Cultural Influence on the Perception and Cognition of Musical Pulse and Meter

DISSERTATION

Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University

Hsiang-Ning Kung

Graduate Program in Music

The Ohio State University

2017

Dissertation Committee:

Udo Will, Advisor

Eugenia Costa-Giomi

Lois Rosow

Copyrighted by

Hsiang-Ning Kung

2017

Abstract

This dissertation revisited the Western contemporary theories of pulse and meter through an embodied perspective, holding that both pulse and meter are cognitive constructs based on the internal and external interactions, with the former universally perceived and the latter more culturally dependent. Contemporary Western metrical theories are based on a hierarchical structure, with pulse as a referential unit. Developed in a literary tradition, these theories are based on abstract principles rather than actual listening experiences and are therefore inadequate in most non-Western contexts, where oral traditions dominate. By critically reviewing the interaction between culture and meter, this study attempted to find a common ground for cross-cultural discussions of meter.

In a behavioral experiment, 10 loops of Turkish rhythmic patterns (representing

Middle-Eastern rhythms) were presented to three groups of subjects who had listening experience with 1) Middle-Eastern music (metrically and culturally familiar group), 2)

Indian music (metrically familiar but culturally unfamiliar group), and 3) no experience with music of complex meters (unfamiliar group). The participants responded to pulse and meter, respectively, in the two parts of the experiment. All rhythmic patterns were presented at two tempi—one around 120 bpm (beat per minute; human’s preferred tempo

ii for pulse perception) and one in a double that tempo. The temporal difference was used as a variable to manipulate the participants’ choice of reference level when responding to the stimuli. In addition to the behavioral responses, participants gave verbal feedback about their entrainment strategy and filled out a questionnaire about their musical cultural background at the end of the experiment session.

This study examined whether and to what extent bodily responses to pulse and meter are influenced by cultural factors, with the former as a natural kind of mechanism and the latter a culturally dependent ability. It inquired about the relationship between response to pulse and response to meter (proportional or dissociated), as well as the role of grouping and entrainment in metrical comprehension. The study found cultural factors to greatly influence the ability for and the tendency of grouping. The ability for responding to pulse, due to its connection with the motor system, appeared to be less affected by cultural factors. However, compared to the other two groups, the listening habit (i.e., grouping) of the “metrically and culturally familiar group” interfered with the listeners’ response to pulse, and to some extent, prevented them from tapping isochronously. The results showed no evidence of hierarchical processing in metrical perception, suggesting that what we understand as metrical perception can in fact be explained by entrainment to the surface sound sequences through gestalt grouping.

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Dedication

To my Shepherd, God of the hills and valleys. To my parents, who love me unconditionally.

Acknowledgments

Foremost, I would like to express my sincere gratitude to Dr. Udo Will, my advisor, for all the guidance and support over the course of my PhD study. I would not have accomplished this dissertation without him.

I would also like to thank the rest of my committee, Dr. Lois Rosow and Dr. Eugenia

Costa-Giomi, for their insightful comments and encouragement.

My sincere thanks also go to the Musicology department at OSU, the School of Music, for its financial support and all the opportunities for me to grow as a teacher.

I wish to thank the participants in the experiment for their time and patience. They made a great contribution to my research.

I also thank my colleagues, especially Yong-Jeon Cheong and Steven Wilcer, for the stimulating discussions and the collaborative experience.

Thanks to my brothers and sisters in Christ, who have offered me all kinds of encouragement and food during the past few months (years, to be precise). Words cannot express my gratitude for their care for me.

Thanks to Sabrina L. for her editorial advice. I have learned a lot from her.

Lastly, I would like to thank my parents’ continuing love and support throughout my PhD journey.

Vita

2005...... B. A. Soochow University, Taipei, Taiwan

2008...... M. M. Manhattan School of Music

2010 to 2012 ...... Graduate Teaching Associate, School of

Music, The Ohio State University

2012 to 2015 ...... Lecturer, School of Music, The Ohio State

University

Publications

Kung, H. (2015). Bach The Preacher and Theologist? Journal of Ewha Music Research Institute 19(3), 93-110. Kung, H., & Will, U. (2016). “Not On The Same Page” – A Cross-Cultural Study on Pulse and Complex Meter Perception. Proceedings of the 14th International Conference on Music Perception and Cognition. Paper presented at ICMPC14, San Francisco, 5-9 July (pp. 816-819). San Francisco: ICMPC.

