Singing in Tune: Insights from Music Educators and Psychological Researchers, by Ana Luisa Santo, York University

SINGING IN TUNE: INSIGHTS FROM MUSIC EDUCATORS AND PSYCHOLOGICAL RESEARCHERS

ANA LUISA LOURO SANTO

A THESIS SUBMITTED TO THE FACULTY OF GRADUATE STUDIES IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF ARTS

GRADUATE PROGRAM IN MUSIC YORK UNIVERSITY, TORONTO, ONTARIO APRIL 2012

©Ana Luisa Louro Santo

SINGING IN TUNE: INSIGHTS FROM MUSIC EDUCATORS AND PSYCHOLOGICAL RESEARCHERS

by Ana Luisa Louro Santo

a thesis submitted to the Faculty of Graduate Studies of York University in partial fulfillment of the requirements for the degree of MASTER OF ARTS © Permission has been granted to: a) YORK UNIVERSITY LIBRARIES to lend or sell copies of this thesis in paper, microform or electronic formats, and b) LIBRARY AND ARCHIVES CANADA to reproduce, lend, distribute, or sell copies of this thesis anywhere in the world in microform, paper or electronic formats and to authorize or procure the reproduction, loan, distribution or sale of copies of this dissertation anywhere in the world in microform, paper or electronic formats. The author reserves other publication rights, and neither the thesis nor extensive extracts from it may be printed or otherwise reproduced without the author’s written permission.

ABSTRACT This thesis is an interdisciplinary examination of the reasons people may sing out of tune. The first chapter is an analysis of interviews with four singing teachers. Common themes include a strong focus on discovering ways to remedy the problem and a belief that everyone can be taught to sing in tune with enough effort and the right methods. The second chapter makes a case for visuospatial deficits as one possible cause of out-of-tune singing, and describes the results of a research experiment that examines this hypothesis. Results show that those with amusia appear to have a deficit in visuospatial working memory, and that out-of-tune singers who lack the pitch-perception deficit present in amusia do not have this deficit, highlighting the separability of the two conditions. The third chapter explores the differences between qualitative and quantitative research and makes suggestions for bridging the gap between music researchers and music educators.

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To Alexandra and Maya

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ACKNOWLEDGEMENTS First and foremost, I would like to express my thanks to my supervisor Rob van der Bliek. Your guidance along the entire process was invaluable, especially in the early stages of organizing and planning. Also, I gratefully acknowledge your decision to supervise such a multi-faceted and interdisciplinary work in the first place, especially when no one else would come near it! Similarly, I would also like to thank the other member of my committee, Mary Desrocher. Your kind suggestions and advice on the psychology-related aspects of this thesis were vital in helping me explore exactly what I wanted to without having to compromise. I would also like to thank Nicholas Cepeda and James Bebko for their consultation during the early stages of this work. Your comments and suggestions played an important role in helping me get started. To Reid Olsen, Brian Piper, and Shane Mueller—thank you for your extraordinary patience and numerous back-and-forth e-mails in helping me figure out how to use the PEBL software. I am very grateful! To Hugh McCague at the Institute for Social Research— thank you for your calm, patient, and detailed help with the statistical analyses. Your contributions are greatly appreciated. To Jennifer Andricola, Robert Abbott, and especially Alycia Panagopoulos— thank you for your meticulous help in preparing the manuscript, for being my hands, and for never balking at yet another scribbled page in urgent need of transcription. I could not do what I do without you behind the scenes. To Barbara Muskat—thank you for your unquestioning faith in me, for cheering me on, and for supporting me through the more difficult times. It means so much to me. I would also like to express my appreciation and thanks to the interviewed teachers who shared their thoughts and experiences. Your comments are an invaluable part of this work, and I am very grateful for the time you took out of your busy schedules to sit and speak with me. Also, my thanks to all the participants in the experiment—research like this is only possible with people like you!

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To Catherine Day, Renata Todros, Karen Rymal, Catherine Robbin, Norma Burrowes, and Lisette Canton—each of you has nurtured and trained my voice in your own way. You have all inspired me, given me confidence, and taught me to never be content with mediocrity. I thank all of you from the bottom of my heart, because each of you has uncovered an aspect of my voice I never knew was there. To Laura, Matthew, Alycia, Laurie, Elvira, and Cathy—thank you for all your support during this process and for being there when I needed you. Your friendship and understanding of me means more to me than I could ever put into words. And finally, to Matthew Keitz—my outlier. Without you, I never would have even thought to try. Thank you for believing in me.

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TABLE OF CONTENTS ABSTRACT................................................................................................................... II ACKNOWLEDGEMENTS .......................................................................................... IV TABLE OF CONTENTS .............................................................................................. VI LIST OF FIGURES ................................................................................................... VIII LIST OF TABLES ........................................................................................................ IX INTRODUCTION .......................................................................................................... 1 Experience of music educators .................................................................................... 2 Amusia ......................................................................................................................... 3 Disconnect between music researchers and educators................................................. 4 The current project ....................................................................................................... 6 CHAPTER 1: SINGING AS A PEDAGOGICAL CONCERN ..................................... 8 Interviewing teachers ................................................................................................... 8 Results.......................................................................................................................... 9 CHAPTER 2: A CLINICAL LOOK AT OUT-OF-TUNE SINGING ......................... 29 Normal development of musical ability ..................................................................... 29 Amusia: A deficit in pitch perception ........................................................................ 32 Etiology of amusia ..................................................................................................... 34 Amusia and the brain ................................................................................................. 34 vi

Speculation about amusia subtypes ........................................................................... 35 Is amusia music-specific? .......................................................................................... 38 Rationale for the current study................................................................................... 47 Hypothesis ................................................................................................................. 49 Methods ..................................................................................................................... 49 Results and Discussion .............................................................................................. 60 CHAPTER 3: BRIDGING THE GAP .......................................................................... 71 Limits of a traditional experiment.............................................................................. 71 Bridging the gap between music researchers and music educators ........................... 73 Usefulness of experiments ......................................................................................... 75 Usefulness of interviews/case studies ........................................................................ 77 Helping those with musical learning disabilities ....................................................... 78 CONCLUSION ............................................................................................................. 80 REFERENCES ............................................................................................................. 85 APPENDIX A: EDUCATORS ..................................................................................... 95 APPENDIX B: MBEA DISTRIBUTIONS ................................................................ 136 APPENDIX C: PARTICIPANT DETAILS ............................................................... 137 APPENDIX D: EXPERIMENTAL DATA ................................................................ 144

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LIST OF FIGURES FIGURE 1: CORSI FW/BW START SCREEN ........................................................................ 54 FIGURE 2: CLOCK TEST START SCREEN .......................................................................... 55 FIGURE 3: MENTAL ROTATION TASK SAMPLE .............................................................. 56 FIGURE 4: MATRIX ROTATION—1ST SCREEN AND COMPARISON EXAMPLE .......... 57 FIGURE 5: MATCH TO SAMPLE—1ST PATTERN AND COMPARISON .......................... 58 FIGURE 6: MALE AND FEMALE MEANS ON CORSI BACKWARDS (TOTAL) ............. 63 FIGURE 7: GROUP BOX PLOTS FOR CORSI BACKWARDS (TOTAL CORRECT) ........ 65 FIGURE 8: MBEA M. SUBSCALE CORRELATION WITH CORSI BW (T. CORRECT) ... 69 FIGURE 9: SCORE DISTRIBUTION OF MELODIC (TASK 1) AND RHYTHM (TASK 2) SUBSCALES.................................................................................................................. 136

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LIST OF TABLES TABLE 1: OUT-OF-TUNE AND IN-TUNE RATINGS ........................................................ 141 TABLE 2: CONSOLIDATED PARTICIPANT CHARACTERISTICS ................................. 142 TABLE 3: MEANS AND STANDARD DEVIATIONS FOR EACH GROUP ON ALL TASKS ........................................................................................................................... 144 TABLE 4: ANOVA—DEPENDENT VARIABLE BY GROUPS .......................................... 144 TABLE 5: MULTIPLE COMPARISONS—CORSI FORWARDS (BLOCK SPAN) ............ 145 TABLE 6: MULTIPLE COMPARISONS—CORSI FORWARDS (TOTAL CORRECT) .... 146 TABLE 7: MULTIPLE COMPARISONS—CORSI FORWARDS (MEMORY SPAN) ....... 147 TABLE 8: MULTIPLE COMPARISONS—CORSI FORWARDS (TOTAL) ....................... 148 TABLE 9: MULTIPLE COMPARISONS—CORSI BACKWARDS (BLOCK SPAN)......... 149 TABLE 10: MULTIPLE COMPARISONS—CORSI BACKWARDS (TOTAL CORRECT)150 TABLE 11: MULTIPLE COMPARISONS—CORSI BACKWARDS (MEMORY SPAN) .. 151 TABLE 12: MULTIPLE COMPARISONS—CORSI BACKWARDS (TOTAL) .................. 152 TABLE 13: MULTIPLE COMPARISONS—MATCH TO SAMPLE .................................... 153 TABLE 14: MULTIPLE COMPARISONS—CLOCK TEST ................................................. 154 TABLE 15: MULTIPLE COMPARISONS—MATRIX ROTATION .................................... 155 TABLE 16: MBEA MELODY SUBSCALE SIGNIFICANT CORRELATIONS WITH VISUOSPATIAL TASKS .............................................................................................. 156

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TABLE 17: MBEA RHYTHM SUBSCALE SIGNIFICANT CORRELATIONS WITH VISUOSPATIAL TASKS .............................................................................................. 156 TABLE 18: MEAN SCORES ON ALL TASKS BY GENDER ............................................. 157 TABLE 19: T-TEST FOR EQUALITY OF MEANS BY GENDER ...................................... 157 TABLE 20: RAW PARTICIPANT TASK DATA .................................................................. 158

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INTRODUCTION The musician may sing to you of the rhythm which is in all space, but he cannot give you the ear which arrests the rhythm nor the voice that echoes it. – Kahlil Gibran

We can probably all call to mind a rendition of “Happy Birthday” that made us cringe, when someone was singing quite obviously out of tune and seemed not to care that their pitches did not match the intended notes, or even the pitches of those around them. Typically, we refer to such poor singers as “tone-deaf,” and some of these individuals even proudly declare how “unmusical” they are. Strangely, others seem to be completely unaware that they cannot sing in tune. Out of tune singing is not only a problem during the occasional birthday gathering, however. Elementary school teachers have to deal with this problem on an everyday basis, especially with very young children who are not yet able to consistently sing in tune for a variety of reasons: their parents don’t sing at home, their music exposure is limited, they lack confidence, they associate negative emotions with singing due to being silenced by adults, etc. (Smith 2006, 28). Whether or not an out-of-tune singer is aware of the extent of their 1

deficit, the inability to sing in tune may cause mild embarrassment in some individuals, and significant distress in others. People who sing out of tune are often asked not to sing at all. This is especially distressing to some children, who feel singled out among their peers. Some teachers even go so far as to tell children to just “mouth the words,” rather than try to sing (Smith 2006, 28).

Experience of music educators Music educators and writers on music education have attempted to grapple with this problem by relying on their personal teaching experiences. Many say that singing in tune does not, in fact, come naturally, and that all children need to be taught to sing in tune. One writer reports that in his experience, up to two-thirds of children cannot sing in unison (Lyon 1993, 20). Another writer claims that children and “primitive peoples” tend to “sing the fourth slightly sharp and the seventh slightly flat.” (Russell-Smith 1967, 43). The development of muscular co-ordination is also seen as an important precursor to singing. Often, the problem is seen as one of motivation. A teacher who wrote about her experiences with eighth-grade singers said that students often sing out of tune because they dislike the music and do not make a serious effort, or because they insist on singing a voice part not suited to their voice. She also says that the problem sometimes comes from the parents, who boast about their

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child’s lack of musical ability, instead of responding with concern, as they would for other subjects, and encouraging the child to try harder (or obtain remedial help) (Bradely 1965, 49). Others have suggested methods for tutoring these out-of-tune singers. Some have proposed graduated methods (Bridgehouse 1978, 53), such as eartraining exercises of progressive difficulty (Bradely 1965, 53), but there does not appear to be a standard method for aiding out-of-tune singers, only trial and error adapted to the individual student’s progress. Still others have proposed that “tone-deafness” does not exist (Kazez 1985, 46; Smith 2006, 30), and that almost all children can be taught to sing well with enough persistence, although a small few may have some form of hearing disorder that interferes with their ability to match pitches (Kazez 1985, 47).

