

59

Figure 4.2: Threshold shift as a function of masker level for the monotic masking

condition. The abscissa represents the time interval between the masker and the signal.

The ordinate represents threshold shifts in dB. The curves on the left side depict

backward masking while the curves on the right side represent forward masking.

Different values of the signal frequencies are denoted by the different colors. Standard

errors of the mean are presented by error bars.

The greatest amount of masking occurred in the simultaneous masking in both

monotic and dichotic conditions (Figure 4.8). The relationship between threshold shifts

and time interval was shown by separately determining the regression line fitted to the

data in monotic and dichotic non-simultaneous masking for various test signals. The

slope of the best fitted lines was compared in monotic versus dichotic conditions.

Figures 4.4 to 4.7 represent threshold shift curves, with linear regression lines

fitted to the mean data. Since monotic non-simultaneous curves showed two distinct

slopes at time intervals shorter and longer than 20 ms, a comparison was considered for

the two best lines fitted to the data at intervals from 2 to 20 ms and 20 to 50 ms. The than

slope of the curves were steeper at shorter time intervals in monotic forward masking in

60

Figure 4.3: Threshold shift as a function of masker level for the dichotic masking

condition. The abscissa represents the time interval between the masker and the signal.

The ordinate represents threshold shifts in dB. The curves on the left side depict

backward masking while the curves on the right side represent forward masking.

Different values of the signal frequencies are denoted by the different colors. Standard

errors of the mean are presented by error bars.

dichotic forward masking for 500Hz (-0.38 vs. -0.005 dB) and 1000Hz (-0.36 vs. -0.01

dB) signal frequencies (Figures 4.4 and 4.5). However, for 2000Hz and 4000Hz signals,

the slope of curves in dichotic forward masking was not similar to monotic forward

masking in terms of the slope for shorter time intervals (Figures 4.6 and 4.7).

The slopes of the lines at 2000 and 4000 Hz signal frequencies were -0.32 and

-0.36 dB in monotic versus 0.04 and -0.23 dB in dichotic masking, respectively. This

indicates smaller threshold changes in dichotic than in monotic forward masking from 2

to 20 ms at low signal frequencies. The slope of the best fitted line at 2000 Hz in dichotic

forward masking was positive, which shows a slight growth of roughly 1.5 dB in shorter

intervals.

61

Figure 4.4: Threshold shift as a function of time interval at 500 Hz. The curves on the left

side depict backward masking while the curves on the right side represent forward

masking. The linear regression lines fitted to data from 2 to 20 ms are shown with red

dotted line and those from 20 to 50 ms with green dashed lines for forward masking and

monotic backward masking conditions. The red dotted lines in dichotic backward

masking represent the best fitted line from 2 to 50 ms.

The dichotic forward masking had a gradual constant slope from 2 to 10 ms, and

was flattened for intervals longer than 10 ms. This provided a different knee point in

dichotic forward masking curve at 4000 Hz than curves at other signal frequencies. For

this reason, a new regression line was fitted to this curve from 2 to 10 ms. The slope of

this line was -0.58 dB, which is greater than the slope of the regression line for

monotic forward masking from 2 to 20 at this test frequency. This may indicate a steeper

threshold shift for dichotic versus monotic forward masking for shorter time intervals

with a high frequency signal.

62

Figure 4.5: Threshold shift as a function of time interval at 1000 Hz. The curves on the

left side depict backward masking while the curves on the right side represent forward

masking. The linear regression lines fitted to data from 2 to 20 ms are shown with a red

dotted line and those from 20 to 50 ms with green dashed lines for forward masking and

monotic backward masking conditions. Red dotted lines in dichotic backward masking

represent the best fitted line from 2 to 50 ms.

Monotic forward masking had a steeper slope than dichotic masking for all test

frequencies, except for 1000 Hz from 20 to 50 ms time intervals. The slopes of the curves

were -0.07, -0.07, and -0.09 dB for monotic masking and -0.23, -0.27, and -0.004 dB for

dichotic masking at 500, 2000, and 4000Hz, respectively. The slope of the curve at 1000

Hz was 0.035 in dichotic versus -0.096 in monotic forward masking. However, threshold

shift in this time interval was 1 dB in dichotic versus 3 dB in monotic masking.

Generally speaking, dichotic forward masking curves were flatter than monotic forward

masking curves in both short and longer time intervals. The only exception occurred for

the 4000Hz signal frequency, where dichotic masking showed a steeper slope than

monotic masking in time intervals shorter than 10 ms.

63




dotted line and from 20 to 50 ms with green dashed lines for forward masking and

monotic backward masking conditions. Red dotted lines in dichotic backward masking


For monotic backward masking, the slope of curves was steeper at shorter time

intervals at lower signal frequencies and became shallower at higher test frequencies. The

slope of the best fitted line from 2 to 20 ms was -0.19, -0.23, and -0.11 dB, at 500, 1000,

and 2000Hz, respectively. The slope remained fairly constant from 2 to 50 ms at 4000 Hz

for monotic backward masking, with a slope of -0.08 dB. Dichotic backward masking,

however, showed slight threshold changes across the time interval which ranged roughly

from 0 to 4 dB. The slope of the curves was nearly constant from 2 to 50 ms, and did not

show any knee point as the curves did in other masking conditions.

64




dotted line and from 20 to 50 ms with green dashed lines for forward masking condition.

The best fitted line to data from 2 to 10 ms for dichotic forward masking is shown with a

red dotted-dashed line. Red dotted lines in monotic and dichotic backward masking


4.3 Effect of Signal Frequency on Detection Threshold

One of the purposes of this experiment was to compare the effect of signal

frequency on dichotic versus monotic masking. Figure 4.8 displays the average threshold

shift in two masking conditions as a function of signal frequency, in which the signal and

masker were presented simultaneously.

