THE FLORIDA STATE UNIVERSITY

COLLEGE OF MUSIC

THE EFFECTS OF MUSIC TRAINING AND SELECTIVE ATTENTION ON WORKING

MEMORY DURING BIMODAL PROCESSING OF AUDITORY AND VISUAL STIMULI

By

JENNIFER D. JONES

A Dissertation submitted to theCollege of Music

in partial fulfillment of therequirements for the degree of

Doctor of Philosophy

Degree Awarded:Summer Semester, 2006

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UMI Number: 3232396

32323962006

Copyright 2006 byJones, Jennifer D.

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The members of the Committee approve the dissertation of Jennifer D. Jones defended on June

15, 2006.

____________________________________________

Jayne M. StandleyProfessor Directing Dissertation

___________________________________________

Jeffrey JamesOutside Committee Member

____________________________________________

John M. GeringerCommittee Member

____________________________________________

Clifford K. MadsenCommittee Member

The Office of Graduate Studies has verified and approved the above named committee members.

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ACKNOWLEDGEMENT

I wish to thank Dr. Jayne Standley for always having answers to my questions and for

supporting my research interests. To Dr. Cliff Madsen, I wish to say thank you for ‘getting me.’

It was an honor to teach with you. To Dr. Geringer, you challenged me to think harder than I

even thought was possible! Thanks for the stats-induced headaches.

I wish to thank my parents for the roots and wings. Thank you, Mother, for always

having time to listen to me. Thank you, Daddy, for determination and great math genes. There is

no way to adequately thank my husband, Jon Jones. You have had many roles – data-miner,

editor-in-chief, financier, chef, computer technician, cat-feeder, and many more. Mostly, I thank

you for always saying, “Yes, you can” every time I claimed I couldn’t, and “Yes, you will” when

I claimed I wouldn’t. Better than better!

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TABLE OF CONTENTS

List of Tables vii

List of Figures viii

Abstract ix

1. INTRODUCTION 1

2. REVIEW OF LITERATURE 5

Theoretical Framework 5Attention Research 8

Measuring Attention and Attention as a Central Resource 8Endogenous and Exogenous Attention 11Attention Research with Infants and Children 12Attention, Intelligence, and Development 14Selective Attention Research 16

Auditory and Visual Stimuli 17Commonalities and Synergy 17Localization and Cueing Differences with Cross-modal Stimuli 19Visual Attention During Auditory Distraction – Irrelevant Sound 20

ParadigmAuditory and Visual Dominance Theories 23

Dichotic Listening Paradigm 25Dual Audio Tasks – Pitch and Duration Judgments (non-dichotic) 29

Music and Memory 30Memory and Songs – The Influence of Auditory Structure on Serial 30

Verbal RecallTheories of Music Processing and Memory 34

Melody Recognition 35Developmental and Training Differences 35Pitch, Rhythm, Contour, and Timbre Discrimination 36Searching for Melodic Targets 39Attention During Multi-Voice Music 40Error Detection and Expectancy as Evidence of Focus of Attention 42

during Multi-voice musicGestalt in Music – Extracting Parts from Wholes 46

Attention to Music – Focused and Therapeutic Listening 47Bimodal Experiences with Music – Complimentary and Non-complimentary 50

Audio-VisualEncoding and Decoding Music Through Visual, Auditory and Tactile Senses 52

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Music Training and Memory Research 54Gender Differences in Music and Memory Research 58The Present Study 61

3. METHOD 63

Pilot Study Materials 63Music (Auditory Stimuli) 63Images (Visual Stimuli) 68Video Development 70Posttest Construction 70Procedure for Pilot Study 72Results of Pilot Study 73Changes to Music Stimuli for Main Experiment 80Changes to Test Construction for Main Experiment 81

Main Experiment 83Participants 83Design 86Procedures 88

4. RESULTS 92

Familiarity – Ratings and Total Correct Scores 92Perception of Attention Allocation 94Analyses of Modality of Error Scores 95Analysis of Question Type under Music Conditions 97Memory Strategies 100Analyses for Memory Decay 103Analyses for Serial Position Effects 104Analyses of Posttest Questions 107

5. DISCUSSION 109

Summary of Results 109Music Training Effects 109Recognition Versus Rejection of Stimuli in Working Memory 111The Role of Strategy 112Rhythm, Attention, and Information Processing 113Contour- Similar or Dissimilar to Target Melody 114Serial Position Effects – Expectancy Theory 115Attention States 116Implications for Music Education and Music Therapy 118