Amusia The term “tone-deaf” is used colloquially to describe poor singers. While this term suggests that these individuals have faulty pitch perception, it is typically used to mean that they have faulty pitch production (i.e. they cannot produce the correct notes when they sing) (Pfordresher and Brown 2007, 95). “Congenital amusia,” on the other hand, is a term proposed to refer to a developmental disorder that is characterized primarily by a deficit in pitch

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perception (Foxton et al. 2004). Amusic individuals have difficulty not only singing in tune, but also recognizing familiar tunes. This disorder occurs in the presence of otherwise intact cognitive abilities, and appears to have a genetic origin (Peretz and Hyde 2003, 363). Because amusics have difficulty perceiving differences in pitch smaller than two semitones (Hyde and Peretz 2004, 357; Peretz 2008, 331), they are unable to acquire the tonal structure of the musical culture they were born into. (Even infants as young as six months appear to have acquired sophisticated pitch processing that surpasses an amusic’s ability (Burns 1999, 252).) As a result, music does not “make sense” to amusic individuals, because they perceive it as a series of unrelated tones that their minds are unable to tie together into musical phrases. The Montreal Battery for the Evaluation of Amusia (MBEA) has been developed to detect amusia, and to differentiate amusics from those who merely have singing problems but can otherwise perceive music normally (e.g. Cuddy et al. 2005). For the purpose of this project, the author will be using the terms “tonedeaf” and “amusic” to refer to these two separate conditions; the former refers to deficits solely in pitch production, and the latter to deficits in pitch perception.

Disconnect between music researchers and educators The knowledge of amusia does not seem to have made it into the

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general knowledge of music educators, possibly because the research is still very new. This suggests two underlying problems. The first is that cognitive deficits (such as amusia or other learning disabilities) are not something the average music educator is concerned with when teaching music. Schools and teachers are generally unaware that “musical disabilities” might exist (Peretz and Hyde 2003, 364). The second concern is that although psychological researchers have amassed a considerable amount of information about a disorder that is musically relevant, this information has not made it into the hands of music educators, whom it could certainly help. This problem is highlighted by Hodges, who writes that neuromusical research either appears “in scientific journals in language that is too difficult for non scientists to easily read and understand, or…in the popular press in such a watered-down fashion that actual facts may be distorted or obscured” (2000, 17). His article goes on to discuss a few interesting neuromusical research findings, presenting them to educators in an accessible way. While attempts like Hodges’ are worthwhile, they do not address the larger concerns that have been identified: disabilities that affect music learning do exist, and the research on them is largely inaccessible to some of the people that could benefit most from the information. It seems that musical research in general, even research that is meant to aid the teaching of “regular” students,

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does not have much of an effect on actual teaching practices. For example, Haston reports that although there is an abundance of literature highlighting the benefits of performance skill modeling, teachers only use modeling about 10-25 percent of the time (2007, 26). The problem of bridging the gap between researchers and educators is compounded by the fact that the tasks used in psychological research are seen as divorced from actual music-making, so there may be a mistrust of researchers making conclusions about music, especially if they are not musicians themselves (Phillips 2008, 3). Whatever the reasons for the disconnect between the two disciplines, it seems a worthwhile goal to try and close the divide, so the two may benefit from each other’s knowledge.

The current project The current project is a multidisciplinary attempt to collect different kinds of data on the problem of out-of-tune singing. Chapter 1 will discuss the information collected from interviews with four singing teachers, and analyze common themes among them. It will consider their thoughts alongside what music education researchers have already written about the challenges involved in helping out-of-tune singers. Chapter 2 will be written as a typical psychology research experiment, reviewing the current available literature and then exploring one specific hypothesis regarding a possible reason for out-of-tune singing. This experiment

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and write-up will also serve as a “case study” of research experiments in general. Chapter 3 will present an examination of the findings from both of the above two very different attempts to gather data. Difficulties encountered during the process will be addressed. It will also include a discussion of how music researchers and music educators can better communicate with each other for the purpose of aiding out-of-tune singers.

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CHAPTER 1: SINGING AS A PEDAGOGICAL CONCERN The human voice is remarkable—it enables us to communicate not only with words and language, but also with various non-verbal sounds such as laughter, crying, sighs, and of course music. Music itself seems to be innate (Patel 2008, 386), starting from an infant’s playful cooing to the instinctive “motherese” of new parents, and nature has provided us with a built-in instrument that is capable of expressing an astonishing array of musical sounds and phrases. The art of singing has been studied in a systematic way since as early as the second century AD (Mason and Wigmore 2012). Today’s singing teachers are just as passionate about the subject, and there is no shortage of books, conferences, workshops, journals, organizations, classes, and other methods of sharing and discussing different methods of singing instruction.

Interviewing teachers To find out some of the current thoughts of those who teach singing today, interviews were conducted with four individuals who teach singing in some capacity: an elementary school teacher, two high school teachers, and a

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private voice teacher. The teachers were recruited through personal connections and all teach in the city of Toronto, Ontario, Canada. Teachers were asked a variety of questions about their experiences with out-of-tune singers. They were asked to detail specific experiences, explain teaching methods, and provide their thoughts on the concept of “tone-deafness.” They were also asked about the ease of accessing current research being done in music education. Appendix A includes transcriptions of the four interviews, as well as further details about each teacher. Quotes from each of the four teachers (identified in the text by the letters A through D) are excerpted from these interviews.

Results The following provides a condensation and summary of many key observations and insights gleaned from the four teacher interviews.

TEACHING METHODS Even though these four teachers taught a variety of ages (from fouryear-olds to adults), they shared many of the same thoughts on the problem of singing in tune and how best to help their students. The three teachers from the elementary and high schools all agreed that

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singing together with others is important for helping those who struggle with pitch-matching. One of the high school teachers (Teacher C) told the story of a young boy who struggled severely not only with matching pitch, but also with hearing differences between pitches; one of her methods for helping him was to recruit a friend of his of the same voice part, and have him sing along with the other boy during his remedial sessions with her. The elementary school teacher (Teacher A) told a similar story, of a little girl who wanted so much to improve her singing that she would spend her recesses with a friend and practice singing with her. The other high school teacher (Teacher B) believes that this is such an important method that she rarely works with these students individually anymore, and instead encourages them to join the choir and participate in sectionals, where they sing together with their own voice part. She even records herself singing each voice part (from a choral piece) individually and emails her students the digital file, so they can practice at home. She says this is vital, especially since many of her current students cannot play the piano or sight-read musical notation. Another method that most of the teachers have employed with out-oftune singers is playing notes on the piano and asking the student if they can discriminate between them. Many of the students struggle a great deal with this initially, and are incapable of telling whether one note is higher or lower than

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the other, even when the intervals are several tones apart. The teachers described the painstakingly slow process of improvement (several months or longer), starting with very wide intervals and training the student to hear the difference, and then gradually moving on to intervals that are closer together. Teacher A, as a teacher of younger children, had many ideas for working with this population. She said that letting children “physicalize” music helps them free their singing voices and relaxes them: “...when you get fabric and you let them dance around and sing, they love that.” She also noted that, especially for children with learning or reading disabilities, the visual requirements of deciphering notation on a musical staff can be quite difficult. She has found that using giant staff paper and marking the middle line in red is a huge benefit to these children in helping them sight-read music. Interestingly, Teachers B and C pointed out that out-of-tune singers often benefit from being taught how to listen for and find the first note. Often, if that note is off, the rest of the song is off; if the first note is correct, the rest tends to follow.

FACTORS AFFECTING THE SINGING VOICE The general consensus among the teachers interviewed was that they didn’t believe anyone was truly “tone-deaf,” to the point of being unteachable. All the teachers seemed to put a great deal of energy, thought and personal time

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into aiding students that struggle to sing in tune. They have also come up with many different hypotheses to explain why some people may struggle more than others with pitch-matching. One point made by almost all of the teachers was that singers sometimes have trouble producing the right notes because “they can’t…figure out what their singing voice is.” As Teacher A points out, children have difficulty differentiating and coordinating between their singing voice and their speaking voice. They also run into difficulties by trying to copy the singing voices of others (i.e. popular music entertainers) whose singing ranges do not match their own, making it even harder to produce the correct notes. Teacher C mentioned something similar about the boy she struggled with, saying “Maybe he just doesn’t know how to use his vocal apparatus to sing the right pitch”; the private voice teacher (Teacher D) expressed the same concerns as well, and works extensively with her students to help make them aware of the way they are shaping their mouths and using their face, throat, and diaphragm muscles. All of the teachers mentioned correct breathing and posture techniques. They highlighted the importance of this when working with their students, with Teacher B making a helpful comparison: “Singing isn’t just opening your mouth and having notes come out…You wouldn’t find a runner who all of a sudden just goes and runs a marathon without warming up…for singers, our

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preparation is proper breathing.” They also cited emotional stress as a factor that can affect control of the voice and therefore the proper production of notes. Teacher D spoke extensively about the importance of being aware of physical problems that can contribute to out-of-tune singing. In her practice, she has encountered people with heart problems, thyroid illness, pregnancy-induced hormone changes, acid reflux, allergies, and premenstrual tension, all of which have caused dramatic effects on their singing voice. For younger boys, the hormones associated with puberty also have obvious dramatic effects on the voice as it changes. Teacher C said that other teachers recommend not singing during this period at all, so as not to cause vocal damage; she personally doesn’t agree with this, and says that it is better to just have an awareness of the issue and accommodate the boys when necessary, usually by exempting them from singing particular notes they are having trouble reaching or controlling. While these physical factors affected pitch production, in most cases the singer was aware of the difficulties. Nevertheless, if physical concerns can wreak havoc even with a good singer’s best intentions, it is easy to imagine how a poor singer’s difficulties would only be compounded by a lack of awareness of how to control the body for correct vocal production. It is possible that out-of-tune singers who have intact pitch perception abilities may have some sort of motor coordination difficulty. This has already been

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proposed by Pfordresher and Brown (2007, 95). Teachers C and D have succeeded in getting an out of tune sound to suddenly become in tune, simply by asking the student to change the vowel they were singing. “Sometimes a different vowel puts a note totally off pitch,” said Teacher D. The importance of getting a student to stop and become aware of their vowels, mouth shape, breathing, posture, and tension, is something all teachers mentioned. Teacher D told the story of a young woman she worked with for a long time; the student had severe difficulties matching pitch and singing in tune. Teacher D worked with her extensively on singing technique and body awareness, and got to the point where, with constant vigilance during lessons and stopping her every time she sensed something was about to go wrong, she could get her to sing fairly well. However, it seemed to be quite difficult for the girl to do this on her own: “…take her out in public or go to do an exam, and she would merrily just carry on, think about having fun with the song, and just slip every time…she couldn’t get rid of it.” It is extraordinarily difficult to pay attention to every moment of sound production, especially when someone has already taught themselves to sing one way and needs to unlearn it. Teacher C compared this challenge to learning a second language—you can be made aware of the different ways you need to shape your mouth to produce a word

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correctly and get the word right, but to do so consistently would take a vast investment of time and energy. Perhaps some singers find this process more difficult than others, just as some people have a natural affinity for language and others do not; this could explain their difficulty responding to their teacher’s instructions. Teacher B tries to slow down the singing process and allow students to become acutely aware of what they’re doing. This process, which she learned from another teacher at a conference, is called “audiating”: …often, if you say, “you’re not in tune, fix it,” they keep singing. They don’t stop and start again, they just keep singing and get louder. So I say, “Stop singing. Step number one of audiating, you have to listen.” And I’ll play the note, a few times. And they have to listen…Sometimes I’ll make them do it with their eyes closed. So they really hear the note. And then I’ll say, “Step two, breathe and pretend you are singing but don’t sing. Go through the process of singing but don’t do it and I’ll play that note instead.”…So it’s like they go through the motion and they don’t sing but they hear me play. And then the third step is to sing. Every single time, it works. They get the note. This “active listening” process, as well as active engagement with and awareness of what one’s body is doing, seems to be an important point for all the teachers.