Fields of Study

Major Field: Music Area of Emphasis: Cognitive Ethnomusicology

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Table of Contents

Abstract ...... ii

Dedication ...... iv

Acknowledgments...... v

Vita ...... vii

List of Tables ...... xii

List of Figures ...... xiii

Chapter 1. Embodied Musicality ...... 1

Introduction to Mind-Body Integration ...... 1

Soma ...... 2

Non-Cartesian Philosophy...... 5

Integrating Culture and Body ...... 7

Limits of the Research Based on Western Notation ...... 14

Summary ...... 17

Chapter 2. Revisiting Pulse ...... 19

Rhythm ...... 19 viii

Entrainment ...... 22

Pulse ...... 25

Preferred Pulse Tempo ...... 26

Pulse–Beat Distinction ...... 27

Contemporary Pulse Theories ...... 28

Summary ...... 34

Chapter 3. Meter and Culture ...... 36

Background vs. Surface...... 36

Contemporary Western Meter Theories ...... 38

Cultural Influences on Metrical Understanding ...... 45

Problems of Applying Western Meter Theories in Non-Western Contexts ...... 45

Western Musical Meter as a Distinct Concept ...... 49

Culturally Shaped Perception of Rhythm and Meter ...... 57

Summary ...... 60

Chapter 4. Design of a Cross-Cultural Experiment on Pulse and Complex-Meter

Perception and Cognition ...... 62

Cultural Factors ...... 62

Rationale and Hypotheses ...... 65

Method ...... 70

Stimuli ...... 70

Participant Recruitment ...... 73

Experiment Procedure ...... 75

Analysis ...... 78

Task Performance ...... 78

Pattern of Tapping Response ...... 80

Synchronization ...... 81

Chapter 5. Experiment Outcome ...... 83

Task Performance ...... 83

Pulse-Periodicity Analysis (Analysis I) ...... 83

Pulse-Meter Analysis (Analysis II) ...... 86

Pattern of Tapping Response...... 90

Pulse vs. Meter Responses under Two Tempi (Analysis III) ...... 90

Response Split by Tempo and Cultural Group (Analysis IV) ...... 97

Synchronization (Analysis V) ...... 105

Chapter 6. Discussions ...... 108

Discussions Based on Quantitative Analyses ...... 108

Analyses I and II ...... 108

Analyses III and IV ...... 112

Analysis V ...... 114

Discussions Based on Qualitative Information ...... 115

Participants Recruitment ...... 115

Listening Strategies ...... 117

Major Findings and General Discussions ...... 119

Suggestions for Future Research ...... 121

References ...... 125

Appendix A: List of Rhythmic Stimuli ...... 138

Appendix B: Experiment Questionnaire ...... 139

List of Tables

Table 4-1. Examples of Indian and Middle-Eastern subdivisions of rhythmic patterns ... 67

Table 4-2. Individual mean inter-onset intervals (IOIS), standard deviations (SDs), and overall mean IOIs of all stimuli ...... 73

Table 5-1. Results for the fixed factors from the GLM analysis, showing parameter estimates, standard errors, Z statistics, and the associated probabilities for main factors and their interactions...... 83

Table 5-2. Results for the fixed factors from the GLM analysis, showing parameter estimates, standard errors, Z statistics, and the associated probabilities for main factors and their interactions...... 88

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List of Figures

Figure 2-1. Simple control scheme for tempo tracking as a sensory-guided action...... 32

Figure 2-2. Will et al.’s motor model on non-isochronous/isochronous entrainment...... 34

Figure 3-1 A subjective contour ...... 37

Figure 3-2. Example of Cooper and Meyer’s hierarchical analysis approach...... 39

Figure 3-3. Example of Lerdahl and Jackendoff’s analytic approach...... 41

Figure 4-1. Sound wave example of Dawr Hindi ...... 71

Figure 4-2. Flowchart of experiment procedure...... 77

Figure 4-3. Tapping frequencies of Groups A, I, and O of a 3-beat pattern to the pulse and the meter tasks in the fast temporal condition...... 81

Figure 5-1. Analysis I: Task performance for Pulse vs. Periodicity (Tempo) ...... 84

Figure 5-2. Analysis I: Task performance for Pulse vs. Periodicity (All) ...... 85

Figure 5-3. Analysis II: Task performance Pulse vs. Meter (Task)...... 87

Figure 5-4. Analysis II: Task performance for Pulse vs. Meter (Complexity)...... 87

Figure 5-5. Analysis II: Task performance for Pulse vs. Meter (All)...... 89

Figure 5-6. Tapping distances for the pulse task under the two tempo conditions ...... 90

Figure 5-7: Tap distances for the meter tapping task...... 92

Figure 5-8. Tapping frequency histograms for two complex patterns in the meter task.. 93

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Figure 5-9. Tapping frequency to the 3-beat patterns in the pulse task...... 95

Figure 5-10. Tapping frequency to the 7-beat Dawr Hindi pattern in the pulse task...... 96

Figure 5-11. Tapping frequency to the 10-beat patterns in the pulse task...... 97

Figure 5-12. Tapping frequency in the beat task split by groups...... 98

Figure 5-13. Tapping frequency for 10-beat Samai Thaqil pattern in the pulse task ...... 99

Figure 5-14. Tapping frequency of the meter task...... 101

Figure 5-15. Tapping frequency to the 3-beat “Tt T T” pattern in the meter task...... 103

Figure 5-16. Tapping frequency to the 4-beat pattern in the meter task...... 104

Figure 5-17. Tapping frequency to the 7-beat Nawakht pattern in the meter task...... 104

Figure 5-18. Tapping frequency to the 9-beat Aqsaq pattern in the meter task...... 105

Figure 5-19. Circular charts of group response in the meter task...... 107

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Chapter 1. Embodied Musicality

How musical and cultural is the human body? How physiological are music and culture? These questions may seem unusual at the first glance because humanities and biology are usually treated separately and considered independent of each other.

However, a closer look at their relationship will reveal, perhaps surprisingly, the profound connection and interdependence between these two seemingly unrelated fields—humanities and science, or culture and physiology. This chapter will consider this relationship, giving an overview of the mind–body, humanity–science integration. From perspectives such as philosophy, biology, musicology, and ethnomusicology, the following discussion grounds the entire dissertation by illustrating the importance of incorporating cognitive approaches with (cross-) cultural studies.