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Appendix A: Main Experiment – Composition of Audio Distractors for The Bailiff’s 120Daughter and Pomp and Circumstance

Appendix B: Informed Consent Form and Approval Letter from 127Human Subjects Committee

Appendix C: Pilot Study – Pre-Experiment Questionnaire 130Appendix D: Main Experiment – Posttest Form for Pomp and Circumstance 132Appendix E: Main Experiment – Posttest Form for The Bailiff’s Daughter 135Appendix F: Pilot Study – Post-Experiment Questionnaire 138Appendix G: Pilot Study – Instructions Script 140Appendix H: Pilot Study – Practice Test Form 143Appendix I: Main Experiment – Pre-Experiment Questionnaire 145Appendix J: Main Experiment – Practice Test Form 147Appendix K: Main Experiment – Post-Experiment Questionnaire 149Appendix L: Audio Instructions Accompanying Introductory and Instruction 152

Slides in Experiment VideosAppendix M: Introductory, Instruction, and Practice Test Slides 155Appendix N: Main Experiment – The Bailiff’s Daughter Posttest 159Appendix O: Main Experiment – Pomp and Circumstance Posttest 163Appendix P: The Bailiff’s Daughter Video 167Appendix Q: Pomp and Circumstance Video 169Appendix R: Raw Data Spreadsheets 171

REFERENCES 226

BIOGRAPHICAL SKETCH 241

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LIST OF TABLES

1. Musicianship as Defined by a Sample of Reviewed Literature 59

2. Descriptive Statistics on Pilot Data Group by Music Type 76

3. Question Analysis for The Bailiff’s Daughter – Pilot Study 77

4. Question Analysis for Pomp and Circumstance – Pilot Study 78

5. Academic Majors of the Participants 85

6. Mean Estimated Hours of Music Heard and Performed By Participants Groups 86

7. Study Design – Participant Distribution by Gender, Major, and Instruction Type 87

8. Perception of Attention Allocation to Music and Pictures for Familiar 94and Unfamiliar Music

9. Mean Correct for Each Question Type for The Bailiff’s Daughter 97

10. Mean Correct for Each Question Type for Pomp and Circumstance 99

11. Frequency Distribution of Strategies Used by Participants 101

12. Mean Total Score for Familiar and Unfamiliar Music By Strategy Type 102

13. Frequency Distribution of Strategies by Instruction Type for Music Conditions 103

14. Frequency Distribution of Total Correct Responses for Pictures by Serial Position 105

15. The Bailiff’s Daughter Frequency Distribution of Total Correct Responses for 106Music Measures

16. Pomp and Circumstance Frequency Distribution of Total Correct Responses for 107Music Measures

17. Bailiff’s Daughter Distractor Music Items Failing Criterion 108

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LIST OF FIGURES

1. Pomp and Circumstance – original 64

2. Pomp and Circumstance – pilot study version 65

3. The Bailiff’s Daughter – original 65

4. The Bailiff’s Daughter – pilot study version 66

5. Hail to the Chief – original notation 67

6. Hail to the Chief – pilot study version 67

7. The Farmer’s Boy – original key and notation 67

8. The Farmer’s Boy – pilot study version 68

9. The Bailiff’s Daughter order of visual training stimuli (black images on white screen) 69

10. Pomp and Circumstance order of visual training stimuli (blue images on 69white screen)

11. Hail to the Chief order of images (green on white screen) for training stimulus, 70practice test 2

12. The Farmer’s Boy order of images (red on white screen) for training stimulus, 70practice test 1

13. Pomp and Circumstance – main experiment 81

14. The Bailiff’s Daughter – main experiment 81

15. Experimental laboratory set-up 89

16.Familiarity ratings by major interaction 92

17. Total correct scores – interaction between major and instruction 93

18. Picture errors – major by instruction interaction 96

19. Music errors – major by instruction interaction 96

20. The Bailiff’s Daughter – question type by gender interaction 98

21. Pomp and Circumstance – question type by gender interaction 99

22. Pomp and Circumstance – question type by major interaction 100

23. Pomp and Circumstance – test half by order interaction 104

24. Question #22 distractor music 107

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ABSTRACT

Researchers have investigated participants’ abilities to recall various auditory and visual

stimuli presented simultaneously during conditions of divided and selective attention. These

investigations have rarely used actual music as the auditory stimuli. Music researchers have

thoroughly investigated melodic recognition, but non-complimentary visual stimuli and attention

conditions have rarely been applied during such studies. The purpose of this study was to

examine the effects of music training and selective attention on recall of paired melodic and

pictorial stimuli in a recognition memory paradigm.