FAMILIARITY WITH MUSIC Both Teacher A and Teacher B noted that there are often children in their classrooms who grew up in different musical cultures. These children 15

may have difficulties properly hearing or singing music based on Western major and minor scales if, for example, they grew up singing and listening to music that contains quarter tone steps. Teacher A also pointed out that some parents simply do not sing at home with their children or expose them to much music at all. This can affect a child’s ability to produce correct notes while singing, especially when they are still very young.

HOW OUT-OF-TUNE SINGING AFFECTS THE ENSEMBLE Many adults who have trouble singing in tune have a similar anecdote: when they were in school, their teachers told them to sit in the back row of the choir, or, even worse, “sing fish” (mouth the words without sound). Teachers A and B both mentioned how traumatic this can be, especially for a young child. When asked how they dealt with out-of-tune singers in a performance situation, each teacher had her own way around the problem. Teacher B spoke of the way she moves individual singers around, based not on where they will be heard less, but rather on what will be best for the individual. For example, when she had an alto who had trouble staying in tune, she moved her to the very edge of the altos, away from the sopranos and the men. With another singer, she moved her to the very front row, because what she needed was for the sound of the choir to come into her ears from behind. Teacher C explained

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that, “…before a competition or something, [if] you don’t have time to work with the person…I have to admit that I will say “Mouth this for a moment.” This allows the student to be involved in the performance but acknowledges their difficulties. Younger students raise different concerns. Teacher A, who works with very young children who are just getting to know their voices, dismisses the concern entirely, saying that the most important thing for the children is to feel the enjoyment of singing: “Let them just sing, who cares?”

THE LEARNING ENVIRONMENT This focus on the enjoyment of music, rather than on creating a perfectly polished performance is something all of the school teachers emphasized. As Teacher B put it: I’m very passionate about [enjoying music] and I think maybe because I’m so passionate that passes on to the kids and they understand…that this is a joy to be here singing and who cares? We don’t need to be the best at it. So long as everyone is happy and enjoying what they’re doing, I’m happy. The teachers spoke of the importance of making sure the classroom environment is a safe place, where students feel comfortable taking risks and being vulnerable. As Teacher B pointed out, “[Our voice is] the one instrument we carry with us for the rest of our [lives]…you have a job, a responsibility to help.” She even carries out trust exercises with her students at the beginning of 17

the school year, to make sure they all feel very comfortable with each other. She explained that sometimes, students with pitch-matching problems will not sing out, and that makes it difficult to correct the problem. By making it feel very safe to sing, she counteracts this tendency. She will even ask one of these students if they would like to help demonstrate the problem to the rest of the class. By addressing the problem in this way, she alleviates the embarrassment and provides confidence for the student. Not only does she take the time to be aware of the problem, she also “normalizes” it by explaining that it is a common problem and reassuring the students that it is fixable. Teacher A also tries to make the classroom environment a very comfortable and safe place for her young students. She explains to them that singing “is like taking a chance…when you take a chance, you take it with everyone there with you. It’s not like you’re there out on your own, we’re there to support you.” She says that making music is a huge risk, even for children, and that teachers have to “make [the classroom] a safe place for them to share who they are. Your voice is a very personal thing.” Teacher C similarly spoke of the importance of a very inclusive classroom, and highlighted the benefit of including other aspects of music in the classroom besides singing and music theory. She understands that students become more engaged with music in general if the curriculum allows them to

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chose which aspects of music they engage with. She gives them this freedom to explore by providing a variety of instructional methods, musical examples, and opportunities to research music that is close to them. She also pointed out the importance of the teacher’s mental state, which can affect the students: “Of course when you are tired, you have less passion for your subject,” and this affects the students’ engagement. Even Teacher D, with her private students, understands the importance of the social environment on someone’s ability to sing in tune. She stresses that it is not always wise to push a student who is having an emotionally difficult day (i.e. because of a failed exam or breaking up with a boyfriend), and that it can be better to wait for another day. The teachers said they take measures to make sure that teasing is minimized or avoided. Teacher B goes so far as to impress upon her students that something as subtle as glancing over at a friend when someone is singing out of tune “will stay with that person forever.” All of the school teachers reported very low levels of teasing around out-of-tune singing. Teacher A explained that by the second grade, everyone is already used to each other’s singing voices, and Teacher C expressed her confidence that our society in general has shifted away from that kind of environment: “…we are in a different era; everything has to be equal; everything has to be accepted. And I think we are in beautiful times when there is no wrong.” Whether the absence

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of teasing in these teachers’ classrooms is truly a cultural shift or just evidence of the teachers’ passion and tolerance reflected in their students, it is an encouraging thought that, despite the ever increasing reports of school bullying that we hear about in the media, the music classroom may be one small place where everyone can risk exploring this aspect of themselves—their voice— without fear.

MUSIC EDUCATION MORE THAN JUST THE “RIGHT NOTES” While all the teachers were very interested in helping their students sing in tune, some also expressed the belief that music education is not just about getting students to sing perfectly or having polished, professional performances. Teacher B explained that it is rare if even one of her students ends up studying music at the university level, so her purpose is not perfection in performance, but something else: I’m trying to train my students who are going to have music with them for the rest of their lives. So they can go to choral concerts and listen and be able to say, “Oh, listen, the tuning was not quite right there,” or “Oh, listen to that chord, it’s perfectly in tune,” or even to just enjoy it, just close their eyes. I have a former student who wrote me that he doesn’t sing anymore but he goes to every [University] choral concert there because he said he’s meant to be in the audience and just know the beauty of it. Teacher A pointed this out too. She is trying to give her students basic music literacy, not only as a skill in and of itself, but so they can use that skill 20

to appreciate and enjoy music. She exposes them to different instruments, musical cultures, dancing, composition, etc., as well as teaches them how to recognize intervals and how to read musical notation: Enjoyment of music is for everybody. It’s not just for people with great voices…there’s a musical soul, so that’s what you want to feed. It’s the poetry, they’re seeing the world, they’re expressing it through music and everybody can do that. She also believes that getting children involved in performances is important, so they can see the work that goes into them and feel a sense of accomplishment. Sometimes, if she knows a child really needs it, she will take that into consideration when they audition for a performance, because she thinks it is important to give kids a chance, to feed that “musical soul”; singing all the “right notes” is not as much of a concern. Even Teacher B’s marking scheme reflects this philosophy. She grades students on seven categories (diction, breath control, posture, etc.). “Someone can come in and not be able to match pitch… [but if she is] doing her vowels, enunciating each of the consonants, has her rhythms and cut-offs very precise, [does] the dynamics as marked, [has] good posture, she can still score [a high mark], easily, without singing the right notes.” Teachers B and C both mentioned the importance of the music classroom for students who have learning disabilities. Teacher B pointed out that the vocal classroom can make an enormous difference for students who are

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usually ...just sitting there in a math class with people there putting up their hands and answering, and for them its like hearing the teacher speak a different language. Their self-confidence takes such a beating. [But then] they come here and they can do something. It makes a world of difference for students. She also believes music is a reprieve for students who have traumatic things going on in their lives. Teacher C echoes this belief: “Music is quite a phenomenon…I think music helps in all kinds of situations, mental, physical, anything.”

PARENTAL AND SOCIETAL VIEWS TOWARDS MUSIC EDUCATION The importance of music education in the public’s mind has changed considerably since Plato wrote of the necessity of universal music education (Hoffer 2009, 9). At present, one is most likely to hear music education being mentioned as the first choice for funding cuts. It is evident that these teachers have a passion not only for the teaching of singing but for music education as a whole. They seem to approach their subject, whether consciously or not, from the philosophical viewpoint of educating the “whole” person (Gerber Jr. 2001, 36). They touched on some of the problems with the education system today, including the lack of funding to music programs due to music being considered a “frill” or unnecessary subject.

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Some students, even those enrolled in vocal classes, do not take the subject seriously, and even if they do have problems matching pitch, it is a lost cause trying to help them not because they are unteachable, but simply because they do not put in the effort. Many parents do not show the same interest in their child’s singing ability as they do in their reading or mathematical ability; however, in schools where parents do value the importance of music education, as at Teacher A’s school, the program definitely benefits, because the parents demand it. Teacher A also mentioned that when the school is a “feeder” school for high schools with big music programs, it also translates into a bigger and better elementary school program. Teacher C said that while some parents don’t have an interest in what their child is doing in their music class, many do, and are excited to hear that their son or daughter can sing really well, or does not sing well yet but has a lot of potential. She says that she “won’t take no for an answer” if there is a situation where a parent might disagree with their child’s choice to choose music as a course.

HOW TEACHERS ACCESS CURRENT RESEARCH The most prominent concern voiced by all of the school teachers when asked about their ability to access current research was that they simply did not have enough time. The life of a school teacher is occupied by many other tasks besides teaching and it seems music teachers have even more commitments

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than teachers of other subjects. Besides teaching and other various projects teachers are required to be involved in, there are also performances, competitions, and choral rehearsals. Sometimes music teachers are even asked at the last minute if they can prepare a performance for a school assembly. All of these things mean teachers usually get home late in the evenings, and after tending to their families, hardly have any time for themselves, let alone for exploring research. Another concern expressed by the school teachers was that they did not even know where to go to access the kind of research that might be beneficial to them. All four teachers did mention conferences as a primary source of information and interaction with other teachers, but these places seem to have more of a focus on practical skills and techniques. Newspapers and television programs were mentioned as places they sometimes ran across recent research. An on-line community for music teachers was mentioned by Teacher B, but she lamented the changes recently made to the site, which made it more difficult to access. Teacher C mentioned a journal that she used to receive in the mail that she found very informative, but was recently changed to e-mail only, which made it more difficult for her to access.

WHAT OTHER TEACHERS ARE SAYING Writers in the field of music education have very similar things to say as

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the four teachers interviewed for this project. The importance of individual accommodation when teaching children to sing has been written about (Merrill 2002, 50), as well as the belief that all adults and children can be taught to sing in tune with enough focused effort (Lyon 1993, 59). The state of music education in schools is also a topic of great concern, with a 2005 Canadian report finding that “20 percent of the music programs in Quebec and 21 percent of the music programs in Ontario had experienced declining enrollments in the past two to three years.” (Kratus 2007, 42). There seems to be a general feeling among music educators that “tonedeafness” does not really exist, and that all children and adults can be taught to sing in tune (e.g. Kazez 1985, 46; Lyon 1993, 59; Smith 2006, 28). Information about congenital amusia does not seem to have yet made its way into most writings about singing education (to the author’s knowledge), although the problem was recognized and written about in Music Educators Journal as early as 1948 (Cox 1948, 62). This is understandable, as the research on amusia is still quite new. However, it would be beneficial for music educators and writers on music education to be aware of this music-related disorder. One article mentions several reasons why children may have trouble singing in tune, and these echo some of the same thoughts expressed in the

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interviews—lack of exposure to music, improper singing technique, etc. (Smith 2006, 28). A comprehensive review on research related to the teaching of singing was done by Phillips in 1992. He writes of the importance of breath control and posture and makes comments similar to what the interviewed teachers spoke of (569). He also discusses the importance of pitch discrimination as a prerequisite to singing, and mentions that some out-of-tune singers may have deficiencies in tonal memory (553).

MUSICAL DISABILITIES—UNANSWERED QUESTIONS Perhaps it doesn’t matter if teachers have an awareness of “musical disabilities.”1 It is quite obvious from the interviews that these four teachers have an inexhaustible passion for their subject and are willing to invest great amounts of time and energy to help their students sing well, by tailoring their approach to each individual student’s difficulties. Even a student with a “regular” disability trying to learn math or reading could not ask for better help than this.