A three-factor within-subject design was considered to analyze the effect of signal

frequency on threshold as a function of time interval for monotic and dichotic masking

conditions. A three-way repeated-measures analysis of variance (ANOVA) with signal

frequency (500, 1000, 2000 and 4000 Hz), time interval (0, 2, 5, 10, 20, and 50 ms), and

65

Figure 4.8: Threshold shift in simultaneous monotic and dichotic masking condition at

various signal frequencies. Different masking conditions are denoted by the different

colors. Standard errors of the mean are presented by error bars.

masking condition (monotic and dichotic) was completed. Greater threshold shift

occurred at 500 Hz in monotic forward masking while a 4000 Hz signal produced greater

threshold shift for dichotic forward masking [F(3,18)= 10.92; p<0.001; η2= 0.645].

Threshold shifts were significantly higher in monotic masking than in the dichotic

forward masking condition [F(1,6)= 1078.69; p<0.001; η2= 0.994]. A significant

interaction was observed between signal frequency and masking conditions (i.e. monotic

and dichotic) [F(3,18)= 10.350; p<0.001; η2= 0.633]. A pair-wise comparison confirmed a

significant effect at 500 Hz (p<0.05) and at 4000 Hz (p<0.05) from other test frequencies.

Mauchley’s test indicated that the assumption of sphericity was violated (p<0.05)

threshold shift mean differences across time intervals and degrees of freedom were

66

adjusted with a Greenhouse-Geisser estimate. There was also a significant difference in

threshold shift across time intervals [F(2.41,18)= 1122.34; p<0.001; η2= 0.995]. Pair-wise

comparisons confirmed the significant differences among most of the time intervals

(p<0.05) while the difference between 2 versus 10 ms and 5 versus 10 ms were not

significant (p>0.05). There was not a significant interaction between signal frequency

and time interval [F(3.82,90)= 1.46; p>0.05; η2= 0.196]. However, a significant interaction

effect was observed between the masking condition and time interval [F(2.406,90)= 840.29;

p<0.001; η2=0.993]. The overall results indicated a significant effect of signal frequency

on threshold shift, where this effect was not produced by similar test frequencies in

monotic versus dichotic masking. A low frequency 500-Hz signal was more efficient for

forward monotic masking while a high frequency signal at 4000 Hz was more effective

for dichotic forward masking condition across all time intervals.

For the backward masking condition, a significant effect for signal frequency was

also observed [F(3,18)= 17.92; p<0.001; η2= 0.749]. Pair-wise comparisons for signal

frequencies showed that this effect was significantly different only for the 500 Hz

frequency (p<0.001). A significant interaction was also obtained between the test

frequency and masking condition [F(3,18)= 16.16; p<0.001; η2= 0.7294]. However, there

was no significant interaction between the test frequency and time interval [F(3.657,90)=

3.657; p>0.05; η2= 0.109]. Although the time interval showed a significant main effect

[F(1,6)= 59.470; p<0.001; η2= 0.908], pair-wise comparisons confirmed that this effect

was significant only at 0 and 2 ms time intervals ( p<0.001). The overall results indicated

that threshold shift was significantly different only for a signal frequency at 500 Hz. This

might be due to the fact that there was not any clear backward masking effect in the

67

dichotic condition, and these findings indicated the effect of frequency for monotic

backward masking. Recall that a similar frequency effect was obtained at 500 Hz for

monotic forward masking.

The results of this part of experiment supported the assumption that the signals

with different frequencies were not equally masked in dichotic versus monotic masking.

Masking was greater at high signal frequency in dichotic conditions compare to monotic.

4.4 Monotic and Dichotic Masking in On- and Off-Frequency Masking Conditions

The goal of second part of the experiment was to compare growth of on-

frequency and off-frequency masking in monotic versus dichotic masking conditions.

Mean data are plotted in Figures 4.9 and 4.10. Data for individual participants and tables

of average data are included in Appendices D and E, respectively. and table of average

data . Both on-frequency and off-frequency functions in monotic masking showed a

gradual increment for a 0 ms time interval (Figure 4.9). For monotic masking, detection

thresholds increased slightly as the level of masker increased at 5 and 20 ms. However,

for off-frequency monotic masking at 20 ms, subtle threshold changes occurred across

the masker level. The masking effect grew slightly for all time intervals in on-frequency

dichotic masking (Figure 4.10). However, threshold changes were dramatically lower

than monotic masking and were limited to masker levels of 65 dB SPL and above. For

off-frequency dichotic masking, though, slight changes in detection were obtained only at

the 0ms time interval. Threshold shifts remained fairly constant for all masker levels at 5

and 20 ms time intervals, for off-frequency dichotic masking.

68

Figure 4.9: Threshold shift as a function of masker level for on-frequency and off-

frequency monotic masking condition. The signal frequency was 4000 Hz. The masker

was centered at 4000 and 1000 Hz in on-frequency and off-frequency masking

conditions, respectively. The curves on the left side display on-frequency masking while

the curves on the right side represent off-frequency masking conditions. Different values

of the time intervals are denoted by the different symbols. The circles, reverse triangles,

and squares represent 0, 5, and 20 ms, respectively. Standard errors of the mean are

presented by error bars.

A three-way repeated-measures analysis of variance (ANOVA) with masker level

(50 to 80 dB SPL in 5 dB increments), time interval (0, 5, and 20 ms), and masking

condition (on-frequency and off-frequency) was completed. The threshold increased

significantly with the masker level for both monotic [F(1.66,6)= 127.34; p<0.001; η2=

0.955] and dichotic [F(6,6)= 8.70; p<0.001; η2= 0.592] masking. However, pairwise

comparisons indicated that mean differences were significant at masker levels lower than

65 dB SPL in monotic masking (p<0.01). For dichotic masking, the mean differences

were significant for masker levels of 70 dB SPL and below (p<0.05). The main effect

was observed for time interval in both monotic [F(1.1,6)= 241.23; p<0.001; η2= 0.976] and

69

Figure 4.10: Threshold shift as a function of masker level for on-frequency and off-

frequency dichotic masking condition. The signal frequency was 4000 Hz. The masker

was centered at 4000 and 1000Hz in on-frequency and off-frequency masking conditions,

respectively. The curves on the left side display on-frequency masking while the curves

on the right side represent off-frequency masking conditions. Different values of the time

intervals are denoted by the different symbols. The circles, reverse triangles, and squares

represent 0, 5, and 20 ms, respectively. Standard errors of the mean are presented by error

bars.

dichotic [F(2,6)= 18.77; p<0.001; η2= 0.756] masking conditions. A significant

interaction between masker level and time interval was obtained in monotic masking

[F(1.92,6)= 51.68; p<0.001; η2= 0.996] while this interaction was not significant in dichotic

masking [F(12,6)= 1.55; p>0.05; η2= 0.205].