A total of 192 music and non-music majors viewed one of six researcher-prepared

training videotapes containing eight images sequenced with a highly familiar music selection and

an unfamiliar music selection under one of three attention conditions: divided attention, selective

attention to music, and selective attention to pictures. A 24-question posttest presented bimodal

test items that were paired during the training, paired distractors, a music trainer with a picture

distractor, or a picture trainer with a music distractor. Total correct scores, error scores by

modality, and scores by question type were obtained and analyzed.

Results indicated that there were significant differences between music and non-music

majors’ recall of the bimodal stimuli under selective attention conditions. Music majors

consistently outperformed non-music majors in divided attention and selective attention to music

conditions, while non-music majors outperformed music majors during selective attention to

pictures. Music majors were better able to reject distractor music than were non-music majors.

Music majors made fewer music errors than non-music majors. However, an unanticipated effect

of gender was found. Females were better at recognizing paired trainers and males were better at

rejecting distractors for both music conditions. Individually selected memory strategies did not

significantly impact total scores.

Analyses of sample error rates to individual questions revealed memory effects for music

due to serial position and rhythmic complexity of stimuli. Participants poorly recalled the final

measure of both music conditions. This finding was unusual since this position is generally

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memorable in serial recall tasks. Simple rhythmic contexts were not remembered as well as more

complex ones. The measures containing four quarter notes were not well recalled, even when

tested two times.

This study confirmed that selective attention protocols could be successfully applied to a

melodic recognition paradigm with participants possessing various levels of music training. The

effect of rhythmic complexity on memory requires further investigation, as does the effect of

gender on recognition of melody. A better understanding of what makes a melody memorable

would allow music educators and music therapists the opportunity to devise and teach effective

strategies.

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CHAPTER 1

INTRODUCTION

Can people do two things at once? When asked, most individuals readily answer “yes” or

“no” to this question. Each seems to understand his/her own capacity and preference for

‘multitasking.’ Those who answer “yes” perceive that their performance is not compromised and

may be enhanced in highly stimulating environments. Those who answer “no” perceive that they

perform best when completing a single task a time. Is either of these groups correct? Researchers

have investigated many aspects of this conundrum – are humans single, double, or multi channel

thinkers? What conditions influence performance accuracy? What stimulus properties influence

the outcome of dual task events? What roles do attention, memory, and experience/training play?

Researchers have discovered partial answers to many of these questions, but as questions are

answered, technology advances and are faced with new sensory environments that pose new

challenges for research.

Modern environments are saturated with stimuli; one prevalent environmental stimulus is

music, made more readily available to listeners than at any other time in history by the iPod and

other portable devices. Researchers have confirmed that music is ever-present in today’s society;

we are influenced by music everywhere from work (Lesiuk, 2005) to restaurants (Caldwell &

Hibbert, 2002). Many times the hearer chooses the music, other times; listeners have little

control over sound environments (North, Hargreaves, & Hargreaves, 2004). Teens and young

adults have reported listening to music from 2.5 or 3 hours per day to as much as 40 hours per

week (Gardstrom, 1999; North, Hargreaves, & O’Neill, 2000; Radvansky, Fleming, & Simmons,

1995; Schwartz & Fouts, 2003; Tarrant, North, & Hargreaves, 2000). While listening to music is

a highly valued leisure activity, it is frequently secondary to another media event, such as

watching television and reading (Kubey & Larson, 1990). Therefore, listening to music can be

researched in the context of dual task experiments.

In fact, many aspects of music listening constitute a dual task, even when listening to the

music is the primary objective. Most music contains both pitch and rhythm information.

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Researchers have investigated the degree to which listeners can attend separately to each of these

components (Byo, 1997; Demorest & Serlin, 1997; Sink, 1983). Additionally, music can present

different timbres and degrees of intensity for listeners’ attentional foci (Madsen & Geringer,

1990; Radvansky et al., 1995; Wolpert, 1990). Songs introduce yet another stimulus by the

presence of text (Bonnel, Faita, Peretz, & Besson, 2001). Performing music also provides a

number of dual task opportunities, including the dual auditory tasks of listening to one’s own

performance while being aware of the performance of others and the inclusion of visual tasks

when performing from notation.