Introduction to Mind-Body Integration

René Descartes’ mind–body dualism is based on the premise that the mind

(responsible for activities of thinking) constitutes the essence of knowledge, while the body (responsible for activities of doing) serves as the mind’s extension and executive organ in space. Thus, Cartesian philosophy handles these two components as distinct from each other, with a hierarchical relation in which the mind transcends and governs the body. Influential as it had been, however, the concept started facing significant 1 challenges in the beginning of the 20th century when some philosophers sought to meld the boundaries between body and mind. Instead of viewing knowledge as a solely intellectual matter, they proposed that the experience gained through bodily interactions with the outer world also contributes to the formation of knowledge. For these non-

Cartesian philosophers, body and mind are interdependent, rather than separate, entities.

They together, with the influence from the contextual world, are interactive with each other and therefore ought to be considered as an undivided whole concerning knowledge formation. Further, time, as an additional dimension that holds these components together, makes the mind–body integration a developing process rather than a static or pre-given phenomenon.

Soma

Let us start the discussion with “body.” In The Body of Life, Thomas Hanna

(1983) used the word soma to refer to the body of life, which is different from—and transcends—the physical body in the world. To Hanna, soma is organic and adaptive, constantly adjusting itself to the surroundings, while the physical body refers to a static and close-ended object. Tracing the etymology of soma back to its Greek root, Hanna

(1983) describes it as “the living body in the wholeness” (p. 6), which involves not only the three physical dimensions (height, depth, and width) but also a fourth––time. With this fourth aspect, soma is not merely a physical entity, but a synthetic integrity that is held together through time in a process that never reaches completion. To understand this process, wrote Hanna, is “to understand the how of life” (p. 8). Thus, soma comprises the entire package of life, in which the body, the mind, and the environment are all included 2 and interrelated. It is a living unit that performs and rehearses continually. This development is ongoing and never ending.

Hanna’s thesis concurs with the non-Cartesian approach, in which “both mind and body work together to create a holistic sense of self” (Markula, 2004, p. 71). One’s thoughts thus would never be separated from one’s bodily condition. During physical illness, for example, one may not be able to think as accurately as usual; mental diseases are also indicators that emotional distress may potentially lead to physiological disorder.

This inseparability has been repeatedly tested and supported in empirical studies. As early as in the 1920s, Jacobson (1938) started to conduct a series of clinical experiments and found a strong correlation between thinking and muscle tension. Subsequent studies further affirmed that not only is one’s physical condition influenced by one’s cognition, the former also has demonstrable effects on the latter. In one experiment, for example,

Smith et al. (1947) temporarily paralyzed the subjects’ muscles while keeping them conscious. The outcome showed that when the subjects were paralyzed, they also lost their focus of thinking although remaining conscious (as cited in Hanna, 1983, p. 146), suggesting that human cognition is influenced by the physiological conditions.

Many argue that human intelligence is fundamentally embedded in physical experiences: “No matter how compartmentalized our institutional learning has become, we become educated as embodied wholes” (Shusterman, 2004, p. 57). That is, what one feels, perceives, and practices in daily life is regularly encoded into one’s entire being, including cognition. This concept is nicely articulated in Dalcroze’s Eurhythmics for music. In this method, music—especially rhythm—is taught through bodily movements

3 or using moving objects that students are already familiar with. Émile Jaques-Dalcroze believed that all the rhythms embedded in our bodies and the world surrounding us, such as walking, running, beating of the heart, and bouncing of the ball, would prepare one’s learning path toward musical intelligence and skills. The interaction between internal and external time becomes one’s (musical) rhythmic ability. Therefore, to learn musical rhythm is to discover the rhythm both inside and outside of the body. Likewise, to teach musical rhythm is not to introduce a new concept to the learners but to direct them to find similar temporal experiences from their past. This idea corresponds to Wayne Bowman’s assertion that sensations and actions are not cognitive achievements; rather, they are the quintessential core of cognition (Bowman, 2004, p. 34).

Indeed, the correlation between physical perception/embodiment and musical knowledge can be found throughout the world in various forms. Many musical terms in different cultures may reflect the way people in those cultures relate music to their body or physical perceptions. For example, unlike Westerners, who describe musical pitch according to frequencies, the concept of pitch in western and central African traditions is commonly based on instrumental construction: Their descriptions of pitch may be exactly opposite to Western ones, because the lower frequencies are usually played at a higher physical position on the instrument (due to longer keys, larger resonators, longer tubes, etc.), and vice versa. In the Amazon region, Suyá people use “young and old” to describe what Westerners call high and low pitches (Seeger, 1987), while in Indonesian gamelan, people refer to the sizes of instruments and call high and low pitches “small and large”

(Zbikowski, 1998). In the tablature notation of Chinese qin, terms of physical actions are

4 used to describe the timbres of sound because they are the actions required to produce them (e.g., “to pick,” “to hit,” “to rub”) (Wei, 2001). These interactions tell us how cognition may be shaped through distinct environments and experiences.

Non-Cartesian Philosophy

Since the early 20th century, the trend toward embodied cognition has been found in the field of philosophy and related disciplines. The body has been elevated to a more central place in the discussion of knowledge formation. Among many philosophers,

William James (1911) boldly proposed in Some Problems of Philosophy that thinking is rooted in corporeality, and that “intelligence is primarily the product of somatic cognitive processes” (as cited in Trigono, 2015, p. 59). He believed that the human body is

“capable of performing complicated forms of cognition even as it does not possess the conceptual apparatus of the discursive, conscious mind” (p. 55), and that the sensory nerves are accountable for “the education of our human hemispheres” (James, 1983, p.