A significant difference was obtained between on-frequency and off-frequency

masking conditions in monotic masking [F(1,6)= 7.65; p<0.05; η2=0.560]. However, the

mean values were not significantly different between on-frequency and off-frequency for

dichotic masking [F(1,6)= 5.68; p>0.05; η2= 0.49]. There was not any significant

interaction between masker level and masking condition in monotic masking [F(1.66,6)=

70

1.22; p>0.0%; η2= 0.169], while a significant interaction was observed in dichotic

masking [F(6,6)= 2.85; p<0.005; η2= 0.322]. The overall result indicated that the growth of

masking was significantly different in on-frequency versus off-frequency monotic

masking for a 0 ms time interval. Although threshold increased significantly at masker

levels of 65 and above in dichotic masking, this effect was not significantly different in

on-frequency versus off frequency dichotic masking.

A correlation for the data revealed that the amount of masking and the masker

level were significantly related (Table 4.1). The only two exceptions occurred at 5 and

20 ms time intervals for off-frequency dichotic masking. “Pearson’s r” is shown in

Table 4.1.Linear regression lines fitted to the data are also shown in Figures 4.11 and

4.12. The slope of the best fitted lines was compared in on-frequency versus off-

frequency masking for both monotic and dichotic conditions. Slopes of the growth of

masking functions for on-frequency masking estimated by linear regression at 0, 5, and

20 ms were 1.1, 0.4, and 0.24 dB for on-frequency masking and 1.01, 0.29, and 0.16 dB

for off-frequency masking, respectively. The results indicated small changes in monotic

off-frequency masking versus on-frequency masking conditions.

Table 4.1: “Pearson’s r” for masking conditions and time intervals. Significant

correlations are shown with an asterisk.

Monotic Masking Dichotic Masking

On-frequency Off-frequency On-frequency Off-frequency

0ms 5ms 20ms 0ms 5ms 20ms 0ms 5ms 20ms 0ms 5ms 20ms

Pearson’s r .895* .996* .992* .995* .979* .975* .916* .921* .922* .898* .508 .372

Number 7 7 7 7 7 7 7 7 7 7 7 7

71

Figure 4.11: Threshold shift as a function of masker level for monotic on-frequency and

off-frequency masking conditions. The curves on the left side represent on-frequency

masking while the curves on the right side depict off-frequency masking. The linear

regression lines fitted to data from 50 to 80 dB masker levels are shown with green

dashed lines for 0 ms, red dotted lines for 5 ms, and blue dotted-dashed lines for 20 ms

time intervals.

The data from dichotic masking showed greater difference between on-frequency

and off-frequency masking compare to monotic masking, where threshold decreased

more steeply as a function of masker level in monotic masking (Figure 4.12). The slope

of curves in dichotic masking at 0, 5, and 20 ms intervals were 0.22, 0.16, and 0.12 dB

for monotic masking and 0.08, 0.04, and 0.02 dB for dichotic masking conditions,

respectively.

72

Figure 4.12: Threshold shift as a function of masker level for dichotic on-frequency and

off-frequency masking conditions. The curves on the left side represent on-frequency

masking while the curves on the right side depict off-frequency masking. The linear

regression lines fitted to data from 50 to 80 dB masker levels are shown with green

dashed lines for 0 ms, red dotted lines for 5 ms, and blue dotted-dashed lines for 20 ms

time intervals.

4.5 Summary of Results

The study aimed to compare the threshold shift as a function time interval in

monotic versus dichotic listening conditions. Dichotic forward masking curves were

flatter than monotic forward masking curves for all time intervals. The only exception

occurred for the 4000Hz signal frequency, where dichotic masking showed a steeper

slope than monotic masking in time intervals shorter than 10 ms. Dichotic backward

masking was not comparable to monotic backward masking because of the considerably

small threshold changes that occurred across time intervals in dichotic backward

masking. This may indicate an absent of backward masking in non simultaneous central

masking condition.

73

Another purpose of the study was to test for the effect of signal frequency on

monotic masking compare to dichotic masking. The results generally showed more

threshold shift at 500 Hz in monotic masking, while in dichotic masking the largest

threshold shift occurred at 4000Hz. For monotic masking, a 500 Hz signal was more

effective in eliciting threshold changes in both forward and backward masking conditions

(Figure 4.2). A signal frequency of 4000Hz was more effective than other test

frequencies for the dichotic forward masking condition (Figure 4.3). This effect was

greater in time intervals from 2 to 10 ms. Backward masking curves, however, did not

show any effect of signal frequency (Figure 4.3). This might result from the

ineffectiveness of backward masking to produce measurable threshold changes in


The study was also designed to compare on-frequency versus off-frequency

masking for forward monotic and dichotic masking conditions in time intervals of 0, 5,

and 20 ms. The results for dichotic masking showed that in off-frequency masking small

changes were obtained at 0 ms for masker levels higher than 65 dB SPL and that at

longer time intervals an off-frequency masker was not effective in producing any clear

changes in the threshold. In contrast, for monotic off-frequency masking, threshold

increased as a function of masker level with a slightly flatter slope compare to on-

frequency masking. The slope of the growth of masking functions was altered

dramatically with increasing time interval from 0 to 5 ms for both on-frequency and off-

frequency monotic masking. This pattern was not seen in dichotic masking. There, the

slope of curves did not show a great difference with increasing time interval, and it

74

remained fairly constant at all time intervals in both on-frequency and off-frequency

masking.