Investigations of bimodal audio-visual processing have included musical and non-

musical stimuli. Research on the effects of soundtracks to movies provides clarity on music’s

influence upon mood (Boltz, 2001) in addition to its impact upon memory for mood-related

aspects of films (Marshall & Cohen, 1988). Other research involving short tone sequences and

common sounds (door bell, duck quack) paired with visual images has revealed developmental

differences in the reliance upon our eyes and ears for information (Napolitano & Sloutsky, 2004;

Robinson & Sloutsky, 2004; Sloutsky & Napolitano, 2003). Sloutsky (2003, 2004) and

colleagues discovered that young children (4-year olds) relied more heavily on auditory

information when encoding bimodal stimuli. This was termed an auditory processing bias.

Additionally, children were not able to shift their attention to visual aspects when instructed or

able to use this information successfully during testing. In contrast, the visually-dominant adults

could shift their attention to auditory inputs successfully.

Baddeley’s (1986) components of working memory, namely the phonological loop,

visuospatial sketchpad, and central executive function, provide a framework for examining recall

for visual and auditory events. According to this proposal, visual and auditory events are

processed in different memory sub-components with central executive function acting like a

coordinator for incoming information. Contemporary information processing theory concurs with

Baddeley’s ideas of separate stores for different incoming stimuli. Information processing

theorists propose that there are filters or buffers that prevent the working memory system from

overloading by prioritizing information into sensory traces, data-driven, and process-driven

concepts (Klahr & MacWhinney, 1998). Information processing theory also categorizes

information as serial, including music, speech, and other events that unfold in time, or parallel,

including many visual stimuli. While speech and music are both examples of serial auditory

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processing, brain studies have discovered that different areas of the brain are used when

processing these events.

Through brain scanning technology, researchers have found that verbal, auditory (Mirz et

al., 1999), and musical stimuli are processed differently. Generally, the left hemisphere is

specialized for speech (Jeffries, Fritz, & Braun, 2003) and words (Samson & Zatorre, 1991)

while the right hemisphere processes melody. Rhythm judgment did not appear to be lateralized

to the left or right hemisphere (Dennis & Hopyan, 2001; Plenger et al., 1996). Curiously, though

some aspects of music are processed in the opposite hemisphere from verbal data, people with

musical training demonstrate superior verbal memory (Ho, Cheung, & Chan, 2003; Kilgour,

Jakobson, & Cuddy, 2000). No such advantage was found for visual memory (Ho et al., 2003).

Seemingly, musicians’ systematic use of their auditory attention and processing yields superior

skills in the general auditory domain. However, few studies have examined how musicians

compare to others when bimodal audio (musical)-visual tasks are presented to them.

Other research has focused on the differences in the male and female brain. The male

brain is characterized as being designed for understanding and building systems (and extracting

rules that govern systems) while the female brain is more socially oriented (Baron-Cohen, 2005).

Likewise, males and females, both infants and adults, responded to music differently, particularly

when under stress (Standley, 1998, 2000), and female infants have more acute hearing (Cassidy

& Ditty, 2001). However, studies examining tonal memory (Norris, 2000), attention responses

(Richard, Normandau, Brun, & Maillet, 2004), and mental capacity (Johnson, Im-Bolter, &

Pascual-Leone, 2003) found no differences between the sexes. Often researchers assign equal

numbers of each sex in participant groups without reporting differences. It is not conclusive if

differences in audio-visual memory between men and women exist at this point.

The present study was designed to investigate how musicians versus nonmusicians and

males versus females remember paired musical (auditory) and visual components following

bimodal encoding examined in a recognition memory paradigm. The effects of attention on the

recall of bimodal stimuli among the groups were tested through selective attention instructions.

Additionally, this study sought to determine the differences between dual encoding unfamiliar

music with unfamiliar images in comparison to retrieval of familiar music and encoding of

unfamiliar images. It was expected that differences in the recall of musical events between

musicians and nonmusicians would emerge, though a difference between males and females was

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not projected. The natural patterns of attention to visual and audio/musical events were examined

in the group receiving no selective attention instructions. The degrees to which participants could

manipulate their attention patterns to musical and visual stimuli were also tested. Encoding and

memory strategies of the groups were categorized.