86). To him, meaning is established through the actual doing in the world when the function and the consequences of an action are consistent and, repeatable in past experiences.

John Dewey (c. 1934), also a pragmatic philosopher, agreed with James on the importance of bodily experiences in cognition, and extended the idea to the realms of aesthetics and education. By differentiating between “immanent meaning as embodied sense” and “meaning as linguistic significance and of logic essence,” he believed that both of them and their immediate contexts are involved in, and mutually accountable for one’s mental function and aesthetic experience (as cited in Garrison, 2015, pp. 39–40). 5

For Dewey, knowledge is not a static status but an ongoing process: “The attainment of settled beliefs is a progressive matter,” therefore “there is no belief so settled as not to be exposed to further inquiry” (as cited in Boydston, 1981, p. 16). As such, newly encountered situations also become integrated into one’s ideology and being. Then, “the new and the old” would continually become “a re-creation in which the present impulsion gets form and solidity while the old, the ‘stored’ material is literally revived, given new life and soul through having to meet a new situation” (Dewey, 1934, p. 63).

In phenomenology, too, Maurice Merleau-Ponty (1945) developed his philosophy with an emphasis on the lived and existential body, through which he sought to depart from the traditional dualism such as between self and the world, subject and object, and phenomenological and biological. By viewing human bodies as both “physical structures” and “lived, experiential structures,” he regarded both entities in the seemingly opposing pairs in dualism (i.e., self/world, subject/object, and phenomenological/biological) as equally important and necessary to Western scientific culture. In other words, it is the continuous circulation between the two sides of the spectrum that forms the so-called mind or cognition (Varela, Thompson, & Rosch, 1991).

Merleau-Ponty’s notion of the “primacy of perception,” although not denying the logical and analytic methods of knowing the world, introduced idea that “such knowledge is always derivative in relation to the more practical exigencies of the body’s exposure to the world” (Reynolds, n.d.).

To summarize, in non-Cartesian philosophy, there is indeed a distinction between percept and concept, or body and mind. But instead of viewing the two separately or

6 locating them in a hierarchical relationship, non-Cartesians maintain that these two flow into each other as one’s experience develops, in an indivisible circulation that unfolds with the progression of time and interacts continually with its contextual situations. Non-

Cartesians believe that it is such interconnection—performed in a reciprocal, accumulative process—that has formed human cognition. Subsequently, as a result of some shared surroundings and the common physiological conditions of humans, meaning, namely the basis of sociocultural communication, is created. Such communication is not based on distinguishing external codes from internal representations. Rather, in everyday life “our bodies . . . and our environment together generate a vastly meaningful milieu out of which all significance emerges” (Johnson,

2015, p. 31). That is to say, through one’s actions and interpretation within the contexts, both the body and the environment are accountable for one’s understanding of the world.

Out of the shared and varying conditions, be they internal or external, interpersonal agreement and disagreement (namely cultures) are developed. This explains why cognition is culturally dependent.

Integrating Culture and Body

Non-Cartesian notions have challenged some approaches in the cultural and ethnographical studies that, under the influence of semiotics, assume meaning to be established by an arbitrary relationship between signs and referents. As a study of sign, semiotics holds that culture is based on the mutual understanding of, and the meaningful communication through this relationship. Since the second half of the 20th century, culture theories have been influenced by postmodernism and cultural anthropology, 7 which tend to consider culture to be autonomous systems in which meaning is arbitrarily assigned through symbol or ritual decoding. Geertz (1973), one of the leading figures in cultural anthropology, described culture as “the webs of significance [man] himself has spun [and is suspended in].” The analysis of culture is therefore “not an experimental science in search of law but an interpretative one in search of meaning” (Geertz, 1973, p.

5). This stance led him to emphasize the contextual utterance and actions of the scenarios that are to be studied. He termed this method “thick description,” which looks deeply into how one understands and interprets surrounding situations and activities. This approach seems to have made it possible for an outsider to assimilate and report on a foreign culture from an insider’s view.

However, thick description appears to be inadequate in conveyance of meaning.

Although it values the significance of context, the scope of a context is confined to the verbal level. With this method, the meanings constituted via nonverbal channels, unfortunately, all have to be limited to descriptive expressions. Verbal interpretation, which thick description largely relies on, may only reveal a partial story. Due to its nonverbal essence, music (in ethnomusicological studies) should not “be conceived as a product of word-based ideological construction” (Blacking, 1992, p. 310).

Ethnomusicologists need to be aware of the fact that conditions such as one’s perception, physical limits, and physiological activities, are equally crucial to one’s cognition. In fact, instead of pure interpretive approaches, the branches of semiotics such as biosemiotics and cognitive semiotics do have considered these above mentioned factors and seek to bridge the gap between verbal and embodied accounts with more interdisciplinary

8 research methods. Complementing culture with some hands-on and “under-the-skin” research is necessary.