1

Besides amusia there are other learning difficulties that can affect the learning of pitches and other musical information. For example, children with general learning disabilities have been found to have trouble with pitch-matching (Mozingo 1997) and tonal memory (Bergendal and Talo 1969). Children with dyslexia have difficulty with the rapid processing of music (Forgeard et al. 2008); children with language disorders may have trouble processing the rapid information required for music learning (Tallal et al. 1991); and Hébert and Cuddy (2006) have suggested that some individuals have such extraordinary difficulties learning to sight-read musical notation that the difficulty be referred to as “music dyslexia.” 26

However, there are still stories of countless adults who gave up on music and singing long ago because their difficulties were too much for their teachers, or because, despite their teachers’ best efforts, they were unable to figure out how to help. Even the teachers interviewed here had a few stories of their own: Teacher D spoke of a girl who she worked diligently with for quite some time, yet in the end her pitch problems refused to go away. Teacher B worked privately with a friend who really wanted to sing, and despite improvement, he never got to the point where he could match pitches all the time. And then there are stories which defy explanation, like Teacher A’s father who cannot sing in tune at all but can nevertheless whistle perfectly in tune. Individually tailored trial-and-error interventions seemed to work for many of these teachers’ students, and the teachers all had very insightful guesses about why their out-of-tune singers had so many difficulties. Nevertheless, the problem of out-of-tune singing persists for many adults who were either not so lucky as to have a concerned music teacher stumble on the right way to help them, or who gave up on music entirely due to extreme discouragement or frustration. If the origins of out-of-tune singing were better understood, it might provide clues to developing better interventions for all. The next chapter will look at the current understanding,

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and then examine one possible reason for out-of-tune singing.

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CHAPTER 2: A CLINICAL LOOK AT OUTOF-TUNE SINGING The interviews provided a rich source of information on individual examples of out-of-tune singers and the variety of interventions implemented by their attentive teachers. While this information is invaluable, it is also important to explore this topic in the available research literature as well. The following is a review of relevant research related to out-of-tune singing and attempts to understand the problem through a researcher’s point of view. A psychological experiment, testing a particular hypothesis related to out-of-tune singing is conducted, explained, and discussed.

Normal development of musical ability A common misconception about musical ability is that it is often thought to be something innate, possessed by a special few. It is also common to hear people casually say they are “left-brained” and that is why they are not musical or artistic. These two assumptions have almost no support in the literature; music performance alone contains many different components like pitch, rhythm, tempo, contour, timbre, loudness, and spatial location (Cook 1999, 214), which are processed in various different parts of the brain (Bizley et

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al. 2009, 2064). A human being comes into the world with a brain that is evolutionarily prepared to learn many things; namely, language (Fromkin 2006, 313) and social interaction (Legerstee 2009, 4). The development of these two processes occurs at a surprisingly rapid pace. Normally developing infants as young as six months of age are capable of distinguishing between the phonemes of their native language and a foreign one (Kuhl 2007, 111). Infants also show social consciousness almost from birth (Legerstee 2009, 4) and are capable of engaging in triadic (three-person) interactions as early as three months (Legerstee 2009, 44). Like language, social interaction, and learning to walk, musical “knowledge” also develops in infancy. Naturally, infants do not come into the world knowing how to play the piano or sight-read musical notation, but neither do they come in knowing how to write a story, share with siblings, or play hockey—these are specific skills that must be taught and practiced, but they would not be possible without the development of the more basic underlying skills (language, social awareness, motor coordination), which the infant develops without specific teaching, merely exposure. Infants appear to come prepared to absorb musical knowledge the same way they absorb language. Researchers have found that infants as young as six

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months show a preference for musical scales with unequal steps and seem to learn them faster than scales with equal steps.2 Unequal steps is a universal property of all scales, regardless of culture or musical system (Thompson and Schellenberg 2006, 91). Even when the unequal scales used in the experiments are invented (not related to any real-life scales), infants seem to prefer them and are able to identify mistunings in them. Experiments to prove music’s innateness have also been done with adults. Adults without any musical training nevertheless show an ability that is comparable to formally trained musicians in detecting out of tune notes, and also have expectancies about what sequences of chords are “legal” in any given piece of music (Peretz et al. 2008, 331). While it is apparent that infants seem to internalize what is “good” music and what isn’t, the evolutionary purpose of music development is something that is under debate. Pinker proposes that music appeared in human culture as a side effect of language development, and is often quoted as saying it is nothing more than “auditory cheesecake” (1997, 534). Others propose that music did actually develop as an evolutionary adaptation (Dalla Bella 2009,

2

Examples of scales with unequal steps would be the Western major or minor scales, or the pentatonic sale; the intervals between each note in the major scale, for example, occur in this pattern of tones (T) and semitones (S): TTSTTTS. A scale with equal steps between notes would have a pattern like SSSSSSS. Such scales do not occur naturally in any known musical culture. 31

243). Regardless of how music came to appear in human culture, it is clear that we are all born with the capability to understand it.

Amusia: A deficit in pitch perception Out-of-tune singing is a problem that has been recognized for a long time, and has been called many different things: tone-deafness, tune-deafness, dysmelodia, dysmusia, and various other terms. However, this condition has only been given systematic attention by researchers in the past ten years (Ayotte, Peretz, and Hyde 2002, 238). The term “congenital amusia” has been proposed by Isabelle Peretz and colleagues (Peretz 2008, 329) to refer to poor pitch perception (out-of-tune singing usually co-occurs) that is present from birth and is not due to acquired brain damage. Amusics have profound musical deficits when compared to normal healthy controls. They are unable to tell whether two melodies are the same or different when obvious pitch changes are present (Peretz 2008, 330), and they do not improve with practice (Hyde and Peretz 2004, 356). They do not show the same sensitivity to obvious dissonant chords in music that is present even in infants (Peretz and Hyde 2003, 363). They have difficulty recognizing familiar tunes without lyrics (Peretz et al. 2008, 330). The most apparent manifestation of their deficit is when they attempt to sing—they are unable to sing in tune, and are also unable to tell that their singing is not in tune. While amusics do

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attempt to produce a rough estimate of what the pitch should be (i.e. singing one note higher than the next, if this relationship was present in the melody), their accuracy is nowhere near what is achieved by normal controls (Hutchins et al. 2010, 508). These difficulties all seem to stem from one main deficit—the inability to perceive differences between pitches; specifically, pitch differences that are smaller than two semitones (Hyde and Peretz 2004, 359). A normal adult control can perceive differences in pitch that are four times smaller than two semitones (Hyde and Peretz 2004, 359). Even more specifically, it appears to be sequential pitch relationships that the amusic brain cannot process (Hyde et al. 2006, 2562). The detection of pitch direction is also impaired (Peretz et al. 2008, 331). If an amusic cannot perceive these fine-grained pitch differences, it would make sense that they most likely do not internalize the “grammar” of the musical scale of their particular culture (Hyde and Peretz 2004, 357); as evidence of this they also seem to have impairments in perceiving pitch patterns in music (Foxton, Nandy, and Griffiths 2006, 89). A deficit in memory for pitch also seems to be present (Tillmann, Schulze, and Foxton 2009, 263); which would also hinder the ability to make sense out of music. Without this musical grammar, they are unable to set expectations about what is happening in music as they listen to it. This can interfere with amusics’ ability to gain

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enjoyment from music, as the ability to form expectations and have those expectations played with is one of the fundamental reasons the brain experiences music as pleasurable (Levitin 2006, 113). Indeed, some amusics even claim that music sounds like unpleasant noise (Sacks 2007, 112).

Etiology of amusia The pitch discrimination deficits present in amusia occur in the presence of otherwise intact cognitive abilities (Peretz and Hyde 2003, 363). Amusia is also not due to a hearing problem. It appears to be a music-specific disorder, due to a congenital anomaly that affects only pitch processing and nothing else (Hyde and Peretz 2004, 356). There is ample evidence that amusia has a genetic origin, which would mean it is present from birth (Peretz et al. 2009, 1278). 39% of family members of amusics also have amusia themselves (Peretz 2008, 32), while it is reported to affect only about 4% of the general population (Kalmus and Fry 1980).3

Amusia and the brain One study measured the electrical responses of amusic brains to differing pitch changes. They found that the amusic brain has no reaction to

3

This widely-quoted estimate may not be accurate; see Henry and McAuley (2010) for a discussion. 34

hearing pitch differences smaller than one semitone, while normal brains do. They also found that amusic brains actually “overreacted” to large changes in pitch (Peretz, Brattico, and Tervaniemi 2005, 480). Interestingly, a more recent study has shown that amusic brains do in fact seem to be able to perceive pitch differences as small as a quarter of a tone (Peretz et al. 2009, 1277). According to the authors, this is important “because it reveals that the amusic brain is equipped with the essential neural circuitry to perceive fine-grained pitch differences. What distinguishes the amusic from the normal brain is the absence of awareness of this ability (emphasis added)” (1283). Another study, this time done with magnetic resonance imaging (MRI) also showed similar results—that brain activity increased in response to fine pitch changes in both amusics and controls (Hyde, Zatorre, and Peretz 2010, 5). The authors suggested that this provides evidence for amusia as a “disconnection syndrome”—the brain is capable of perceiving the information, but it gets lost somewhere along the way and is not translated into conscious awareness.

Speculation about amusia subtypes Several researchers have proposed the possibility of there being subtypes of amusia. They have found that only a subset of amusics have vocal production difficulties (Hutchins et al. 2010, 510), deficits in discriminating

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between pure tones (Jones et al. 2009a, 69), or trouble with tests of pitch direction (Liu et al. 2010, 1691). Despite being an easily observed (or heard) problem, out-of-tune singing in non-amusics has not been given much attention by psychological researchers (Hutchins et al. 2010, 505). Peretz says that future research should focus on comparing the perception and production skills of amusics (2008, 341). There is some evidence that “tone-deafness” (out-of-tune singing with intact pitch perception ability) is either a separate disorder or a subtype of amusia. About 15% of the population believes that they are “tone-deaf” (Thompson 2007, 159). This is much higher than Kalmus and Fry’s 4%. A study that used the Distorted Tunes Test (DTT) screened eight hundred and sixty-four people, and found 69 of them to be “tune deaf” (Jones et al. 2009a, 228). This is 8.8%—more than twice as high as the oft-quoted 4%. The reason for these differing percentages is not clear. However, because many more people than any of the quoted percentages think of themselves as “tone-deaf,” it is quite possible that the difference is made up by people who cannot sing in tune, but are not otherwise deficient in their ability to tell pitches apart (Cuddy et al. 2005, 320). An interesting study done by Loui, Alsop, and Schlaug used diffusion

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tensor imaging (DTI) to look at the brains of amusics.4 They found that the arcuate fasciculus (AF) (a neural pathway that connects the frontal cortex and the area where the temporal and parietal lobes meet) had much less volume than controls. This suggests that the neural connection between these two important brain areas is impaired. The ability to discriminate pitches seemed to be correlated with the volume and size of the fiber tracts in the AF (Loui, Alsop, and Schlaug 2009, 10217). They also suggest that rather than being a quantitative difference between amusics and controls, it is likely a difference in quality, where the volume in amusics’ AF is at the low end (10219). Based on this evidence, the authors propose that amusia might be a disconnection syndrome—a disorder where two parts of the brain fail to exchange information. This is an interesting idea, because it implies that even among amusics there might be varying degrees of deficit. It would also imply that some nonamusics could possibly have milder musical impairment. They also noticed that the AF is involved in auditory-motor behavior (e.g. hearing a note or melody and then attempting to reproduce it by singing): while the superior

4

DTI uses information gathered from MRI scans to determine where in the brain there is water that is diffuse in a medium with barriers. Long, myelin-covered neurons, also known as white matter, are such a medium. Therefore, brains with less or poorly myelinated neurons will have images that reflect this as less white matter. Myelin is responsible for speeding up the transmission of electrical signals between neurons: less myelin/white matter means slower transmission of information. 37

branch of the AF seems to predict pitch discrimination ability, its inferior branch seems to predict sound production ability. One article did examine poor singing ability as separate from pitch perception deficits. The authors suggest that the inability to sing in tune may be caused by sensorimotor integration issues (Pfordresher and Brown 2006, 95). It also seems that, because out-of-tune singers can perceive pitches without difficulty, they have an accurate mental representation, but for some reason are unable to translate this into accurate singing (112). This mismatch between accurate perception but inaccurate production is reminiscent of Loui and colleagues’ “disconnection syndrome” model of amusia. It is possible that “tone-deafness” could also be a different kind of “disconnection syndrome” since mental representation and motor production seem to be indeed “disconnected”; this possibly has also been suggested by Hutchins and colleagues (2010, 510).