75

CHAPTER 5: DISCUSSION

5.1 General Discussion

The most effective experimental method to study the effects of the MOCB has

been electrical stimulation of the crossed olivocochlear bundle (COCB) at the floor of the

fourth ventricle. This approach has allowed researchers to estimate how the acoustic

characteristics of the stimulus can affect some efferent fiber responses. Physiological

findings revealed that the MOCB provides a mechanism for central feedback to and

control of activity at the auditory periphery (Galambos, 1956; Fex, 1959; Wiederhold and

Kiang, 1970; Gifford and Guinan, 1987, Zheng et al., 1999, Salo et al., 2003, Guinan et

al., 2005). It is suggested that this control is provided by the anatomical and functional

relationships of the outer hair cells (OHCs) with the efferent system (Warr, 1975; Warr &

Guinan, 1979, Mountain, 1980; Siegel and Kim, 1982; Brown et al., 1983; Brownell,

1990, Bucki et al., 2000; Yoshida, Liberman, 2000; May et al., 2002).

Some further insights into the nature and practical implications of the efferent

system were gained through psychoacoustic experimentation. Despite the thorough

description of the efferent system anatomy and the extent of the physiological findings on

MOCB function, the functional role of the MOCB has been addressed by surprisingly

few psychophysical masking studies (Strickland and Viemeister, 1995; Lidén et al., 1959;

Blegvad, 1967; Zwislocki et al., 1968; Zwislocki, 1972, 1978; Kawase et al., 2000; Smith

et al., 2000). In these experiments, the effect of MOCB stimulation was examined in the

76

presence of masking noise. This approach commonly involved using a masker with low

intensity level, and revealed two effects of the MOCB on hearing detection threshold.

One is considered as an enhancing effect, called the antimasking effect (Kawase and

Liberman, 1993), and the other, suppressive effect is known as central masking (Wegel

and Lane, 1924; Zwislocki et al., 1968). Psychophysical data suggest a role for the

MOCB in central masking, which was confirmed by central masking findings on efferent

sectioned macaque monkeys (Smith et al., 2000).

Previous physiological and psychophysical studies have shown that a contralateral

masking effect was eliminated when the MOC fibers were sectioned at the floor of the

fourth ventricle (Kawase & Liberman, 1993; Warren and Liberman 1989a; Bonfils et al,

1986a, b; May et al., 2004; Scharf et al. ;1997; Giraud et al., 1995; Zheng et al.,2000,

Smith et al., 2000). These findings indicate that contralateral masking produces changes

in cochlear mechanics that are known to be mediated by the MOC fibers.

Zwislocki (1971), found that central masking is affected by the temporal

relationship between the signal and the masker. In that study, the signal was introduced

after the onset of the masker. Threshold shift was measured as a function of delay

between the onsets of both stimuli. However, the signal was not temporally separate

from the masker that is, both stimuli ended simultaneously. Central masking has not

been studies using non-simultaneous masking paradigms.

One may ask why it is important to investigate the central masking effect under a

non-simultaneous masking paradigm. There are many important acoustic events that

occur in rapid succession, such as phonemic segments in a word or formant transitions in

a consonant-vowel sound. Our ability to perceive these events depends on the temporal

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relationship between consecutive stimuli in a normal listening environment. One example

of this environment includes listening to speech in background noise. A masker that

occurs roughly within 100 ms before or after a signal can interfere with signal recognition

(Massaro and Burke, 1991). This phenomenon, known as non-simultaneous masking,

plays an important role in many auditory phenomena including the ability to detect a

target sound and sound localization (Guttman et al., 1960; Elliot, 1962 a,b; Gaskell &

Henning, 1999). Given that central masking reflects MOCB activation, measuring a non-

simultaneous central masking effect can clarify the influences of MOCB functioning on

signal detection when one is exposed to rapidly varying various acoustic stimuli. This

would approximate the acoustic environment that listeners are exposed to in their

everyday lives.

The experiment reported here was completed to determine the central masking

effect in normal listeners under non-simultaneous masking paradigms. One of the goals

of this research was to demonstrate the influence of the time delay between the masker

and the signal on central masking. It also aimed to determine if the effects of time delay

and signal frequency on central masking were comparable to similar influences on

monotic masking. The purpose of the second part of the experiment was to test the

compare the growth of masking with on-frequency and off-frequency maskers for central

and monotic masking.

5.1.1 Effects of Time Interval and Signal Frequency

Limited findings exist that compare monotic with dichotic masking conditions.

Two of the pioneer studies were conducted by Elliot (1962 a,b). In a series of tests, she

78

compared the detection threshold shifts of a pure tone in white noise at high intensity

levels. She demonstrated that the amount of masking was greater in monotic than in

dichotic conditions. Elliot’s results also showed that masking disappeared in a dichotic

condition at time intervals longer than 15 ms. Masking occurred, albeit very slight, at

time intervals as long as 50 ms in the monotic condition.

The results of this experiment were in agreement with Elliott’s findings. The

present study demonstrated that threshold shifts were significantly greater in monotic

compare to dichotic conditions. The masking effect was also very small in time intervals

equal to or longer than 10 ms in dichotic forward masking. However, monotic forward

masking occurred at time intervals as long as 20 ms. The main disagreement between the

present study and Elliot’s findings was seen for backward masking conditions. She

reported a greater backward than forward masking effect in both monotic and dichotic

listening. In the experiment, dichotic forward masking in her experiment, in normal

hearing listeners was practically nonexistent.

Elliot’s (1962b) findings for backward masking vs. forward masking were also in

disagreement with those of Raab (1961) and Chistovich and Ivanova (1959), where

backward masking showed a smaller amount of threshold shift than forward masking. It

has been suggested that backward masking was a weak effect in trained listeners, and

only causes an increase in the lowest detectable level of the signal when the signal is

within 20 ms or so of the onset of the masker (Oxenham and Moore, 1994). This

disagreement among backward masking studies may result from the differences between

listeners in terms of their experience in psychophysical studies. All of the participants in

this study, except for one, were trained listeners who had participated in previous

79

experiments in the Psychoacoustics Laboratory in the Department of Speech and Hearing

Science. Thus, we expected a lower amount of masking in backward versus forward

masking conditions in this experiment.