In ethnomusicology, embodied musicality is not a novel idea. While not working from a scientific perspective, some ethnomusicologists have long recognized the significance of actual experience as well as the verbal limit in ethnography. One of them,

Mantle Hood, coined the term “bi-musicality” in 1960 in order to address the importance of performance practice in ethnomusicological research. He was inspired by the bilingual ability of those who speak two languages fluently, and thought that it is similarly possible, and actually necessary, for ethnomusicologists to learn to play the music of the ethnographic fields they work in. He believed that through this process, ethnomusicologists will immerse themselves more fully in the musical cultures they study. Hood (1957) proposed that only by obtaining hands-on experiences and attempting to achieve fluency in another musical language could an ethnomusicologist better understand the challenge, theory, practice, aesthetic, and other contexts of a musical culture from an insider’s perspective. His definition of ethnomusicology––“a field of knowledge, having as its object the investigation of the art of music as a physical, psychological, aesthetic and cultural phenomenon”––also reveals his view on the embodied musicality (p. 2, emphasis added).

Other ethnomusicologists have held similar views on the importance of musical experience. For example, Herndon (1974) maintained that to more thoroughly communicate a musical culture, the abilities of “music music” and “speech music,” (p.

246)—the former being hands-on participation in music practice and the latter the verbal-

9 theoretical description of music—are equally important. Blacking (1973) agreed that learning to perform is important in participant-observation fieldwork. Baily (1992, 2001,

2008), who replaced the term bi-musicality with intermusicality, further expounded on the benefits of obtaining actual performing experience in the field, noting that it helps to achieve better comprehension of the music, including its theories, modes of enculturation, people’s social status and identity, and a cognition of music-making. Even Alan Merriam

(1964), who is known for studying music anthropologically, suggested the importance of musical experience by regarding musical sound as “the result of human behavioural processes that are shaped by the values, attitudes, and beliefs of the people who comprise a particular culture” (p. 6, emphasis added). He held that it is through musical practice that the concepts and values of a musical culture are reproduced and reshaped. With actual involvement in music events, people’s perception, learning experience, and interpersonal social exchanges interact with one another, which would gradually result in distinct musical cultures.

Some ethnomusicologists have looked deeper into certain aspects of the bodily experience and recognized the importance of biology in music-making and musical culture. Blacking (1992), one of the pioneers, argued that musical ability is not only

“socially constructed” but also “genetically conditioned” (p. 305). According to

Blacking, just as every healthy infant has the potential for language ability, the potential for musicality is also embedded in every human body and can be advanced by exposure to particular contexts. Secondly, since all kinds of music-making, whether singing or playing an instrument, involve a certain level of bodily resonance and/or some

10 physiological aspects, it would be impossible to discuss the development of musicality super-organically. To ignore the body as a factor in enculturation also leads to conceptual inconsistencies, as Labby (1976) put it: “there is, properly speaking, no such thing as a distinct or separate ‘culture analysis’” (p. 12). Based on the similar concern that music- making usually engages bodily movements and their interaction with the instruments,

Baily (1985, 1992) more specifically examined the relationship between the modes of the sensorimotor system and musical structures, proposing that musical styles are shaped and conditioned to some extent by the motor pattern of the human body. It is out of what he called the “motor grammars” that the performance practices and compositional customs are fashioned.

However, Blacking and Baily did not mean that the biological prerequisites would fully determine the musical outcomes. Rather, when musicality is nurtured, the social and other external elements may provide the body with various feedback that encourages different reactions in given situations. These elements eventually lead to miscellaneous types of musical development. On the other hand, discrepancy among individuals is also a factor: What one body can manage easily might require significantly more training and effort for another. While some may practice harder to achieve that, others may simply take alternative approaches to reach similar goals. In other cases, even physical abnormalities, such as Paganini’s probable connective tissue disease that very likely contributed to his extraordinary virtuosity (Blacking, 1992; Smith & Worthington, 1967), may give rise to new techniques or musical inventions that could be adopted by other musicians and eventually become standard in a musical culture.

In addition, the development of neuroscience has pushed the research on the relationship between the body and culture into a different realm. The discovery of brain rhythm in early 20th century has inspired more research on the interaction between brain rhythm, musical cognition, and the motor actions that are essential for music-making.

The idea of brain rhythm, to be brief, is that “brains are foretelling devices and their predictive powers emerge from the various rhythms they perpetually generate,” and that

“brain activity can be tuned to become an ideal observer of the environment, due to an organized system of rhythms” (Buzsáki, 2006, p. vii). That is to say, our perception and cognitive ability emerges from the spontaneous neuron activities that are highly sensitive to the changes in the environment and are ready to adjust accordingly. As for experience, which Buzsáki (2006) defined as the “accumulation of knowledge or skill that result from direct action” (p. 221), it would not be able to unfold without the brain’s output

(activities). Richard Held and Alan Hein’s (1963) classical experiment on kitten serves as an example of the connection between action and cognition, that the understanding of space cannot be completely developed without actual, bodily rehearsals within the world.

Varela, Thompson, and Rosch (1991) discussed the relationship between cognition and experience more thoroughly in their treatise The Embodied Mind, arguing that only by bringing the two to a common ground in a circulate base can the human mind be more fully understood. Rather than choosing between external objectivism or internal (neurophysiological) subjectivism, the authors supported the enactive approach, which combines both elements into a reciprocal relationship, thus making their interaction the essence of cognition. Varela et al. elaborated on this concept with the

12 function of color vision, stating that because of its experiential and non-isolative nature, color is neither embedded solely in the surface reflectances, nor perceived through one’s neuronal activities without being regulated by ambient feedback or coupling with other modalities of experience. It is on this complex, interactive process of structural coupling that we base our understanding of the colored world. Similarly, when dealing with new situations in the environment, the body will take alternative actions in response, and when that occurs, the sense of the world will also be modified (Varela et al., 1991, p.85).