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CHAPTER 2

REVIEW OF LITERATURE

Theoretical Framework

Researchers have long investigated how humans remember (James, 1902). Numerous

forms of memory have been differentiated, including implicit and explicit memory (Schacter,

1993), autobiographical memory, episodic, and semantic memory (Nelson, 1993) among the

more generally recognized long-term and short-term memory divisions. Few theorists debate the

existence and functions of a long-term memory component, though short-term memory theory

has undergone and continues to undergo revision. Alterations in short-term memory theory from

the late 1950s to the early 1970s included a shift from the dominant view of memory as a

“relatively undifferentiated unitary system” (Baddeley, 1976, p. 187) to one of distinct stores for

acoustically based, limited-capacity, short-term storage and a more durable long-term store of

considerable capacity. Even in the mid 1970s growing evidence that sensory systems (visual,

auditory, and kinesthetic) may have a unique memory store compelled further differentiation of

short-term memory theory. Baddeley’s (1986) conceptualization of working memory in three

major divisions has proven hearty enough to withstand rigorous research and has spawned years

of debate. This concept of the central executive with its slave components, the phonological loop

and visuospatial sketchpad, provided a framework for not only researching visual and auditory

information processing, but how information is selected, organized, coordinated, stored, and

ultimately remembered (Baddeley & Hitch, 1974).

Broadbent (Broadbent, 1971) contributed the concept of information selection. In the

initial proposal in 1958, there was a single channel with a limited capacity through which all

information funneled. The capacity limit of the single channel was a function of the rate of

information flow, meaning that the organism needed time to process the stream of incoming

information. In order to accommodate this limit, selective perceptual processing utilized a buffer

store and a filtering system (Broadbent, 1971). Information could be held in the store and

selected information filtered out for immediate processing. Broadbent also contributed the

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concepts of vigilance and expectancy to early work in early information processing. Today,

vigilance and expectancy are probably best conceived as functions of attention, including

selective attention, sustained attention, and inhibiting or ignoring distracting stimuli. Jones

(1999) credited Broadbent with the concept of selective attention, particularly for auditory

events, that has been exhaustively researched through the dichotic listening paradigm.

The role of attention during information processing has continued to be important to

working memory theory development. Treisman and Davies (1973) proposed the concept of

parallel attention and processing, thereby expanding the single channel theory. In parallel

processing, incoming stimuli of different modalities or different properties of the same stimuli

can be analyzed at the same time because they do not use the same resources. Two studies

conducted by Allport, Antonis, and Reynolds (1972) supported the hypothesis. Allport et al.

(1972) proposed a multi-channel hypothesis after research showing participants displayed

abilities to accurately recall photography presented while they were engaged in speech

shadowing. A second study involved music majors who were able to sight-read piano music

while speech shadowing easy and difficult prose passages. There were no significant differences

in the memory posttest for the prose passages under conditions of sight-reading on the piano and

only speech shadowing. Furthermore, the differences in error rates during the piano task were not

significantly different in session 2 under divided or focused attention. This research clarified that

when the simultaneous tasks are different enough, each can be completed successfully. The

allocation of attention to one task, speech shadowing, did not affect visual memory or motor

performance.

Cowan (1995) proposed that attention and memory intersected and conceptualized

working memory in terms of focus of attention. Cowan (1998) devised a definition of working

memory as follows: Working memory is the collection of mental processes that permit

information to be held temporarily in an accessible state, in the service of some mental activity”

(Cowan, 1998, p. 77). He furthered compared his working memory system with Baddeley’s

system (central executive, phonological and visuospatial stores and processors) acknowledging

the differing sensory memories for visual and auditory events. Cowan’s working memory system

is composed of a capacity-limited focus of attention along with temporarily activated information

in permanent memory. According to Cowan, attention to events summons long-term memory

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resources that allow for semantic processing (Cowan, 2005). The use of long-term resources,

such as chunking and schemata, was not a new concept.

Miller (1956) proposed chunking as a means of overcoming capacity limits for short-term

memory. The basic concept of chunking was that like information was perceptually grouped such

that information was encoded in small groups rather than a string. One of the most common

examples of chunking is remembering telephone numbers in groups of three or four. Researchers

have investigated the degree to which stimulus features render the chunks or cogitative processes

of the observer (Crawley, Acker-Mills, Pastore, & Weil, 2002; Green & McKeown, 2001).

Stimulus-driven chunking would provide evidence of a bottom-up or data-driven approach while

scheme-driven chunking would be indicative of a top-down or concept-driven approach, using

information technology language (Klahr & MacWhinney, 1998). Chunking obviously occurs; the

degree to which it is perceptually (automatic) or conceptually (thought) driven is still under

investigation.

Information processing theory has developed alongside the understanding and

development of computer programming. Based upon storage units, filters, and schemata

proposed by psychological theorists, programmers have designed computer models that imitate

human information processing. One particular area of interest has been auditory selective

attention, a topic intriguing to cognitive psychologists, neurologists, musicians, and

computational engineers alike (Wrigley & Brown, 2004). Psychologists have developed and

tested theories with behavioral experiments, and computer engineers have integrated information

from electrophysiology and neurology. A model was developed that grouped incoming streams

of intentional information and allowed for ‘leaks’ representative of the processed unintentional

auditory streams. The model represented a culmination of the research on the processing of

attended and unattended auditory events. Psychologists have tested this phenomenon by using

multiple auditory streams or auditory streams in addition to other input and asking participants to

divide attention across streams or select a single stream. Myriad researchers have developed the

selective attention paradigm in both auditory and bimodal (often auditory and visual) paradigms.