Is amusia music-specific? Since amusic individuals do not have difficulties with other aspects of cognitive functioning, it seems as if amusia is a disorder that affects the processing of musical pitches, and nothing else. However, there does appear to be some evidence that amusics may have other subtle cognitive deficits.

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PROBLEMS WITH PROSODY One area where amusics may have subtle difficulties is in the understanding of prosody. Prosody refers to the patterns of stress and intonation in a language. (For example, in English, we usually raise the pitch of the last word in a sentence when we want to ask a question.) Since amusics have deficits in pitch perception, it would make sense that they might have difficulty discerning meaning in speech. Studies of subjects with brain damage have shown that musical ability and speech prosody do seem to be related (Della Bella 2009, 259; Bautista and Ciampetti 2003, 467), giving credence to this idea. Studies with amusics have been done to examine this possibility, and results have been mixed; however, it does appear that amusics have subtle difficulties in understanding prosody. One study showed that amusics have trouble distinguishing between (and imitating) statements and questions when the final pitch differences are small (Liu et al. 2010, 1642). Because typical questions (in French and English) usually have a rise in pitch that is very large (over seven semitones), amusics do not usually have difficulties with everyday conversation (Hyde and Peretz 2004, 359); these large pitch differences are more easily perceived by them. It is likely that the studies which did not show evidence of a prosody deficit did not do so because they used these large

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intervals, and the study by Liu and colleagues, with smaller intervals, seems to confirm that. Another study also found that amusics seem to have trouble detecting the direction of pitch changes in speech as well (Patel et al. 2008, 366). Evidence has also been found for amusics’ impairment in decoding emotional cues in prosody (Thompson 2007, 163). Even when amusics seem to have no difficulties with normal speech prosody, it has been noted that when sentences have their linguistic information removed and only the pitches are played, amusics find this considerably more difficult (Ayotte, Peretz, and Hyde 2002). It has been suggested that the context in which language is spoken usually provides enough information on meaning, so even if sentences do contain meanings conveyed by small pitch differences, the context is usually enough to alert amusics to the meaning, and therefore no difficulty is perceived5 (Stewart and Walsh 2002, 420). Approximately 60-70 percent of the world’s languages are tone languages (Yip 2002, 1). Tone languages use comparative differences in pitch to distinguish meaning between phonemes that are otherwise identical. For example, in Mandarin, the sound [ma] can have four different meanings: [má], said with a rising tone, means “hemp,” but said with a falling tone, [mà] means

5

Interestingly, music training has also been shown to aid phonetic experts in identifying linguistic tones, and to enhance normal subjects’ ability to decode the emotions in prosody (Kolinsky et al. 2009, 235).

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“scold.” With other tone variations it can also mean “mother” and “horse” (Deutsch et al. 2004). Infants born into tone-language-speaking cultures have to be able to identify these pitch changes, or they would have severe difficulties understanding their own language. It has been hypothesized that amusia might not be as prevalent in tone-language cultures, because early and consistent exposure to tone-discrimination might compensate for a pitch processing deficit (Peretz 2008, 332). The converse is also possible—that amusic speakers of tone languages have more noticeable language difficulties than English or French speakers (Peretz and Hyde 2003, 366). Recently, a study was conducted to investigate these possibilities. For the first time, amusia was observed in speakers of a tone language (Mandarin). 3.4% of the screened participants tested as amusic, which is close to the 4% rate reported in other studies (Nan, Sun, and Peretz 2010, 2641). About half of the 22 amusics in this study had impairments in tone discrimination in their own language; however, they had no difficulties producing the four lexical tones in Mandarin. These results show that amusia is possible despite early exposure to a tone language, and that amusia is not specific to musical pitches but also affects the processing of lexical tones as well, at least for a subset of amusics. It is also interesting to note that even though they had difficulty perceiving lexical tones, their tone production was not impaired. The authors suggest that

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this points to a dissociation between pitch perception and pitch production in speech. (A dissociation between language perception and production is already well established (Pinker 1994, 317).) Because only some amusics appear to have deficits with prosody, Patel and colleagues (2008, 366) suggest incorporating tests of prosody perception into the diagnosis of amusia, to separate the possible different subtypes.

VISUOSPATIAL ABILITY A study by Douglas and Bilkey (2007) tested both amusics and controls on visuospatial ability (using a mental rotation task) and found that amusics were significantly more impaired on the task than controls. Also, when participants were asked to complete both the mental rotation task and a task of melodic discrimination at once, the control group made more errors on the mental rotation task and were slower in making the pitch judgments, suggesting that the two tasks shared some common property, which caused them to interfere with each other. This interference did not occur with amusics, however. This could mean that amusics are not using the same mechanism for pitch discrimination that normal subjects are. A recent study by Tillmann and colleagues (2010) attempted to replicate the results of the Douglas and Bilkey study. They used a line bisection task to assess the spatial representations of amusics and controls. The two groups did

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not differ on accuracy for this task. They then tested the two groups with the same mental rotation task used by Douglas and Bilkey. Their study failed to replicate the results of Douglas and Bilkey’s experiment, suggesting that amusia and visuospatial processing are not related. Another recent study, using several measures of visuospatial ability, also failed to replicate the results (Williamson, Cocchini and Stewart in press). As proposed by Patel and colleagues (2008, 366) it is possible that there are subtypes of amusia, and that the small number of amusics used in the three studies could be the reason for the conflicting results. It could be that only some amusics have visuospatial deficits, and the small samples happened to be biased towards one subtype or another. It could also be that only a specific kind of visuospatial ability is related to amusia, and that clearer results would be found by using a variety of tests to measure different aspects of this ability. Besides having a pitch perception deficit, amusics appear to have a pitch memory deficit as well (Williamson et al. 2010), so one possibility is that amusics have a deficit specifically in visuospatial memory. Under the premise of amusia subtypes, it is possible that “tone-deafness,” or the inability to sing in tune in the absence of any deficit in pitch perception, is one of these subtypes, and that visuospatial deficits may only be present in this subpopulation. The idea that visuospatial ability and musical skills are related is not

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new. A correlation has been found between memory for visuospatial location and memory for pitch and contour in melody (Mozingo 1989, 67). In a study using children, it was found that creative musical ability was correlated to spatial orientation in both boys and girls, and to spatial visualization in girls (Hassler, Birbaumer, and Feil 1985, 111). The direction of this relationship is not clear, however. It is likely that it goes both ways, with musical training enhancing visuospatial ability and vice versa. Those with higher innate visuospatial ability are perhaps more likely to continue in music lessons and do well. It is possible that both skills share a common neural representation and thus influence each other (Douglas and Bilkey 2007, 919). Several studies have also shown that pitch height is represented visually in the brain (Roffler and Butler 1968; Rusconi et al. 2006), and that spatial rotation and musical “permutations” share underlying processes (Cupchik, Phillips, and Hill 2001), again suggesting a relationship between pitch perception and visuospatial ability.

POSSIBLE PARALLELS BETWEEN A VISUOSPATIAL LEARNING DISABILITY AND AMUSIA Non-verbal learning disability (NLD) is a term proposed by several researchers (e.g. Rourke 1989) to encompass the range of deficits related to “nonverbal” ability that tend to appear together (e.g. difficulties with nonverbal

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problem solving, visuospatial material, social ability, motor coordination). Many medical conditions (metachromatic leukodystrophy, velocardiofacial syndrome, periventricular leukomalacia, and excessive radiation treatment for brain tumors) all present with a cluster of non-verbal learning deficits. Because these conditions all have white matter deficits in common, Rourke (1989) has proposed a “white matter hypothesis” for those who have non-verbal deficits in the absence of any identifiable physical condition, claiming that the NLD syndrome is likely caused by white matter deficits, especially in the right hemisphere. Because the right hemisphere contains more white matter, it is thought that general white matter damage will have more of an effect on right hemisphere functions. White matter pathways, especially in the corpus callosum, have been shown to be deficient in those with Asperger’s Syndrome (Lincoln et al. 1998), which shows a close relation to the NLD syndrome.6 The literature on NLD is interesting when compared to amusia. White matter abnormalities in the right hemisphere have also been associated with amusia (Hyde et al. 2006). Specifically, amusic brains have been found to have less white matter in the right inferior frontal cortex (Peretz 2008, 332). Also, visuospatial deficits have been found in right hemisphere lesioned patients who also have musical deficits (Särkämö et al. 2009, 2646) and white matter deficits

6

Asperger’s Syndrome may in fact be synonymous with NLD; see nldbprourke.ca/BPRA41.html for a discussion. 45

have been related to both visuospatial deficits and amusia (Hoffmann 2008, 86). Individuals with epilepsy who were going to have their temporal lobes removed were administered parts of a musical aptitude test before and after surgery. Those who had their right temporal lobes removed performed significantly worse on the subtest measuring tonal memory (Winner 1998, 376). The pitch perception and production of individuals with right hemisphere damage has been found to be impaired in comparison to those with left hemisphere damage (who show deficits in rhythm production and perception) (Alcock et al. 2000, 47). While the entirety of music processing is certainly not limited to the right hemisphere alone (i.e. Alossa 2009, 274; Dalla Bella 2009, 256; Loui, Alsop, and Schlaug 2004, 10218), it is clear that this hemisphere plays a key role in pitch processing (Dalla Bella 2009, 245). Other similarities between NLD and amusia are that those with NLD also have difficulties with prosody (Palombo 2006, 87), and amusics may have poor memory for other non-verbal sounds besides pitch (Tillmann, Schulze, and Foxton 2009, 263). Understanding prosody, or at least, the emotional and social cues in prosody, is considered to be a non-verbal ability, and those with general right-hemisphere damage do show difficulties with this ability. They often misunderstand prosodic cues, and use monotone or otherwise odd prosody in their speech (Shields et al. 1996, 474). Many studies have also shown that the

46

right hemisphere is largely responsible for processing prosodic information (e.g. Ross and Mesulam 1979). Furthermore, a case study of someone with right hemisphere seizures showed that they caused both aprosody and amusia (Bautista and Ciampetti 2003, 467). These provide an interesting parallel between amusia and NLD. If NLD and amusia share similar deficits in prosody, processing nonverbal sounds, and have similar neurological abnormalities with respect to white matter, it is possible that they both share deficits in visuospatial ability as well. Because these similarities are tenuous, the hypothesis does not go as far as suggesting amusia and NLD are the same disorder. Rather, in the same way that nonverbal deficits may have the same underlying basis (white matter deficits) though with different causes for it (excessive radiation, birth defect, etc.), it is hypothesized that amusia may also occur due to white matter deficits while having a different origin.

Rationale for the current study While there is no shortage of interventions and programs for children who have learning disabilities, the plight of the learning disabled (LD) student attempting to learn music often goes unnoticed. Those with learning disabilities presumably have cognitive deficits that undoubtedly interfere with the varied musical skills required for full participation in a music community.