In this reciprocal loop, then, none of the elements is ever objective or autonomous. By contrast, they are deeply interlocked, giving rise together to our knowledge of the world in which we live.

These arguments and findings in cognitive science have shaken the interpretive methodology of cultural studies, which has dealt with meaning (and when mutually understood, culture) as being nurtured and given only limited consideration of its

“nature,” such as the physical, physiological, and cognitive conditions with which meaning and culture are formed. Recently, some ethnomusicologists have started to accept the notion that meaning “is grounded in the interactions of organisms with and within their environment, not in arbitrary socio-cultural conventions” (Will & Turow,

2001, p. 5), and that the formation of musicality and the process of enculturation are built on the balance and conversation between culture and nature––the two equally important elements. Despite the potentiality shared by all humans to grow musically, how people use their bodies, how their bodies develop in response to particular conditions, and how cognition is shaped through these activities, can result in quite different consequences.

All these internal and external factors will become integrated and/or lead to one another with great potential. Depending on the contextual influences, some aspects of the biological capability may be challenged more rigorously and develop more fully in one culture than in another. Out of the exchange of these social, physical, and physiological conditions, numerous musical skills, styles, and more broadly, musical traditions have come into existence and will grow continually.

Limits of the Research Based on Western Notation

Although researchers have gradually taken notice of the significance of bodily experience (see Leman & Maes, 2014, for a review on this development), and despite the fact that an increasing number of empirical approaches have been introduced into the cultural domain, these investigations are mostly limited to Western art music. As Will and Turow (2011) argued, both the researchers and the recruited subjects of these experiments are restrictively from Western cultures and have Western musical backgrounds, which focuses mainly, if not solely, on the acoustic domain of music. This is problematic because, as discussed previously, in addition to acoustic information, the accompanying physical and physiological elements are of crucial importance and cannot be ignored. Moreover, in some cultures, music is not merely or primarily an acoustic phenomenon as it is considered in the European tradition. Some cultures do not even have an equivalent word for what Westerners call “music,” for their sound-making events are always combined with other dimensions of the context, such as certain bodily movements or rituals. For them, music and these other dimensions are one integral idea instead of individual percepts. Such a phenomenon is quite common in oral-based 14 cultures, since “in the absence of elaborate analytic categories that depend on writing to structure knowledge at a distance from the lived experience (performance), oral cultures must conceptualize and verbalize all their knowledge with more or less close reference to the life-world and the immediate, familiar interaction of human begins” (Will, 1999, p.

5).

Another relevant issue is that Western (musical) culture is predominantly based on a literary system that led to the development of concepts having no or very different meanings outside this cultural framework (Cross, 2003; Will & Turow, 2011). For example, in the present Western culture, notation is used as if it is almost the complete representation of music. By translating the evanescent aural-temporal information to the visual-spatial domain, it is seemingly possible for acoustic information to be preserved in paper form, ready to be revisited at any time for reproduction. In reality, however, notations are never able to convey the reality of performance in its context; instead, they

“contribute nothing to the understanding of initial forms and the development of melodic thinking” (Will, 1999, p. 3). For example, in transcribing music, no matter which kind of notating system is used, the transcribers have to select some performance features over others to write down. Since what is significant and regarded as prominent in one culture might not be so in another, “there is no guarantee that transcribers are able to perceive and to reproduce on paper the music of another culture in any adequate way” (Will, 1999, p. 3). Very likely, the Western-developed notation system would turn out to be awkward in describing musics that are orally transmitted or literarily transcribed in the other forms

(e.g., tablature notation).

Moreover, as one’s experience with musical literacy unfolds, that experience changes and shapes how one listens to music. While the visual-spatial frameworks usually allow people to process abstract structures from a distance, those who grow up in oral musical cultures would handle the acoustic flow sequentially under the constraints of psychological presence, which only lasts about two to three seconds (Clayton, 2000). In linguistics, a field of study frequently compared to music, a substantial body of research has supported this distinction. Linguists have found that in literate societies, writing systems have changed the way people think about spoken languages. Being introduced to text reading and writing would change one’s original ability to process the spoken language (Lord, 1960; Olson, 1994) and gradually mold one’s cognition to interact with the acoustic flow in a more analytic, literate way. Olson (1994) stated: “Writing is not a simple ‘transcription’ of speaking, it affords us a conceptual model for speech” (p. 108).

Similarly, in a literate musical culture, the notation system is not only a tool that helps preserve elusive acoustic information, but also a cognitive shaper that guides one’s listening strategies. Consequently, cognition developed in a literate musical culture is likely to be considerably distinct from that developed in an oral musical culture.

In fact, one should also keep in mind that the Western art music known today, though literarily transmitted, came into being from formerly oral cultures. From the precursors of neumes to the modern staff system, the European musical notation has changed from a supplementary tool of mnemonic purpose to a precise, interpretive guideline for processing musical sound. It was not invented to represent music in the first place, but it was developed later to the extent that makes Western music culture so

16 different from those of the oral tradition. This change indicates that people of different musical backgrounds, such as how they have been trained and which musical environments they have been exposed to, may understand music in substantially diverse ways due to the variety of their previous experiences. In empirical and embodied research, therefore, it is important for researchers to consider the subjects’ past experiences and employ these parameters for cross-cultural studies instead of hastily jumping to conclusions as if the findings hold true universally.