The attention research for bimodal audio-visual and dual/multiple audio events has been

framed by Baddeley’s three components of working memory (Baddeley, 1976, 1986; Baddeley

and Hitch, 1974) and contemporary theories of information processing with an elaborate system

of sensory-specific filters and stores. Investigations have been designed to better understand the

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capacity limits for unimodal information and bimodal information, particularly the unique

differences between auditory and visual events. Investigations on the recall of serial and

nonserial information as well as paired or associated events have provided understanding of the

coordination processes during information processing. Researchers have manipulated encoding

methods, rehearsal times and strategies, and output. Measurement of performance has included

reaction or response times, accuracy rates, including hit and false alarm rates, and a number of

brain scan technologies. Designs have included detection, recognition, and discrimination

protocols, each contributing different and, at times, conflicting outcomes. Participants have been

instructed to attend to stimuli, ignore stimuli, and divide attention across events. Through these

expansive and complex investigations of attention and working memory during dual tasks or

multisensory environments, much has been learned about how humans process and retain

information.

While educators are particularly invested in understanding how learning is differentially

achieved through vision and audition, research on learning through different senses has of

interest to a broad audience. The effects of multisensory input are of special interest to music

therapists and music educators. While the researchers studying attention during dual audio tasks

have systematically manipulated frequency, duration, and intensity in short tone sequences,

fewer researchers have used actual music. Music as a stimulus provides a number of foci for

attention, including rhythm, pitch, melody, and harmony, to name a few. Additionally, cognitive

memory strategies can be examined using music (Madsen & Madsen, 2002). The use of music as

an agent for facilitating the learning of non-musical information has been investigated in addition

to the teaching of music understanding and performance. The effect of music training upon

memory for verbal and nonverbal information has provided a fertile ground for examining the

role of experience in memory and attention.

Attention Research

Measuring Attention and Attention as a Central Resource

Auditory attention has proven to be a difficult construct to measure though James’ (1902)

claimed that we all know what attention is. Two such tests have claimed to measure auditory

selective attention, namely the Goldman-Fristoe-Woodcock Auditory Selective Attention Test and

the Flowers Auditory Test of Selective Attention. Glass, Franks, and Potter (1986) compared

these test to determine if they indeed measured the same construct; the researchers found the

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tests to correlate (r = .44). Though the correlation was positive, the relative weakness of the

relationship indicated that the construct of auditory selective attention was broad. Auditory

selective attention ranges from being aware and localizing of sounds, to perceptual processing of

relevance, as well as ignoring distraction, and maintaining focus of attention over time. Despite

the difficulties presented by empirical measures of attention, a study by Kahneman, Ben-Ishai,

and Lotan (1973) demonstrated the validity of attention as a construct. Based upon a high

number of accidents – a behavior attributed to poor attention - bus drivers were tested for

auditory attention. Kahneman et al. (1973) found moderate, positive correlations between the

number of accidents per year by professional bus drivers in Israel and a test of selective auditory

attention.

Cowan (1995, 2005) has established the importance of attention to working memory;

therefore, measures of working memory may to provide an estimate of one’s attention. One

aspect of attention that has been frequently measured is the ability to resist distraction.

Resistance to auditory distraction, referred to as the irrelevant sound paradigm (Jones, 1999), is a

common technique. Beaman (2004) gave participants the Operations Span Task (OSPAN) for

working memory during conditions of auditory distraction. He later compared the scores for

relationship between the test and behavior. The OSPAN was not predictive of the irrelevant

sound effect on serial or free recall of verbal material (Beaman, 2004). Irrelevant speech sounds

and words affected both high and low scores from the OSPAN. Though the relationship was not

hearty enough to demonstrate a significant relationship, low span individuals were more likely to

experience intrusion from previous list trials than high span individuals. It does appear that these

tests are spotlighting the same concept, though they have demonstrated flaws.