Another disagreement between Elliot’s findings in backward masking and the

results in this study was found in the dichotic masking condition. In the present study,

very small nonsystematic changes were observed in dichotic backward masking, which

did not indicate any clear masking effect in this condition. This finding is in agreement

with the neurophysiologic findings of MOCB activation. Findings from the literature

have shown that the suppression produced by electrical stimulation of the olivocochlear

bundle requires from 50 to 100 ms to develop (Fex, 1962; Wiederhold & Kiang, 1970).

Moreover, studies on contralateral suppression of evoked otoacoustic emissions (EOAEs)

have shown that a steady-state level of suppression was reached within 50 ms to 2

seconds of the introduction of a contralateral steady-state broad band noise (Puria et a.,

1996). Contralateral suppression did not exist before introducing the noise or within 2 ms

after starting a 30 ms noise (Tavartkiladze et al., 1993). Recall that contralateral

suppression of OAEs is attributed to the activation of OCB (Berlin et al., 1993, 1994;

Kujawa et al., 1993; Puel and Rebillard, 1990).

The dichotic masking condition in the present study represents a central masking

effect that is assumed to be mediated by the MOCB. Given that OCB activation will

develop within 2 ms of presenting a contralateral acoustic stimulation, this can lead to a

lack of backward central masking, which was confirmed in this experiment. In Elliot’s

study, the contralateral masker was presented at levels higher than that was used in the

present study (90 dB SPL vs. 75 dB SPL). This might have added a peripheral component

80

(transcranial physical stimulation) to the masking effect, which in turn led to noticeable

backward masking at short time intervals in her study.

One of the aims of the present experiment was to compare the effect of signal

frequency in monotic versus dichotic masking. There are some contradictions with regard

to the effect of signal frequency on non-simultaneous masking in the literature. Some

studies have shown greater forward masking at high frequencies, including 2000 to 8000

Hz, particularly at relatively long signal delays (Harris and Rawnsley, 1953; Harris et al.,

1958). In contrast, other researchers have reported greater forward masking at very low

frequencies vs. at high frequencies (Elliott, 1962 a,b; Jesteadt et al., 1982).

A similar disagreement also exits between studies on the effects of signal

frequency on backward masking. Some researchers have demonstrated greater backward

masking with low frequency signals (Dolan and Small, 1984; Duifhuis, 1973, Samoilova,

1956; Elliot, 1962b), while others have shown the opposite effect (Sherrick and Albernaz,

1961). These differences may have resulted from psychoacoustic procedure and

participants’ listening experience. The effect of signal frequency reported in the present

study indicated a significant difference between dichotic and monotic forward masking at

the highest (4000Hz) and the lowest (500Hz) signal frequencies. These results are

consistent with those investigations which demonstrated greater non-simultaneous

monotic masking with low frequency signals (Dolan and Small, 1984; Duifhuis, 1973,

Samoilova, 1956; Elliot, 1962b; Jesteadt et al., 1982).

For non-simultaneous dichotic masking, findings are in agreement with

anatomical and neurophysiologic findings of OCB, as well as psychophysical findings in

central masking. Anatomical findings have shown a larger number of MOCB projections

81

to the middle turn of the cochlea. Higher density of MOCB fibers in the middle turn of

the cochlea can result in greater neural activity for efferent fibers with mid to high (2 to 4

kHz) characteristic frequency (Guinan et al., 1983; Velenovsky and Galttke, 2002). This

anatomical feature of MOCB fibers may have resulted in greater central masking at 4000

Hz in the present study. Studies of the suppression of OAEs have also shown greater

contralateral suppression between 1 to 4 kHz, which is evidence of greater MOCB

activation in this frequency range (Berlin et al., 1993; Collet et al., 1990; Norman &

Thornton, 1993). Moreover, psychophysical central masking studies have shown a

general enhancement in the masking effect with increasing signal frequency (Ingham,

1959; Dircks & Malmquist, 1965; Sherrick and AIbernaz, 1961; Studebacker, 1962;

Dirks & Norris, 1966ì; Mills et al., 1996; Palva, 1954; Lidén et al., 1959). In general, the

effect of frequency on central masking in this experiment is consistent with other

neurophysiologic and psychophysical literatures. The results also confirm the influence

of OCB activation in contralateral masking, where other known contralateral masking

origins, including crossover and acoustic reflex, are excluded.

5.1.2 On-frequency versus Off-frequency Masking

The second part of this experiment provided a comparison of on-frequency versus

off-frequency masking, for forward monotic and dichotic listening in time intervals of 0,

5, and 20 ms. The aim of this part of study was to support two hypotheses. First, the

growth of on-frequency masking in dichotic listening occurs at a slower rate than in a

monotic condition. Second, the masking effect in an off-frequency dichotic condition

would not exist or would be very small at all time intervals compared to on-frequency

82

masking. If these hypotheses were confirmed, it would demonstrate how MOCB

activation influences thresholds with a non-simultaneous contralateral masker as a

function of masker level.

Previous psychoacoustic experiments have shown that both on-frequency and off-

frequency monotic listening conditions result in a linear growth of masking at higher

masker levels (Plack and Oxenham, 2000). Oxenham and Plack (2000) demonstrated that

the slope of masking functions became shallower as the delay between the masker and

the signal was increased. The results presented in this experiment were consistent with

the literature (Plack & Oxenham, 2000; Oxenham & Plack, 2000). The slope of the

growth of masking changed slightly in off-frequency conditions compared to on-

frequency monotic listening. These changes were seen at various time intervals. The

threshold generally decreased with increasing masker-signal delay for a given masker-

signal level. These results were in line with previous findings (Oxenham & Plack, 2000).