Summary

From philosophy to neuroscience, researchers since the 20th century have come to widely believe that cognition is not based on a top-down hierarchy in which thinking rules over physical execution. Rather, it is built upon the mutual interaction between mind and body, as well as how this interaction is situated in and shaped by a given environment through bodily experience. This development continues indefinitely as time unfolds, creating an open-ended process that invites in culture. This ongoing process explains why studying culture via the embodied channel is important: As a kind of contextual environment, culture participates in shaping human cognition. As an outcome brought out by people under shared conditions, it is also shaped by human development in cognition formation. However, this concept has not been accepted widely in cultural research.

In the 20th century, while some ethnomusicologists have demonstrated their acceptance of the mind–body integration by actively practicing music to enhance their intellectual research, the interpretive approach of the discipline has unfortunately 17 broadened the distance between culture and nature, or humanities and natural science.

Nevertheless, since abundant research has made explicit that the human brain is greatly shaped by bodily experiences, this gap needs to be reconciled. That is, culture should not always be studied through a postmodernist lens as if it is isolated from nature. Neither should music, as a cultural phenomenon, be understood as merely a pure acoustic and abstract phenomenon that is to be interpreted in pure interpretive, verbal accounts.

Recently, although more and more scientific methodologies have been introduced to the research of music psychology and other newly emerged disciplines (e.g., music cognition and empirical musicology), non-Western music is still largely outside the scope of such studies. To study music cross-culturally, it is important for ethnomusicologists to incorporate more interdisciplinary methodologies such as empirical studies into the discourse, especially those of natural science, which has largely been ignored in the past.

Chapter 2. Revisiting Pulse

People have used such diverse terms in discussing or describing the temporal aspect of music that much confusion has resulted. It has been more so since the late twentieth century, when concepts of embodiment began to emerge in the field of music and corresponding empirical studies started to develop, and while they have broadened the scope of research, such interdisciplinary approaches have also increased the diversity and confusion of terminology. It is necessary, therefore, to rethink the meanings behind these terms proceeding in our discussions to clarify how they were used in the current research and possibly to find a common basis on which they can be more effectively discussed across the disciplines.

This chapter revisits the contemporary theories of musical pulse, which is one of the main concepts discussed in this study. It begins with clarification of terminology and the introduction of the concept of entrainment. The primary concept of this study, as well as the influence of cultural factors on it, will be addressed in the following chapter.

Rhythm

Rhythm is a word so familiar in both everyday life and academic writings that it seems all-encompassing enough to comprise everything and therefore hardly specifies anything. The Oxford Dictionary of English (2017) defines rhythm as “a strong, regular, 19 repeated pattern of movement or sound,” but the sub-definitions of the entry continue to describe it as “the systematic arrangement of musical sound, principally according to duration and periodic stress,” “a particular type of pattern formed by rhythm,” and “a person’s natural feeling for rhythm.” From here, one may already be wondering: Is rhythm a physical phenomenon, a specific musical style or figure, or a quality felt by the listeners? Is rhythm in the object (sound) or in the subject (mind)? If it involves them both, how are they related, and what makes people feel something to be rhythmic or

“having rhythm?” Moreover, other than in music, rhythm is also discussed in linguistics and some other categories of performing arts (e.g., dance, theater) where time is a critical element. Rhythm is also relevant even in fields that may seem only remotely related to music, such as visual art, physics, neuroscience, and astronomy. Although there appears to be a general level of agreement regarding the meaning of rhythm, which is often related to some sort of arrangement or regularity in a given space or time span, confusion usually arises when the discussion delves more deeply into the meaning and nature of rhythm.

Even within the realm of music, rhythm is too vague a term that requires more precise delineation for meaningful discussion. Using rhythm as one blanket term is not satisfactory; for example, when people describe a song as “rhythmic” or “having rhythm,” very often they mean that this song induces a sense of temporal regularity.

However, such sense of regularity pertains to the abstract percepts known as “pulse” or

“meter” that need to be distinguished from the physical sound events for in-depth analysis of rhythm.

In an effort to bring clarity to this problem, Michael Thaut (2005) distinguished between two categories of rhythm, one in the broad sense, involving “order and pattern in discernible temporal organization,” and the other more narrowly, “carrying the two core aspects of temporal organization: periodicity, and [its] subdivision into similarly structured groupings.” He understood periodicity to be “the grouping of events into successive sequences of equal temporal and spatial extent,” and by the subdivision of groupings, he meant “the similarity of internal structures among these groups” (pp. 4–5).

Thaut’s understanding of rhythm in the narrow sense involves the ideas of pulse and meter on which the present thesis expounds. Although Thaut’s differentiation between the two categories of rhythm was crucial to this thesis, he was not the only one to recognize the complexity of rhythm and to propose the need to make distinctions between the general and specific meanings of rhythm. For example, McAuley (2010) argued that the term rhythm has been used in at least two ways: one as “the sound pattern,” which he described as “the serial pattern of durations marked by a series of event,” and the other as

“the perception of that pattern,” which refers to “the perceived temporal organization of physical sound pattern” (p. 166).

In this thesis, rhythm is used in its broad sense to indicate the physical sound phenomenon as opposed to the perceptual features. In other words, rhythm here refers to the surface temporal aspects of sound sequences, which are generated by the onset timing and the temporal relation of acoustic events or caused by the sudden changes of one or more components of music such as pitch, timbre, or dynamics in a musical stream.