Morey and Cowan (2004, 2005) verified attention to be a central resource in working

memory. In the 2004 study, participants were asked to recite their 7-digit phone number, a

random set of 7 digits, 2 digits, or no digits while examining visual arrays with 4, 6, or 8 colored

squares and subsequently making same-different judgments on the visual arrays. The recitation

of numbers was designed to prevent verbal rehearsal of the positions and colors of squares in the

visual array by directing attention to numerical recitation. There were significant differences in

scores by visual array size and recital condition with no significant interactions between the

variables. Performance was best for the smallest array size. The participants’ scores were poorest

when reciting 7 random digits in comparison to the other three conditions that did not differ

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significantly from one another. The authors concluded that some shared space in working

memory was used for digits and visual information. The 2005 study provided additional support

for the central resource for attention. Morey and Cowan (2005) found that participants were able

to make visual array judgments of same or different equally well under no digit recall conditions

and silent rehearsal of digits conditions, but vocal rehearsal of the digit lists significantly

impacted visual array judgments. The recitation of the to-be-remembered digits, whether before

the first visual array or after, interfered with visual memory. Attention was presumably drawn

away from the visual task during recall of the list, indicative of a central attentional resource

(Morey & Cowan, 2005). The distracting effect of speaking was likely the result of tapping into

resources from the phonological loop, particularly since digits were not disruptive to visual array

judgments when silently rehearsed. The impact of the distracting spoken digits occurred

regardless of the location of the distractor in the sequence (before arrays or during).

Further evidence from both studies that a central attention resource was responsible for

auditory and visual information was the relationship between accuracy in both modalities. Morey

and Cowan (2004) found that visual array comparisons were significantly more accurate when

accompanied by correct digit list recall than when the digit recall was incorrect. The same

relationship existed for correct digit recall as correct lists were accompanied by correct visual

arrays. The co-occurrence of error (and accuracy) confounded the idea of a simple trade-off

between stimulus types under dual-task conditions. The same relationship was found in the 2005

study; when the digits were recalled incorrectly, accuracy on the visual array task was lower than

when digits were correctly recalled. Demonstration of successful attention allocation was

evinced by correct recall of both digits and visual arrays.

Research in the auditory distraction paradigm also supports attention as a major

component of working memory. Berti and Schroger (2003) had listeners identify the duration of

tones, the majority of which were 1000 Hz (90%) and a few of which (10%) were 1050 Hz or

950 Hz, immediately (low-load task) or upon the arrival of the next tone (high-load) task. There

was a significant interaction between response times and load, and main effects for response

times. Under the high-load condition, there was less difference in response times between

standard and deviant tones. Response times were lower for both standard and deviant tones in the

low-load condition, as would be expected. The greater interruption of the irrelevant pitch change

in the low-load condition appeared to be triggered by the preattentive detection system, however,

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the task requiring greater attention reduced the sensitivity of the preattentive system. Attention

mediated response times until the task load was too large. An automatic response (faster reaction

time) indicated a greater ability to ignore the irrelevant dimension of pitch during duration

judgments. Additionally, this research provides evidence that the salience of stimulus features

can be dependent upon task load.

Endogenous and Exogenous Attention

While attention can be directed toward certain stimuli or specific stimulus attributes,

attention can be ‘captured’ by salient aspects of events without intentional attention shifts. Green

and McKeown (2001) discussed the differentiation between endogenous attention, the top-down,

voluntarily controlled attention, and exogenous attention, the attention that is largely automatic.

Their research results provided evidence for stimulus-driven control of frequency selection

during informative and uninformative cue trials despite the participants’ intention to ignore

frequency. This processing of unintentional auditory features, or in other cases auditory streams,

was precisely what challenged the computer engineers’ computational model of auditory

selective attention (Wrigley & Brown, 2004).

Another study in auditory perception confirmed the role of stimulus-driven attention.

Crawley et al. (2002) conducted research designed to determine differences between musicians’

and nonmusicians’ ability to use primitive (stimulus-driven, bottom-up) and scheme-driven

grouping to detect single errors in 3-voice music with homophonic or polyphonic textures. The

authors proposed that musicians would demonstrate better flexibility in selecting schemes due to

experience, particularly the ability to attend to single lines in homophonic music despite the

likely perceptual grouping of chords. However, the data refuted this hypothesis. Both musicians

and nonmusicians were better at identifying subtle melodic changes in a homophonic texture,

particularly when the change was chord-unrelated. The performance of both groups suffered

when directed to search for melodic changes in a specific voice instead of any change in the

overall texture. While musicians were significantly better at the error detection task overall than

nonmusicians, Crawley et al. (2002) concluded that music training did not appear to provide

musicians with the ability to override perceptual grouping tendencies but did give them better

ability to use the information in error detection. While control of attention was the intention,

stimulus properties evoked automatic perceptual strategies despite intention to select a specific

cognitive strategy.