47

Yet how having a learning disability might affect learning to play an instrument, singing, sight-reading, or even remembering music, has hardly been explored in the literature (see Bergendal and Talo 1969, Carlson 1986, Forgeard et al. 2008, Hébert and Cuddy 2006, Mozingo 1997, and Sloboda 1978, for isolated but notable exceptions). The problem of learning disabilities and music learning may go unnoticed for a variety of reasons. It is possible that LD students may initially be interested in music, but quickly become discouraged because of their challenges and the lack of awareness of the problem. The literature shows that specific cognitive deficits do indeed interfere with the learning of music, from phonemic awareness (Gromko 2005), to dyslexia (Forgeard et al. 2008), to processing speed (Kopiez and Lee 2006, 118), to visuospatial ability (Gillman, Underwood, and Moorhen 2002). To be useful, of course, any attempts to explain how music learning might be affected by learning disabilities should look at specific cognitive processes and compare them to specific musical tasks. Because amusia is a known condition that affects music processing, it provides an opportunity to look at a specific musical task (singing in tune) to see if it is related to any other cognitive ability—in this case visuospatial ability. The rationale for the relationship between these two abilities has already been discussed. It should be noted that this is only one of dozens of

48

hypotheses that could be examined to explore the relationship between learning disabilities and music.

Hypothesis The present hypothesis is as follows: both those with pitch perception deficits (amusics) and those with pitch-production deficits in the absence of amusia (“tone-deaf”) will perform significantly poorer than trained singers and controls on six measures of visuospatial ability. Differences between those with amusia and those with "tone deafness" will be explored post-hoc.

Methods PARTICIPANTS All participants were recruited via notices put up at York University, the University of Toronto, craigslist.org, kijiji.ca, and word of mouth. There were three types of notices: some asked for people who had ever been told or considered themselves to be tone-deaf, some asked for non-musicians, and the others asked for trained singers. The age range of participants was 18-70, with the median age being 22. There were 29 males and 29 females in the study.

MATERIALS Two subscales of the Montreal Battery for the Evaluation of Amusia

49

(MBEA) were used to screen participants for amusia.7 These tests involve listening to pairs of short melodies and deciding whether they are the same or different. The “different” melodies contain a one note mistuning, which is obvious to normal listeners but undetectable by amusics. A score of two standard deviations below the mean—under 22 for the melodic subscale, and under 23 for the rhythmic subscale (Peretz, Champod, and Hyde 2003, 66)—is thought to be diagnostic, since there is no overlap between the scores of amusics and controls (Ayotte, Peretz, and Hyde 2002, 242).8 To measure singing ability, participants were asked to sing “O Canada,” the national anthem. In cases where the participant did not know “O Canada,” “Jingle Bells” was substituted. (In a few cases where the participant did not know “Jingle Bells,” “Happy Birthday” was used.) The singing was then evaluated by three separate raters (who were professional singing teachers) as “in tune” or “out of tune” singing. Those who received an “out of tune” scoring from two of the three raters were considered “tone-deaf” and grouped accordingly (see below). The individual ratings can be found in Appendix C.

Breakdown into experimental groups Participants were divided into four main groups determined by the

7 8

An example of this test can be found online at www.delosis.com/listening A large-sample score distribution on this test may be found in Appendix B. 50

author: Amusic, Tone Deaf, Non-musician, and Singer. A fifth group (Amusiarhythm) was added later. Group 1: Amusic Those who scored 22 or below on the MBEA melodic subscale and 23 or below on the rhythmic subscale (whether or not they could sing in tune) were considered “amusic.” Participants who could not sing in tune and who scored 22 or below on the melodic subscale but above 23 on the rhythmic subscale were also included in the “amusic” category. There were 16 people in this group.9 Group 2: Tone Deaf Those who scored normally on the melodic subscale but could not sing in tune were put into this category, regardless of their performance on the rhythmic subtest. There were 9 people in this group. Group 3: Non-musician Participants who scored above 22 and 23 on the melodic and rhythmic subscales, respectively, and sang in tune were placed in this category. These participants all had less than 2 years of musical training. There were 10 people

9

Not all people who score below the cutoffs actually test as amusic after being administered the full MBEA; therefore it is quite possible that not all participants placed in the Amusic category for this study had true amusia—this must be considered when interpreting the results. 51

in this group. Group 4: Singer Participants in this category scored normally on both subscales, sang in tune, and had at least 3 years of private vocal training and/or membership in a choir that required auditions. There were 16 people in this group. Group 5: Amusia-rhythm Five participants scored normally on the melodic subscale but below 23 on the rhythmic subscale (all five could sing in tune); a fifth group was added to the analyses to accommodate these participants. The appearance of these “rhythmic amusics” is interesting in light of a recent study which found one participant who had remarkable difficulty synchronizing to music (despite normal pitch perception and singing ability). The authors suggested that this was possibly a new form of congenital amusia—“beat deafness” (PhillipsSilver et al. 2011, 967). Most amusics do not have any deficits with rhythm (Hyde and Peretz 2005).10 Other studies have also shown that some amusics have rhythm deficits, but these appear to be caused by interfering pitch changes, which may distract from the rhythm (Tillmann et al. 2010, 1). Further testing would have to be done on these individuals, however, to

10

In the current study, one Amusic participant even reacted with a startle to a rhythm difference in the MBEA rhythmic subscale, in stark contrast to her painstaking difficulty in telling two different melodies apart. 52

find out if they are truly beat-deaf or if their poor performance on the rhythmic subscale of the MBEA was due to some other reason. (The participant with beat-deafness mentioned above actually performed normally on the rhythmic subscale but poorly on the meter subscale. The latter was not administered to participants in the current study). Non-grouped participants Two participants did not fit into these categories; one had a score of 22 on the melodic subscale but a normal score on the rhythmic subscale, but nevertheless could sing in tune. Another had normal scores on both subscales and could sing in tune, but was excluded from the non-musician category because they had too many years of musical experience. Both of these person’s data were included only in the correlational analyses.

Visuospatial tasks Six measures of visuospatial ability were administered on the computer (Mueller, 2010).11 These measures were chosen because they were easily available and test a wide variety of visuospatial functions. The order of the tasks was counterbalanced between participants using a random sequence

11

All measures were obtained from pebl.sourceforge.net, with the exception of Corsi Backwards, which was provided by Reid Olsen in an email to the author on January 20, 2011. 53

generator. Corsi Forwards is a task used extensively to assess, investigate, and measure visuospatial skills, nonverbal memory, and visuospatial memory (Berch, Krikorian, and Huha 1998, 318). In the adaptation used in this study, nine blue squares are seen on the computer screen, and some of the squares “light up” in a certain order. The participant is required to click on the squares in the same order they lit up. The computer ends the task after several consecutive incorrect responses. Corsi Backwards is a similar test, but the participant is now required to click on the squares in the opposite order they lit up (i.e., the last

Figure 1: Corsi FW/BW start screen

square that lights up would be the first to be clicked). This measures not only the participants’ visuospatial memory but also their ability to keep this information in working memory (or the “visuospatial sketchpad”) and manipulate it (Kessels et al. 2008, 427). It is also thought to tap non-sequential 54

visuospatial abilities (Mammarella and Cornoldi 2005, 1064). The computer also ends the task after several incorrect responses. Corsi Forwards and Corsi Backwards produce four scores each: block span (the longest string of blocks remembered correctly); total correct (the number of correct trials); memory span (total correct + 2, divided by 2); and TOTAL (block span x total correct). Figure 1 shows a sample of the screen at the start of the Corsi tasks, before the blocks begin to light up.

Figure 2: Clock Test start screen

The Clock Test measures visual attention (Lichstein, Riedel, and Richman 2000, 153). In the version used in this study, a large ring made up of small empty circles is seen on the screen. A red dot moves around the ring, and

55

Figure 3: Mental Rotation task sample

occasionally skips a circle. Each time this happens, the participant is required to press the space bar. The task takes approximately 60 seconds and produces a score out of 60. Figure 2 shows what the participants see on starting. The Mental Rotation task is based on Shepard and Metzler’s (1971, 70) original version of this task, which is a measure of spatial ability. In this task, participants see two geometric shapes side by side. Sometimes the shapes are identical but one is a rotation of the other; other times, one of the shapes is a mirror image (that may also be rotated). The latter is considered “different” while the former is “same.” Figure 3 shows a sample of a pair of shapes. Participants indicate their choice by pressing the “D” or “S” key. In this case the correct response is “Different.” 12 The Matrix Rotation task is a measure of spatial orientation and rotation

12

The Mental Rotation scores were not used, as it was discovered later that the PEBL program was configured to record random scores for this task.

56

and short term memory (Lentz 1989, 18). In this task, a pattern is presented, and the participant is instructed to take as much time as they need to memorize

Figure 4: Matrix Rotation—1st screen and comparison example

it and press any key when they are done. This makes the original pattern disappear. Another pattern immediately takes its place, and participants are required to indicate whether this second pattern is the same or different, by pressing the left or right shift key, respectively. The pattern may be either a rotation of the one they memorized (same), or something entirely different. This task produces a score out of 20. Figure 4 on the left side shows a typical pattern presented to the participant; the right side presents a sample of a second pattern which the participant is asked to judge as being the same as (merely rotated) or different from the first. In this case the answer is “Same.” The Match to Sample task is a measure of short term visual memory

57

Figure 5: Match to Sample—1st pattern and comparison

(Swartz et al. 1995, 205). This task presents participants with a similar sort of pattern as in the Matrix Rotation task, with the same instructions for memorizing. After the key is pressed to clear the screen, a few seconds elapse before the presentation of two new patterns. Participants are required to indicate which of the two patterns identically matches the first one they memorized by pressing the left or right shift key. No rotation occurs. This task produces a score out of 30. Figure 5 on the left side shows an example of a first pattern participants might see; on the right side is an example of a screen that appears after a short delay, giving the participant two patterns to compare to the one in memory. In this case, the correct answer is “Left.” A questionnaire was also given to participants to gather personal data such as years of musical experience, handedness, their own perceptions of their singing ability, etc. A sample questionnaire is provided in Appendix C. 58

PROCEDURE Participants were given the consent form and had it explained by the reseacher before they signed. They were told the researcher was interested in looking at differences in singing ability, and how that might be related to other cognitive skills. All participants were administered the MBEA subscales first. The test was administered via computer, in a quiet room, with the volume set to a comfortable level. The participants were instructed to click “different” if they believed the second melody in the pair was different in any way, and “same” if the melodies were identical. The researcher remained in the room during the task, quietly working at another table. After the MBEA subscales, participants were given the six visuospatial tasks in a counterbalanced order. Each task was explained verbally, and there were also written instructions on the screen. All participants were then asked to sing “O Canada” (or one of the substitute songs). They did not know beforehand that this would be the song they would be required to sing. The lyrics were provided on the computer screen. The researcher started a tape recorder and then left the room while the participant sang, to minimize errors caused by nervousness. The questionnaire was then given to participants to fill out. When the tasks were complete, the participants were paid $10.

59

Results and Discussion The data was analyzed using statistical software (SPSS). Specifically, one-way Analysis of Variance (ANOVA), multiple comparisons, Pearson correlations and t-tests were performed. The nature of these analyses and the differences in the test groups that appear under them follow. 13

ANOVAS AND MULTIPLE COMPARISONS ANOVAs were used to measure differences between all groups (Amusic, Tone Deaf, Non-musician, Singer, and Amusia-rhythm) on the visuospatial tasks. When significant differences were found between groups (p1
4 M 48 >1
5 M 22 0

6 M 70 >1(?)

7 M 19 >1 8 F 20 4

9 F 20 0

10* M 24 2

11 M 26 0 12 M 19 6

13 M 24 1
14 F 18 22

15 M 25 1


24 M 29 1

25 F 21 0

26 M 32 8
27 F 51 2.5 28 F 18 14
29 F 23 0

30 M 20 11 31 M 23 0



142

TD by assess.





