Zwislocki (1967) demonstrated that in dichotic masking, the threshold shift

increased near the masker onset with masker intensity, at a rate of three to four times

slower than the growth of monotic masking. No study has specifically attempted to

investigate the growth of masking in non-simultaneous central masking. Results of the

present study were in agreement with Zwislocki’s (1967) finding at a 0 ms time interval.

The growth of masking in on-frequency condition occurred at a rate of four to five times

slower than monotic masking. However, this difference in the growth of masking

changed in non-simultaneous masking conditions. The difference of masking function

slopes between monotic and dichotic forward masking ranged from 0.3 to 0.1 dB, which

was less than the difference in simultaneous masking conditions (i.e. 0.9). Recall that the

83

masking effect at high frequency signals in non-simultaneous monotic masking was

smaller than at low frequencies. In contrast, the greatest non-simultaneous masking effect

occurred using high frequencies in dichotic listening. Given these results, the

similarities in slope of the masking growth in non-simultaneous monotic and dichotic

conditions can be attributed to a frequency effect. This may have led to a smaller

difference in the growth of masking between monotic and dichotic listening in forward

masking.

One of the common findings in the growth of masking in dichotic compared to

monotic masking, is smaller changes in threshold shifts as a function of increasing

masker levels. Single neuron recording in cats resulted in a few dB attenuation for

ipsilateral stimulus, after presenting contralateral acoustic stimulation to the efferent units

(Warren & Liberman, 1989a). The mean level of these attenuations were reported as 4.5,

5.0, and 3.9 dB shifts in neural discharge for low-, medium-, and high-spontaneous rate

units, respectively. These values are comparable with the findings in psychophysical

central masking studies. Zwislocki (1972) compared the normalized firing rates of four

neural units located in various parts of the superior olive with the median data from

central masking as a function of sound intensity. He demonstrated a noticeable agreement

between the two groups of data. He concluded that the characteristics of neurons of the

superior olive were reflected in central masking characteristics.

Other psychophysical central masking data have confirmed these results, by

demonstrating a low rate of growth of masking in central masking. Sherrick and Albernaz

(1961) reported an approximately 1 dB increase in threshold shifts for each 10-dB

increment in the masker level. In another study, Dirks and Norris (1966) found roughly a

84

2 dB change in threshold for each 15-dB increase in the masker level. The data of the

present study are consistent with both the physiological and psychophysical studies. For

on-frequency dichotic masking, the threshold shift increased approximately 2 dB for each

15-dB masker level increment at 0ms on-frequency masking. The present experiment also

demonstrated that the growth of masking curves became flatter with increasing time

intervals. Thresholds changed about 1 dB with a 10 dB increase in the masker level at 5

and 20 ms intervals. However, for off-frequency dichotic listening, a 0.5-dB increase was

shown in the 0 ms interval.

No clear changes in threshold were observed during off-frequency dichotic

listening when there was a time disparity between the masker and the signal. These

results are in agreement with other behavioral central masking studies. Zwislocki and

colleagues (1967, 1968) showed that the threshold shift produced by the contralateral

masker increased when the frequency of the masker approached the frequency of the

signal. Their reported data revealed that the maximum threshold shift occurred at a

masking frequency equal to or slightly lower than the signal frequency. They indicated

that the most masking occurred in a small range of frequencies around the masker

frequency. This frequency range was quite close to critical bandwidth (Zwislocki et al.,

1968). Mills and his associates (1996) confirmed these results. The masking observed in

their experiment was greatest when the frequency of the masker was equal to the

frequency of the signal.

Physiological findings are in agreement with psychophysical reports. The

suppression of auditory nerve-fiber response with contralateral acoustic stimulation has

been shown to be maximal for near characteristic frequency (CF) (Warren & Liberman,

85

1989b). Suppression typically dropped to a small fraction of its maximum value when the

contralateral tone frequency reached one octave above or two octaves below CF.

Electrical stimulation of the OCB also revealed that on-CF tones suppressed ipsilateral

responses considerably more than those to off-CF tones (Wiederhold, 1970; Guinan &

Gifford, 1988b). Given the frequency distribution of central masking, no clear masking

effect occurred in off-frequency dichotic conditions at all time intervals in the present

experiment. The only exception was a 4-dB threshold shift at 75 to 80 dB SPL masker

levels, at a 0 ms interval. This might have resulted from the spread of excitation patterns

on the basilar membrane with a low frequency maker at high levels, which has led to a

small threshold shift.

5.2 Conclusions

In the first part of the experiment, threshold changes in non-simultaneous central

masking were compared with monotic masking. The results indicated that forward central

masking decreased as a function of the masker-signal interval. In contrast to monotic

listening, backward masking did not occur in central masking. This result was in

agreement with physiological findings of MOCB activation time course, and suggested

the influence of MOCB function on non-simultaneous central masking. Central masking

was greater for high frequency signals. This effect was demonstrable when the signal and

the masker did not occur simultaneously. This finding indicated that non-simultaneous

central masking is a frequency dependant phenomenon.

In the second part of the experiment, the growth of monotic and dichotic forward

masking was compared, using an on-frequency masker and a masker well below the

86

signal frequency for masking intervals of 0, 5, and 20 ms. In contrast to monotic

listening, threshold changes were very small as a function of masker level for on-

frequency central masking. In addition, off-frequency masking almost did not occur for

forward central masking at all time intervals. The results shown in the present experiment

were in line with previous physiological and psychological experiments on MOCB

functioning, and suggest a descending influence of hearing sensitivity by means of the

efferent system. This influence may exist even when the masker and the signal do not

occur simultaneously. As a result, MOCB activity may alter intensity encoding by the

peripheral auditory system, which may likely affect intensity perception in a noisy

environment.

5.3 Implications for Future Research

The suppression effect of contralateral stimulation has implications for the

investigation of many auditory phenomena involving binaural coding. The conclusion

based on the present findings was limited to the data collected from normal hearing

listeners. Clearly, the results would have been strengthened if they had included the

results from patients who had some evidence of efferent system dysfunction. Patients

who have undergone vestibular neurotomy or neurectomy surgery can be considered as

surgically de-efferented subjects. Also, those who did not show contralateral suppression

in otoacoustic emission, such as patients with central auditory processing disorders

(CAPD), may considered as suitable candidates for future studies.