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Attention Research with Infants and Young Children

Sustained attention to a stimulus and distraction by other stimuli can be investigated in

very young participants. Richard et al. (2004) investigated attention getting (localization) and

attention holding (habituation) patterns of infants (5 months old) exposed to simple and complex

auditory stimuli (repeating scale pattern) using a looking paradigm. The data on localization and

habituation differentiated the two attention processes in response to these auditory stimuli; a

progressive decrease in attention-holding but not attention-getting was observed across trials. By

simply turning their heads, the infants indicated awareness of the location of presented stimuli

and made preference decisions by the length of time the infant focused on a location. Infants

preferred complex tones as indicated by longer looking times. These differences were significant.

Distinct acoustic properties influenced the sustained attention of the infants.

Infants attend to verbal and musical sounds differently. Kinney and Kagan (1976) tested

the orienting responses of 7-month-old boys and girls for auditory stimuli, specifically short

verbal (nonsense syllables) and musical phrases (varying in rhythm and timbre) that were

presented along a continuum of variability from none to extreme. Using heard turns and heart

rate deceleration as indicators of an orienting response and captured attention, the hypothesis that

the response would be curvilinear with moderate stimulus changes being more alerting than no

change or extreme change was supported for both types of stimuli. However, some distinct

response differences were noted. More infants vocalized during musical stimulus presentations

with great variability among the boys in the sample. Girls’ fixation responses on variable stimuli

were closer to the predicted quadratic trend while boys’ responses fell into an inverted U-shape.

Clearly infants’ responses were discriminate among the variable verbal and musical stimuli with

differences between the sexes emerging.

Infant attention to bimodal stimuli can also be tested. Ruff and Capozzoli (2003)

investigated the attention getting properties of audio and visual distractors in children engaged in

play with toys. They compared casual, settled, and focused attention disruption by audio only,

visual only, or audio-visual distractors on children 10 months, 26 months, and 42 months old.

Based upon the number of head turns as an indicator of the attention-getting properties of the

distractor, there were significant differences among the age groups by modality of distractor.

While the three age groups did not differ in responses to visual only distractors, 10 month old

infants had more head turns in response to audio only (2 or 3 tone sequences) and audio-visual

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(tone sequences plus pictures on screen). The differences in complexity of the auditory

distractor, 2 tones versus 3 tones, were evident in the 42-month-old group only. In the audio only

condition, children looked longer at the monitor after simple (2-tones) tunes, but longer looking

times were documented under audio-visual conditions following complex (3 tone) tunes. These

findings seem to indicate that sustained attention by resisting distraction has a developmental

sequence that is different based upon the modality of the distractor. The meaningfulness of the

distractor, the actual tunes versus two tones, was a more salient distractor for the 42-month-old

group. Perhaps the longer looking times were a reflection of conceptual processing.

Bahrick and Lickliter (2000) provided convincing evidence that infants’ (5 months old)

attention adhered to the intersensory redundancy hypothesis. The hypothesis proposed that

information presented synchronously across two sense modalities was processed thoroughly as a

result of focused attention to the event versus lesser attention for unimodal presentation. Infants

were presented with a bimodal training stimulus where a red hammer pounded out distinct,

synchronized auditory rhythms. When presented with a novel rhythm pattern during the test

phase, significantly longer looking times were noted in comparison to repetition of the training

rhythm. (Infants look longer at novel presentations.) However, when training was either visual or

auditory alone, there were no significant differences in looking times during unimodal test

phases. Not only were the infants stimulated by bimodal stimuli, the encoding of such events

appeared to be more thorough and provided a basis for future decision making in comparison to

singular inputs. These data provide further evidence of dual processing capabilities when the

encoded stimuli recruit different sensory functions.

Using a protocol similar to Bahrick and Lickliter (2000), Lewkowicz (2003) documented

that infants as young as 4 months old detected changes in rhythm following audiovisual encoding

of both syllables and sounds (toy hammer taps). However, only 10-month-old infants looked

longer at a desynchronized audiovisual rhythm. The author concluded that these older infants

were able to process the audiovisual events as a single perceptual stream rather than two separate

streams. This developmental milestone would reduce the load and allow for the attention to

desynchronized rhythm as a novel, meaningful stimulus. Infants from 4 to 10 months increased

looking times to desynchronized, arrhythmic nonsense speech. The abilities of infants to process

synchronized audiovisual events is particularly important to the development of language and

speech.

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