Group assigned A A — N T A-R N A T N T — T S T A A-R A-R A-R N A S A N A S N S T S T

P# 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46* 47 48 49 50 51 52 53 54 55 56 57 58

Sex

Age

F M M M F F F M F M F M F F M F F F F F F M F F F F M

21 26 19 20 53 22 20 53 18 18 19 19 46 19 22 21 23 24 22 31 20 18 27 22 23 20 26

Music training (yrs.) 9 2.5 8 2 0 26 20 0 12 1 0 18 0 3 8 0 25 17.5 0 26.5 65 0 >1 41 0 0 0

LD

TD by self

TD by other

TD by assess.






























































Group assigned S A N N A S S A S A A S A A S T S S A-R S S A A S N T N

Table key: Music training (yrs.)—number of years of private music instruction in any instrument including voice (note: multiple instruments were counted consecutively which accounts in some cases for years of training exceeding participant’s age.) LD—indicates a self-ascribed learning disability TD by self—the participant considers themselves “tone-deaf” TD by other—the participant recalls being called “tone-deaf” by others TD by assess.—the participant is assessed as “out-of-tune” by at least two raters Group—indicates the group into which the participant was placed for the purposes of statistical analysis pertaining to the current study: A=Amusic, N=Non-musician, T=Tone Deaf, S=Singer, A-R=Amusia-rhythm *These two participants were left-handed

143

APPENDIX D: EXPERIMENTAL DATA Dependent Variable Corsi Forwards (block span) Corsi Forwards (total correct) Corsi Forwards (memory span) Corsi Forwards (TOTAL) Corsi Backwards (block span) Corsi Backwards (total correct) Corsi Backwards (memory span) Corsi Backwards (TOTAL) Clock Test

Amusic Tone Deaf Non-musician Singer (N=16) (N=9) (N=10) (N=16) M=5.81 M=6.22 M=6.20 M=6.88 SD=1.515 SD=1.394 SD=1.317 SD=1.500 M=8.00 M=8.78 M=8.90 M=9.75 SD=1.932 SD=1.787 SD=1.853 SD=2.266 M=4.75 M=5.22 M=5.30 M=5.69 SD=1.000 SD=.972 SD=.949 SD=1.138 M=48.94 M=56.56 M=57.10 M=69.75 SD=22.472 SD=23.415 SD=23.335 SD=28.841 M=5.19 M=6.89 M=6.10 M=6.75 SD=1.047 SD=1.269 SD=1.524 SD=1.125 M=7.19 M=9.44 M=8.80 M=9.75 SD=1.940 SD=2.789 SD=2.044 SD=1.844 M=4.81 M=6.00 M=5.60 M=6.13 SD=.981 SD=1.414 SD=1.075 SD=1.025 M=39.06 M=67.44 M=56.30 M=67.38 SD=16.743 SD=30.936 SD=25.334 SD=22.479 M=51.69 M=54.33 M=51.70 M=55.44 SD=6.405 SD=2.739 SD=3.622 SD=3.794 Matrix Rotation M=15.75 M=16.00 M=16.20 M=16.63 SD=1.949 SD=2.398 SD=4.237 SD=2.473 Match to Sample M=26.56 M=27.33 M=29.30 M=29.38 SD=3.119 SD=4.796 SD=1.059 SD=1.204 Table 3: Means and Standard Deviations for each group on all tasks Dependent Variable

F (4, 51) Corsi Forwards (block span) 2.471 Corsi Forwards (total correct) 2.440 Corsi Forwards (memory span) 2.218 Corsi Forwards (TOTAL) 2.622 Corsi Backwards (block span) 5.795 Corsi Backwards (total correct) 4.986 Corsi Backwards (memory span) 4.643 Corsi Backwards (TOTAL) 5.058 Clock Test 2.652 Matrix Rotation 1.089 Match to Sample 2.938 Table 4: ANOVA—Dependent variable by groups * indicates that the value is significant at the .05 level.

144

p-value .056 .059 .080 .045* .001* .002* .003* .002* .044* .372 .029*

Amusia-rhythm (N=5) M=4.80 SD=.447 M=7.20 SD=1.095 M=4.60 SD=.548 M=34.80 SD=7.430 M=4.60 SD=1.673 M=5.80 SD=3.271 M=4.20 SD=1.643 M=31.00 SD=21.794 M=49.00 SD=5.523 M=13.80 SD=1.924 M=28.60 SD=1.140

Multiple Comparisons (Tukey HSD) Note: for all of the following Multiple Comparison tables the mean difference is significant at the .05 level; values falling below this level are indicated in the tables by *.

Mean Difference (I) Group

(J) Group

Amusic

Tone Deaf

Tone Deaf

Non-musician

Singer

Amusia-rhythm

Std. Error

Sig.

-.410

.584

.955

Non-musician

-.388

.565

.959

Singer

-1.063

.495

.218

Amusia-rhythm

1.013

.718

.624

Amusic

.410

.584

.955

Non-musician

.022

.644

1.000

Singer

-.653

.584

.796

Amusia-rhythm

1.422

.782

.374

Amusic

.388

.565

.959

Tone Deaf

-.022

.644

1.000

Singer

-.675

.565

.754

Amusia-rhythm

1.400

.768

.371

Amusic

1.063

.495

.218

Tone Deaf

.653

.584

.796

Non-musician

.675

.565

.754

Amusia-rhythm

2.075*

.718

.043

Amusic

-1.013

.718

.624

Tone Deaf

-1.422

.782

.374

Non-musician

-1.400

.768

.371

.718

.043

Singer

(I-J)

-2.075

*

Table 5: Multiple comparisons—Corsi Forwards (block span)

145

Mean Difference (I) Group

(J) Group

Amusic

Tone Deaf

Tone Deaf

Non-musician

Singer

Amusia-rhythm

(I-J)

Std. Error

Sig.

-.778

.813

.873

Non-musician

-.900

.787

.782

Singer

-1.750

.690

.098

Amusia-rhythm

.800

1.000

.929

Amusic

.778

.813

.873

Non-musician

-.122

.897

1.000

Singer

-.972

.813

.754

Amusia-rhythm

1.578

1.089

.599

Amusic

.900

.787

.782

Tone Deaf

.122

.897

1.000

Singer

-.850

.787

.816

Amusia-rhythm

1.700

1.069

.510

Amusic

1.750

.690

.098

Tone Deaf

.972

.813

.754

Non-musician

.850

.787

.816

Amusia-rhythm

2.550

1.000

.095

Amusic

-.800

1.000

.929

Tone Deaf

-1.578

1.089

.599

Non-musician

-1.700

1.069

.510

Singer

-2.550

1.000

.095

Table 6: Multiple Comparisons—Corsi Forwards (total correct)

146

Mean Difference (I) Group

(J) Group

Amusic

Tone Deaf

Tone Deaf

Non-musician

Singer

Amusia-rhythm

(I-J)

Std. Error

Sig.

-.472

.418

.790

Non-musician

-.550

.404

.655

Singer

-.938

.355

.077

Amusia-rhythm

.150

.514

.998

Amusic

.472

.418

.790

Non-musician

-.078

.461

1.000

Singer

-.465

.418

.799

Amusia-rhythm

.622

.559

.799

Amusic

.550

.404

.655

Tone Deaf

.078

.461

1.000

Singer

-.388

.404

.872

Amusia-rhythm

.700

.549

.708

Amusic

.938

.355

.077

Tone Deaf

.465

.418

.799

Non-musician

.388

.404

.872

Amusia-rhythm

1.088

.514

.229

Amusic

-.150

.514

.998

Tone Deaf

-.622

.559

.799

Non-musician

-.700

.549

.708

Singer

-1.088

.514

.229

Table 7: Multiple Comparisons—Corsi Forwards (memory span)

147

Mean Difference (I) Group

(J) Group

Amusic

Tone Deaf

Tone Deaf

Non-musician

Singer

Amusia-rhythm

(I-J)

Std. Error

Sig.

-7.618

10.031

.941

Non-musician

-8.163

9.705

.916

Singer

-20.813

8.512

.120

Amusia-rhythm

14.138

12.335

.781

Amusic

7.618

10.031

.941

Non-musician

-.544

11.062

1.000

Singer

-13.194

10.031

.683

Amusia-rhythm

21.756

13.428

.492

Amusic

8.163

9.705

.916

Tone Deaf

.544

11.062

1.000

Singer

-12.650

9.705

.690

Amusia-rhythm

22.300

13.186

.448

Amusic

20.813

8.512

.120

Tone Deaf

13.194

10.031

.683

Non-musician

12.650

9.705

.690

Amusia-rhythm

34.950

*

12.335

.049

Amusic

-14.138

12.335

.781

Tone Deaf

-21.756

13.428

.492

Non-musician

-22.300

13.186

.448

Singer

-34.950*

12.335

.049

Table 8: Multiple Comparisons—Corsi Forwards (TOTAL)

148

Mean Difference (I) Group

(J) Group

Amusic

Tone Deaf Non-musician

Tone Deaf

Non-musician

Singer

Amusia-rhythm

(I-J)

Std. Error

Sig.

-1.701*

.523

.017

-.912

.506

.383

.444

.008

*

Singer

-1.563

Amusia-rhythm

.588

.643

.891

Amusic

1.701*

.523

.017

Non-musician

.789

.577

.651

Singer

.139

.523

.999

.700

.016

*

Amusia-rhythm

2.289

Amusic

.912

.506

.383

Tone Deaf

-.789

.577

.651

Singer

-.650

.506

.702

Amusia-rhythm

1.500

.688

.203

Amusic

1.563*

.444

.008

Tone Deaf

-.139

.523

.999

Non-musician

.650

.506

.702

.643

.013

*

Amusia-rhythm

2.150

Amusic

-.588

.643

.891

Tone Deaf

-2.289*

.700

.016

Non-musician

-1.500

.688

.203

Singer

-2.150*

.643

.013

Table 9: Multiple Comparisons—Corsi Backwards (block span)

149

Mean Difference (I) Group

(J) Group

Amusic

Tone Deaf

Tone Deaf

Non-musician

Singer

Amusia-rhythm

(I-J)

Std. Error

Sig.

-2.257

.923

.120

Non-musician

-1.613

.893

.381

Singer

-2.563*

.783

.016

Amusia-rhythm

1.388

1.134

.738

Amusic

2.257

.923

.120

Non-musician

.644

1.017

.969

Singer

-.306

.923

.997

1.235

.037

*

Amusia-rhythm

3.644

Amusic

1.613

.893

.381

Tone Deaf

-.644

1.017

.969

Singer

-.950

.893

.824

Amusia-rhythm

3.000

1.213

.113

Amusic

2.563*

.783

.016

Tone Deaf

.306

.923

.997

Non-musician

.950

.893

.824

1.134

.009

1.134

.738

1.235

.037

*

Amusia-rhythm

3.950

Amusic

-1.388 *

Tone Deaf

-3.644

Non-musician

-3.000

1.213

.113

Singer

-3.950*

1.134

.009

Table 10: Multiple Comparisons—Corsi Backwards (total correct)

150

Mean Difference (I) Group

(J) Group

Amusic

Tone Deaf

-1.188

Non-musician

-.787

Tone Deaf

Non-musician

Singer

Amusia-rhythm

(I-J)

*

Std. Error

Sig.

.479

.111

.463

.443

.406

.018

Singer

-1.313

Amusia-rhythm

.612

.589

.836

Amusic

1.188

.479

.111

Non-musician

.400

.528

.941

Singer

-.125

.479

.999

Amusia-rhythm

1.800

.641

.053

Amusic

.787

.463

.443

Tone Deaf

-.400

.528

.941

Singer

-.525

.463

.788

Amusia-rhythm

1.400

.630

.188

Amusic

1.313*

.406

.018

Tone Deaf

.125

.479

.999

Non-musician

.525

.463

.788

.589

.016

*

Amusia-rhythm

1.925

Amusic

-.612

.589

.836

Tone Deaf

-1.800

.641

.053

Non-musician

-1.400

.630

.188

Singer

-1.925*

.589

.016

Table 11: Multiple Comparisons—Corsi Backwards (memory span)

151

Mean Difference (I) Group

(J) Group

Amusic

Tone Deaf Non-musician

Tone Deaf

Non-musician

Singer

Amusia-rhythm

(I-J)

Std. Error

Sig.