It should also be noted that generalization of the findings is limited to the age

group of young adults. Age-related change was not considered in this experiment. Given

87

the effect of age on hearing thresholds, especially at high frequencies, the implications of

non-simultaneous central masking may be limited to normal hearing adults. Determining

the developmental effect on MOCB functioning using a non-simultaneous central

masking experiment may also lead to an improvement in predicting binaural processing

disorders in children.

The importance of studying efferent system function arises from the fact that this

system may play an important role in speech recognition in a noisy environment. This

experiment attempted to study the influence of MOCB activation by using pure tones in

acoustic events where the signal and the masker do not occur simultaneously. However,

in a normal listening environment one is exposed to complex sounds such as speech.

Studying non-simultaneous central masking with complex sounds can provide better

prediction of MOCB influence on intensity encoding in a noisy environment. Central

masking can be measured utilizing complex sounds, such as synthesized vowels, with a

contralateral white noise. Such stimuli and information are provided in a psychophysical

experiment, and in combination with electrophysiologic techniques can be useful in a

wide range of studies of the efferent system.

88

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107

APPENDIX A: INDIVIDUAL AUDIOMETRIC AND IMMITTANCE AUDIOMETRIC

RESULTS

108

Table A.1: Audiometric and Immittance Audiometric Results for Subject 1.

Signal Frequency

(Hz)

Signal frequency

(Hz) Absolute

Threshold (dB

HL) 0.5 1 2 4

Contralateral

Acoustic Reflex

Threshold (dB

HL) 0.5 1 2 4 E.C.V M.E.P

Peak

Ytm

Right Ear 5 5 0 5 Right Ear NR NR NR NR 0.8 -15 0.4

Left Ear 15 10 5 5 Left Ear NR NR NR NR 0.9 -20 0.3


Signal Frequency

(Hz) Signal frequency (Hz) Absolute

Threshold (dB

HL) 0.5 1 2 4

Contralateral

Acoustic Reflex

Threshold (dB

HL) 0.5 1 2 4 E.C.V M.E.P

Peak

Ytm

Right Ear 5 5 0 0 Right Ear 100 100 100 90 0.9 -35 0.3

Left Ear 5 0 0 0 Left Ear 95 95 85 90 0.9 -15 0.3


Signal Frequency

(Hz)

Signal frequency

(Hz) Absolute

Threshold (dB

HL) 0.5 1 2 4

Contralateral

Acoustic Reflex

Threshold (dB

HL) 0.5 1 2 4 E.C.V M.E.P

Peak

Ytm

Right Ear 10 0 5 15 Right Ear 85 85 85 90 0.7 0 0.4

Left Ear 5 0 5 5 Left Ear 90 85 90 90 0.6 15 0.4

109


Signal Frequency

(Hz)

Signal frequency

(Hz) Absolute

Threshold (dB

HL) 0.5 1 2 4

Contralateral

Acoustic Reflex

Threshold (dB

HL) 0.5 1 2 4 E.C.V M.E.P

Peak

Ytm

Right Ear 10 15 15 10 Right Ear 100 90 95 90 0.9 15 0.5

Left Ear 10 15 10 20 Left Ear 90 85 90 85 0.9 10 0.4

110

APPENDIX B: INDIVIDUAL DATA FOR THRESHOLD SHIFT AS A FUNCTION

OF TIME INTERVAL

111

Figure B.1: Threshold shift as a function of time interval for monotic masking in subject

1. The curves on the left side depict backward masking while the curves on the right side

represent forward masking.

Figure B.2: Threshold shift as a function of time interval for dichotic masking in subject



112







113







114







115

APPENDIX C: AVERAGE DATA FOR THRESHOLD SHIFT AS A FUNCTION OF

TIME INTERVAL

116

Table C.1: Mean, standard deviation, and standard error of the data in simultaneous

masking condition.

Monotic Dichotic Signal

Frequency (Hz)

Mean Standard

Error Standard

Deviation Mean Standard

Error Standard

Deviation

500 62.80 0.69 1.38 4.09 0.62 1.25

1000 57.93 0.54 1.10 4.92 0.89 1.78

2000 55.91 1.74 3.47 5.8 1.20 2.37

4000 52.96 1.95 3.91 8.67 1.37 2.75


frequency in forward masking condition.

Monotic Dichotic

∆t (ms) Mean Standard

Error

Standard

Deviation

Mean Standard

Error Standard

Deviation

2 19.24 1.61 3.22 3.16 0.87 1.73

5 18.44 1.19 2.38 3.44 0.69 1.37

10 16.49 1.43 2.87 3.23 0.59 1.18

20 12.50 0.71 1.41 3.17 0.24 0.48

50 10.23 0.61 1.22 2.48 1.10 2.18


frequency in backward masking condition.

