This document describes a dissertation that examined the effects of music training and selective attention on working memory during the processing of paired auditory and visual stimuli. A pilot study was conducted to develop music, image, and test materials. The main experiment involved 192 music and non-music majors viewing training videos with music and images under divided, music-focused, or image-focused attention. Participants completed a posttest assessing recall of paired and unpaired stimuli. Results showed music majors outperformed non-music majors under divided and music-focused attention, while non-music majors did better with image-focused attention. Analyses revealed effects of rhythmic complexity, serial position, gender, and individual differences on memory performance.

1. 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
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By
JENNIFER D. JONES
A Dissertation submitted to the
College of Music
in partial fulfillment of the
requirements for the degree of
Doctor of Philosophy
Degree Awarded:
Summer Semester, 2006

2. UMI Number: 3232396
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Copyright 2006 by
Jones, Jennifer D.
All rights reserved.
UMI Microform
3232396
2006
by ProQuest Information and Learning Company. Copyright
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3. The members of the Committee approve the dissertation of Jennifer D. Jones defended on June
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15, 2006.
____________________________________________
Jayne M. Standley
Professor Directing Dissertation
___________________________________________
Jeffrey James
Outside Committee Member
____________________________________________
John M. Geringer
Committee Member
____________________________________________
Clifford K. Madsen
Committee Member
The Office of Graduate Studies has verified and approved the above named committee members.

4. 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, PREVIEW
“Yes, you can” every time I claimed I couldn’t, and “Yes, you will” when
I claimed I wouldn’t. Better than better! iii

5. TABLE OF CONTENTS
List of Tables vii
List of Figures viii
Abstract ix
1. INTRODUCTION 1
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2. REVIEW OF LITERATURE 5
Theoretical Framework 5
Attention Research 8
Measuring Attention and Attention as a Central Resource 8
Endogenous and Exogenous Attention 11
Attention Research with Infants and Children 12
Attention, Intelligence, and Development 14
Selective Attention Research 16
Auditory and Visual Stimuli 17
Commonalities and Synergy 17
Localization and Cueing Differences with Cross-modal Stimuli 19
Visual Attention During Auditory Distraction – Irrelevant Sound 20
iv
Paradigm
Auditory and Visual Dominance Theories 23
Dichotic Listening Paradigm 25
Dual Audio Tasks – Pitch and Duration Judgments (non-dichotic) 29
Music and Memory 30
Memory and Songs – The Influence of Auditory Structure on Serial 30
Verbal Recall
Theories of Music Processing and Memory 34
Melody Recognition 35
Developmental and Training Differences 35
Pitch, Rhythm, Contour, and Timbre Discrimination 36
Searching for Melodic Targets 39
Attention During Multi-Voice Music 40
Error Detection and Expectancy as Evidence of Focus of Attention 42
during Multi-voice music
Gestalt in Music – Extracting Parts from Wholes 46
Attention to Music – Focused and Therapeutic Listening 47
Bimodal Experiences with Music – Complimentary and Non-complimentary 50
Audio-Visual
Encoding and Decoding Music Through Visual, Auditory and Tactile Senses 52

6. Music Training and Memory Research 54
Gender Differences in Music and Memory Research 58
The Present Study 61
3. METHOD 63
Pilot Study Materials 63
Music (Auditory Stimuli) 63
Images (Visual Stimuli) 68
Video Development 70
Posttest Construction 70
Procedure for Pilot Study 72
Results of Pilot Study 73
Changes to Music Stimuli for Main Experiment 80
Changes to Test Construction for Main Experiment 81
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Main Experiment 83
Participants 83
Design 86
Procedures 88
4. RESULTS 92
Familiarity – Ratings and Total Correct Scores 92
Perception of Attention Allocation 94
Analyses of Modality of Error Scores 95
Analysis of Question Type under Music Conditions 97
Memory Strategies 100
Analyses for Memory Decay 103
Analyses for Serial Position Effects 104
Analyses of Posttest Questions 107
5. DISCUSSION 109
Summary of Results 109
Music Training Effects 109
Recognition Versus Rejection of Stimuli in Working Memory 111
The Role of Strategy 112
Rhythm, Attention, and Information Processing 113
Contour- Similar or Dissimilar to Target Melody 114
Serial Position Effects – Expectancy Theory 115
Attention States 116
Implications for Music Education and Music Therapy 118
v

7. Appendix A: Main Experiment – Composition of Audio Distractors for The Bailiff’s 120
BIOGRAPHICAL SKETCH 241
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Daughter and Pomp and Circumstance
Appendix B: Informed Consent Form and Approval Letter from 127
Human Subjects Committee
Appendix C: Pilot Study – Pre-Experiment Questionnaire 130
Appendix D: Main Experiment – Posttest Form for Pomp and Circumstance 132
Appendix E: Main Experiment – Posttest Form for The Bailiff’s Daughter 135
Appendix F: Pilot Study – Post-Experiment Questionnaire 138
Appendix G: Pilot Study – Instructions Script 140
Appendix H: Pilot Study – Practice Test Form 143
Appendix I: Main Experiment – Pre-Experiment Questionnaire 145
Appendix J: Main Experiment – Practice Test Form 147
Appendix K: Main Experiment – Post-Experiment Questionnaire 149
Appendix L: Audio Instructions Accompanying Introductory and Instruction 152
Slides in Experiment Videos
Appendix M: Introductory, Instruction, and Practice Test Slides 155
Appendix N: Main Experiment – The Bailiff’s Daughter Posttest 159
Appendix O: Main Experiment – Pomp and Circumstance Posttest 163
Appendix P: The Bailiff’s Daughter Video 167
Appendix Q: Pomp and Circumstance Video 169
Appendix R: Raw Data Spreadsheets 171
REFERENCES 226

8. 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 94
17. Bailiff’s Daughter Distractor Music Items Failing Criterion 108
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and 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 106
Music Measures
16. Pomp and Circumstance Frequency Distribution of Total Correct Responses for 107
Music Measures

9. 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 69
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white screen)
11. Hail to the Chief order of images (green on white screen) for training stimulus, 70
practice test 2
12. The Farmer’s Boy order of images (red on white screen) for training stimulus, 70
practice 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

10. 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.
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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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11. 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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12. 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.
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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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13. 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
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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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14. 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.
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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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15. 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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16. CHAPTER 2
REVIEW OF LITERATURE
Theoretical Framework
Researchers have long investigated how humans remember (James, 1902). Numerous
forms of memory 1993), autobiographical more generally recognized existence and functions has undergone and the late 1950s to “relatively undifferentiated acoustically based, PREVIEW
have been differentiated, including implicit and explicit memory (Schacter,
memory, episodic, and semantic memory (Nelson, 1993) among the
long-term and short-term memory divisions. Few theorists debate the
of a long-term memory component, though short-term memory theory
continues to undergo revision. Alterations in short-term memory theory from
the early 1970s included a shift from the dominant view of memory as a
unitary system” (Baddeley, 1976, p. 187) to one of distinct stores for
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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17. 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.
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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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18. 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.
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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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19. 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.
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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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20. 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.
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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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21. 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).
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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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22. 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).
PREVIEW
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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23. 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.
PREVIEW
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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24. (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)
PREVIEW
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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