-28.382*

9.608

.037

-17.237

9.295

.355

8.153

.009

*

Singer

-28.313

Amusia-rhythm

8.063

11.814

.959

Amusic

28.382*

9.608

.037

Non-musician

11.144

10.595

.830

Singer

.069

9.608

1.000

12.862

.049

*

Amusia-rhythm

36.444

Amusic

17.237

9.295

.355

Tone Deaf

-11.144

10.595

.830

Singer

-11.075

9.295

.756

Amusia-rhythm

25.300

12.630

.279

Amusic

28.313*

8.153

.009

Tone Deaf

-.069

9.608

1.000

Non-musician

11.075

9.295

.756

11.814

.026

11.814

.959

12.862

.049

Amusia-rhythm

36.375

Amusic

-8.063

*

*

Tone Deaf

-36.444

Non-musician

-25.300

12.630

.279

Singer

-36.375*

11.814

.026

Table 12: Multiple Comparisons—Corsi Backwards (TOTAL)

152

Mean Difference (I) Group

(J) Group

Amusic

Tone Deaf

Tone Deaf

Non-musician

Singer

Amusia-rhythm

(I-J)

Std. Error

Sig.

-.771

1.118

.958

Non-musician

-2.738

1.081

.099

Singer

-2.813*

.948

.035

Amusia-rhythm

-2.038

1.374

.578

Amusic

.771

1.118

.958

Non-musician

-1.967

1.233

.507

Singer

-2.042

1.118

.370

Amusia-rhythm

-1.267

1.496

.915

Amusic

2.738

1.081

.099

Tone Deaf

1.967

1.233

.507

Singer

-.075

1.081

1.000

Amusia-rhythm

.700

1.469

.989

Amusic

2.813*

.948

.035

Tone Deaf

2.042

1.118

.370

Non-musician

.075

1.081

1.000

Amusia-rhythm

.775

1.374

.980

Amusic

2.038

1.374

.578

Tone Deaf

1.267

1.496

.915

Non-musician

-.700

1.469

.989

Singer

-.775

1.374

.980

Table 13: Multiple Comparisons—Match to Sample

153

Mean Difference (I) Group

(J) Group

Amusic

Tone Deaf

Tone Deaf

Non-musician

Singer

Amusia-rhythm

(I-J)

Std. Error

Sig.

-2.646

1.963

.663

Non-musician

-.013

1.899

1.000

Singer

-3.750

1.665

.178

Amusia-rhythm

2.688

2.413

.799

Amusic

2.646

1.963

.663

Non-musician

2.633

2.164

.742

Singer

-1.104

1.963

.980

Amusia-rhythm

5.333

2.627

.267

Amusic

.013

1.899

1.000

Tone Deaf

-2.633

2.164

.742

Singer

-3.737

1.899

.296

Amusia-rhythm

2.700

2.580

.832

Amusic

3.750

1.665

.178

Tone Deaf

1.104

1.963

.980

Non-musician

3.737

1.899

.296

Amusia-rhythm

6.438

2.413

.073

Amusic

-2.688

2.413

.799

Tone Deaf

-5.333

2.627

.267

Non-musician

-2.700

2.580

.832

Singer

-6.438

2.413

.073

Table 14: Multiple Comparisons—Clock Test

154

Mean Difference (I) Group

(J) Group

Amusic

Tone Deaf

Tone Deaf

Non-musician

Singer

Amusia-rhythm

(I-J)

Std. Error

Sig.

-.250

1.124

.999

Non-musician

-.450

1.087

.994

Singer

-.875

.954

.889

Amusia-rhythm

1.950

1.382

.624

Amusic

.250

1.124

.999

Non-musician

-.200

1.239

1.000

Singer

-.625

1.124

.981

Amusia-rhythm

2.200

1.505

.591

Amusic

.450

1.087

.994

Tone Deaf

.200

1.239

1.000

Singer

-.425

1.087

.995

Amusia-rhythm

2.400

1.478

.489

Amusic

.875

.954

.889

Tone Deaf

.625

1.124

.981

Non-musician

.425

1.087

.995

Amusia-rhythm

2.825

1.382

.260

Amusic

-1.950

1.382

.624

Tone Deaf

-2.200

1.505

.591

Non-musician

-2.400

1.478

.489

Singer

-2.825

1.382

.260

Table 15: Multiple Comparisons—Matrix Rotation

155

MBEA subscale correlations The following tables give MBEA subscale correlations with visuospatial tasks showing significant values.

MBEA (melody subscale) and

Significance (p-value)

Strength

Corsi Forwards (memory span):

.049

.259 (weak)

Corsi Backwards (block span):

.000

.445 (moderate)

Corsi Backwards (total correct):

.002

.400 (moderate)

Corsi Backwards (memory span):

.007

.351 (weak)

Corsi Backwards (TOTAL):

.001

.412 (moderate)

Match-to-Sample:

.001

.441 (moderate)

Table 16: MBEA melody subscale significant correlations with visuospatial tasks

MBEA (rhythm subscale) and

Significance (p-value)

Strength

Corsi Backwards (block span):

.004

.369 (weak)

Corsi Backwards (total correct):

.002

.393 (weak)

Corsi Backwards (memory span):

.006

.354 (weak)

Corsi Backwards (TOTAL):

.004

.372 (weak)

Match-to-Sample:

.002

.395 (weak)

Table 17: MBEA rhythm subscale significant correlations with visuospatial tasks

156

Table 18: Mean scores on all tasks by gender* Dependent Variable Corsi Forwards (block span) Corsi Forwards (total correct) Corsi Forwards (memory span) Corsi Forwards (TOTAL) Corsi Backwards (block span) Corsi Backwards (total correct) Corsi Backwards (memory span) Corsi Backwards (TOTAL) Clock Test Matrix Rotation Match to Sample MBEA (melody subscale) MBEA (rhythm subscale)

Female 5.90 8.14 4.90 50.66 5.66 7.86 5.14 46.34 52.79 15.83 28.03 23.66 24.24

Male 6.55 9.45 5.52 64.14 6.52 9.31 5.93 64.97 53.03 16.07 28.28 24.14 24.76

*(males: N=29; females: N=29)

Table 19: t-test for equality of means by gender Dependent Variable Corsi Forwards (block span) Corsi Forwards (total correct) Corsi Forwards (memory span) Corsi Forwards (TOTAL) Corsi Backwards (block span) Corsi Backwards (total correct) Corsi Backwards (memory span) Corsi Backwards (TOTAL) ˚˚ Clock Test Matrix Rotation Match to Sample MBEA (melody subscale) MBEA (rhythm subscale)

t (56)˚ -1.705 -2.537 -2.365 -2.055 -2.303 -2.207 -2.365 -2.760 - .185 - .343 - .323 - .498 - .474

p-value (2-tailed) .094 .014* .022* .045* .025* .031* .022* .008* .854 .733 .748 .620 .638

* Significant at .05 level

˚A negative t-value indicates that the female estimated mean was lower than the corresponding male estimated mean.

˚˚Needed to have equal variances not assumed. df=48.760.

157

Table 20: Raw participant task data MBEA SUBSCALES Melody Rhythm

P#

VISUOSPATIAL TASKS Corsi Forwards b. span

tot. corr.

Corsi Backwards

mem. TOTAL b.span span

Match Clock Matrix to Test Rotation Sample

tot. mem. TOTAL corr. span

158

1

18

23

8

9

5

72

6

8

5

48

23

54

12

2

15

19

5

7

4

35

4

5

4

20

24

56

18

3

22

28

8

11

6

88

8

13

8

104

29

55

16

4

29

27

8

10

6

80

8

10

6

80

30

56

17

5

24

24

6

9

5

54

8

12

7

96

30

58

18

6

23

21

5

6

4

30

2

1

2

2

27

41

17

7

23

27

8

12

7

96

8

12

7

96

30

55

15

8

21

26

5

7

4

35

6

10

6

60

29

57

17

9

24

24

5

8

5

40

6

9

6

54

30

53

16

10

26

28

6

9

5

54

6

9

6

54

30

52

19

Melody Rhythm

P#

Corsi Forwards b. span

tot. corr.

Corsi Backwards

mem. TOTAL b. span span

Match Clock Matrix to Test Rotation Sample

tot. mem. TOTAL corr. span

159

11

27

28

8

12

7

96

9

13

8

117

29

57

15

12

27

27

8

11

6

88

8

12

7

96

27

49

16

13

25

27

6

9

5

54

6

8

5

48

26

55

16

14

23

23

8

10

6

80

5

8

5

40

32

57

19

15

30

17

5

8

5

40

7

10

6

70

29

51

14

16

17

16

6

9

5

54

4

5

4

20

21

52

15

17

23

21

4

6

4

24

6

9

6

54

30

52

14

18

27

22

5

8

5

40

4

4

3

16

29

46

13

19

23

20

5

8

5

40

5

7

5

35

28

55

12

20

23

29

5

6

4

30

5

7

5

35

28

49

5

21

18

17

5

7

4

35

6

9

6

54

28

55

14

22

25

28

6

9

5

54

6

9

6

54

28

57

15

Melody Rhythm

Corsi Forwards b. span

Corsi Backwards

23

22

28

4

tot. corr. 6

24

24

25

5

8

5

40

6

9

6

25

16

20

3

4

3

12

4

4

26

28

30

9

14

8

126

7

27

27

30

5

7

4

35

28

25

24

6

10

6

29

24

22

5

7

30

28

30

5

31

25

21

32

25

33

P#

mem. TOTAL b. span span 4 24 5

Match Clock Matrix to Test Rotation Sample

tot. mem. TOTAL corr. span 6 4 30

160

28

40

15

54

29

57

20

3

16

23

42

12

11

7

77

30

57

20

4

6

4

24

30

52

16

60

5

6

4

30

29

59

14

4

35

7

5

4

35

15

50

11

7

4

35

7

10

6

70

30

57

17

8

10

6

80

8

13

8

104

28

54

18

25

8

10

6

80

6

11

7

66

30

58

13

17

20

8

10

6

80

5

7

5

35

23

57

16

34

25

28

6

10

6

60

6

8

5

48

30

49

18

35

28

28

8

11

6

88

8

11

7

88

29

51

16

Melody Rhythm

Corsi Forwards b. span

Corsi Backwards

36

19

24

5

tot. corr. 7

37

27

27

5

6

4

30

6

9

6

38

29

28

8

13

7

104

7

8

39

20

26

8

11

6

88

6

40

27

29

8

10

6

80

41

22

22

6

10

6

42

22

16

5

6

43

24

27

5

44

20

25

45

18

46

P#

mem. TOTAL b. span span 4 35 5

Match Clock Matrix to Test Rotation Sample

tot. mem. TOTAL corr. span 7 5 35

161

30

44

15

54

30

58

19

5

56

28

52

11

9

6

54

30

42

18

8

12

7

96

30

57

15

60

7

10

6

70

30

58

16

4

30

5

7

5

35

26

50

15

8

5

40

8

11

7

88

28

48

17

8

10

6

80

5

8

5

40

30

59

17

18

6

8

5

48

3

4

3

12

24

50

18

25

27

8

13

7

104

9

13

8

117

30

59

19

47

27

30

5

6

4

30

6

8

5

48

29

57

18

48

23

23

8

10

6

80

7

10

6

70

30

59

17

Melody Rhythm P#

Corsi Forwards b. span

Corsi Backwards

162

49

28

29

5

tot. corr. 8

mem. TOTAL b. span span 5 40 6

50

26

16

5

8

5

40

6

8

5

51

23

22

8

11

6

88

8

11

52

30

29

5

7

4

35

6

53

22

23

6

10

6

60

54

22

21

5

7

4

55

28

29

8

10

56

24

27

5

57

23

20

58

30

30

Match Clock Matrix to Test Rotation Sample

tot. mem. TOTAL corr. span 7 5 42

27

48

17

48

29

51

13

7

88

30

56

19

10

6

60

29

50

17

6

8

5

48

29

58

18

35

6

8

5

48

27

53

16

6

80

7

10

6

70

29

55

17

8

5

40

4

6

4

24

27

45

17

8

10

6

80

5

7

5

35

30

54

18

6

8

5

48

6

10

6

60

30

51

19