Monotic Dichotic


Error

Standard

Deviation

Mean Standard

Error Standard

Deviation

2 13.97 1.51 3.02 2.10 0.86 1.72

5 13.80 2.24 4.48 3.93 0.70 1.40

10 12.59 1.89 3.80 3.46 0.49 0.97

20 10.66 1.60 3.20 3.08 1.47 2.93

50 10.18 2.13 4.25 1.27 1.10 2.20

117



Monotic Dichotic


Error

Standard

Deviation

Mean Standard

Error Standard

Deviation

2 14.97 1.12 2.24 1.88 0.65 1.31

5 11.76 0.31 0.61 1.26 0.98 1.96

10 10.02 0.71 1.42 2.16 0.52 1.05

20 7.86 0.69 1.38 1.37 1.07 2.13

50 4.97 0.28 0.55 2.41 0.56 1.13



Monotic Dichotic


Error

Standard

Deviation

Mean Standard

Error Standard

Deviation

2 8.90 2.96 5.92 1.70 0.64 1.29

5 7.82 2.10 4.20 2.30 0.87 1.74

10 5.64 2.82 5.65 2.49 0.43 0.86

20 4.61 2.05 4.09 3.04 0.47 0.94

50 4.68 1.54 3.08 2.82 0.36 0.73



Monotic Dichotic


Error

Standard

Deviation

Mean Standard

Error Standard

Deviation

2 14.38 1.01 2.03 1.70 1.00 2.00

5 12.65 0.52 1.05 0.68 0.56 1.11

10 10.30 1.04 2.07 1.20 0.74 1.50

20 8.50 1.05 2.11 2.03 0.26 0.52

50 5.91 0.23 0.46 1.22 0.77 1.54

118



Monotic Dichotic


Error

Standard

Deviation

Mean Standard

Error Standard

Deviation

2 6.29 1.11 2.23 2.75 0.99 1.98

5 6.99 2.20 4.40 2.23 1.03 2.07

10 6.00 2.97 5.94 2.51 0.69 1.38

20 4.67 1.68 3.36 2.85 0.70 1.39

50 5.33 1.67 3.35 2.34 0.17 0.34



Monotic Dichotic


Error

Standard

Deviation

Mean Standard

Error Standard

Deviation

2 14.61 1.73 3.46 7.30 1.29 2.59

5 13.84 0.89 1.79 5.55 1.02 2.04

10 11.80 1.39 2.80 2.65 0.63 1.27

20 8.30 1.78 3.56 2.86 0.62 1.24

50 5.60 1.67 3.35 2.75 0.48 0.96



Monotic Dichotic


Error

Standard

Deviation

Mean Standard

Error Standard

Deviation

2 8.00 2.81 5.62 2.14 1.24 2.47

5 6.89 2.91 5.83 1.41 0.65 1.29

10 6.20 2.29 4.58 0.59 1.18 2.36

20 6.00 3.17 6.34 1.77 0.52 1.04

50 3.74 0.56 1.11 0.84 0.86 1.73

119

APPENDIX D: INDIVIDUAL DATA FOR GROWTH OF MASKING WITH ON-

FREQUENCY AND OFF-FREQUENCY MASKERS

120

Figure D.1: Growth of masking with on-frequency and off-frequency maskers for subject

1. The curves on the left side depict monotic masking while the curves on the right side

represent dichotic masking. Filled symbols represent on-frequency and unfiled represent

off-frequency masking. Circles, triangles, and squares represent 0 ms, 5 ms and 20 ms

time intervals, respectively.






121











122

APPENDIX E: AVERAGE DATA FOR GROWTH OF MASKING WITH ON-

FREQUENCY AND OFF-FREQUENCY MASKERS

123


off-frequency masking condition in 0 ms ∆t.

On-frequency Masking Off-frequency Masking

Masker

Level (dB SPL)

Mean Standard

Error

Standard


Error

Standard

Deviation

50 23.02 2.44 4.88 13.55 4.58 9.15

55 31.83 2.21 4.42 18.48 5.53 11.06

60 37.56 2.35 4.70 24.92 5.87 11.75

65 43.20 2.94 5.88 31.01 5.00 10.00

70 48.77 2.51 5.01 35.38 4.94 9.90

75 52.96 1.95 3.91 35.38 1.94 3.88

80 56.47 1.74 3.48 44.13 2.26 4.52




Masker

Level (dB SPL)

Mean Standard

Error

Standard


Error

Standard

Deviation

50 3.43 1.28 2.56 1.42 1.27 2.53

55 5.09 0.73 1.46 1.47 1.66 3.33

60 7.38 1.01 2.01 3.17 1.72 3.43

65 9.17 0.98 1.97 4.57 1.75 3.50

70 11.24 1.05 2.11 7.06 1.58 3.16

75 13.84 0.89 1.79 8.64 1.92 3.83

80 14.64 0.56 1.12 8.82 1.15 2.30

124




Masker

Level (dB SPL)

Mean Standard

Error

Standard


Error

Standard

Deviation

50 2.93 1.24 2.48 1.33 1.09 2.17

55 3.17 0.62 1.24 1.93 1.35 2.71

60 4.98 0.94 1.88 1.90 1.34 2.68

65 5.64 0.70 1.40 2.79 1.21 2.41

70 7.24 0.77 1.52 4.06 1.50 3.01

75 8.29 1.78 3.56 4.94 1.84 3.68

80 9.78 0.99 1.98 5.94 1.19 2.38




Masker

Level (dB SPL)

Mean Standard

Error

Standard


Error

Standard

Deviation

50 1.77 0.84 1.69 1.93 0.08 0.16

55 1.89 0.68 1.36 2.14 0.77 1.54

60 3.08 0.42 0.84 2.21 0.47 0.93

65 4.00 0.38 0.77 2.39 0.74 1.49

70 8.67 1.37 2.75 2.52 0.91 1.82

75 8.68 1.37 2.75 3.54 0.53 1.06

80 6.52 1.72 3.44 4.46 0.85 1.69

125




Masker

Level (dB SPL)

Mean Standard

Error

Standard


Error

Standard

Deviation

50 1.08 0.30 0.61 1.33 0.46 0.93

55 1.54 0.61 1.22 0.03 1.23 2.46

60 1.4 0.24 0.47 1.30 0.64 1.28

65 2.19 0.91 1.83 -0.13 0.40 0.81

70 4.62 1.17 2.35 1.15 0.29 0.58

75 5.56 1.02 2.04 1.81 0.21 0.42

80 4.94 1.73 3.47 2.00 0.38 0.76




Masker

Level (dB SPL)

Mean Standard

Error

Standard


Error

Standard

Deviation

50 0.43 0.89 1.79 0.70 0.50 1.00

55 0.26 0.39 0.77 0.87 1.14 2.28

60 0.42 0.35 0.70 1.36 0.18 0.36

65 1.09 0.49 0.98 1.30 0.19 0.38

70 3.10 1.32 2.64 1.59 0.29 0.59

75 2.86 0.62 1.24 2.11 0.79 1.59

80 3.43 1.70 3.40 1.15 0.56 1.12

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Comparison of central masking versus monotic masking in non-simultaneous masking conditions

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