Phenomena such as changes in length of adjacent sounds, high pitches over a low

21 register, singers’ yodeling (rapid switches between chest and head voice), and occasional accents of a repeated sound, etc., all may produce rhythm. It is important to keep in mind that although these surface features seem to have significant influence on one’s pulse and metrical perceptions, there is no one-to-one correspondence between them. A sense of pulse can be evoked by surface rhythms even if they do not contain repeated patterns or sound events on every beat. Examples of these scenarios will be introduced in later sections, but before turning to pulse and meter, let’s begin with the concept of entrainment, which is essential to temporal processing.

Entrainment

Entrainment refers to the process by which two or more independent temporal systems synchronize with each other through mutual interaction. There are two essential components in the entrainment phenomenon: 1) the autonomous oscillators that can independently sustain their periodic or quasi-periodic operations; and 2) the oscillator’s coupling effect with the other systems when they come to interact with and adjust toward each other before gradually reaching a state of shared phase or periodicity (Clayton,

Sager & Will, 2005). The phenomenon of entrainment was first discovered in the 17th century by Dutch scientist Christiaan Huygens in an experiment in which he observed that pendulum clocks hung from a common support all moved in synchrony after one day, although they were first set out randomly (cited in Pikovsky, 2003). Ever since

Hyugens’s experiment, entrainment has been discussed and developed extensively in diverse areas, for such phenomena are found so widely and “[occur] at different scales of time and space, in both biological and mechanical systems” (e.g., synchronizing fireflies, 22 circadian entrainment, intra- and inter-person coordination of bodily movements, etc.)

(Clayton, 2012, p. 49). Despite the broad application of entrainment, this study focuses only on the entrainment in human musical perception, focusing particularly on the process through which one’s behavior comes to synchronize with acoustic temporal stimuli.

An entraining relationship may be symmetrical or asymmetrical (Clayton, 2012).

For instance, in a (small) ensemble collaboration, the musicians most likely have equal influence on one another, but when one listens to recorded music, the interaction between the two systems is hugely asymmetrical because the listener cannot influence the timing of the music. The degree of entrainment is determined by the strength of coupling force(s) between the oscillatory processes: the stronger the coupling, the larger the degree of synchronization. To analyze synchronization, researchers select reference points (such as the audible onsets) for each autonomous oscillatory process and place them in a stroboscopic analysis to measure their phase relationship (Pikovsky et al., 2001; Clayton et al., 2005). On the circular plot, when the two oscillatory systems are highly synchronized, they may, for instance, exhibit relative phase 0˚ (“in phase”). If they occupy opposite places on the circular plot , they show relative phase 180˚ and are said to oscillate in“antiphase.” However, the precision of a specific phase relationship is not the criterion for determining the presence of entrainment. Rather, Clayton (2012) explained that the evidence of entrainment includes 1) “a stabilization of the relative phase relationship,” be it in phase, antiphase, or somewhere in between; and 2) “the reassertion of this stability following a perturbation.” That is, the reference points of the two

23 oscillatory systems do not necessarily synchronize perfectly, yet their phase relationship remains more or less stable, and this stability will be reestablished after being disturbed.

The discovery of entrainment has considerably influenced what people think about musical pulse and pulse-based rhythm and challenging the applicability of the scalar expectancy theory (SET) to these phenomena. Based on experimental results first found in animals and then in humans, John Gibbon (1977) and his colleagues (Gibbon,

Church & Meck, 1984) proposed SET as a quantitative model of temporal processing, suggesting that one’s sense of timing and duration is based on an internal clock that ticks constantly as time unfolds. With an attention-controlled switch, the ticks flow into the accumulator during the target period so that the representation of duration is calculated.

The calculation is cleared whenever the switch resets, but during the target periods, the duration estimations would gradually be saved as representational codes in the memory.

The codes serve as temporal references against which new target periods will be compared, so that an individual may determine if the new periods are longer or shorter than the stored codes. However, “the entrainment-based approaches to beat (pulse),” as

McAuley (2010) wrote, overall “offer advantages over internal clock approaches” (p.

191). Rather than viewing duration or periodicity as explicit representational codes stored in memory, entrainment models represent it implicitly by the oscillator period. In the entrainment models, consecutive temporal estimates are dependent on one another, and such models “assume more gradual correction of oscillator phase and period” (McAuley,

2010, pp. 171–172). The entrainment approach also corresponds better to the idea of embodied music discussed in chapter 1. It makes more sense than SET because humans

24 naturally want to comprehend the things happening in their surroundings. Through the reciprocal exchange between external feedback and internal adjustment, we actively try to adjust to our environment. Such coupling processes are critical to the understanding of recent theories regarding pulse perception, to which we now turn in the following section.

Pulse

Musical pulse is a kind of endogenous, quasi-periodic sense of time one possesses internally or perceives in response to a stream of sound events. It is sometimes expressed in one’s movements such as head nodding, hand clapping, or feet tapping along the rhythmic groove in music listening. Most theorists have agreed that the regularity of sound sequences has significant influences on one’s pulse perception by inducing a strong feel of even intervals (Jones, 2010; Mathewson et al., 2010; also see the dynamic attending theory below). However, pulse as a subjective percept does not necessarily coincide with the surface rhythm. The sense of pulse, for example, may arise even though the regularity of rhythmic patterns is shuffled or limping. This situation is commonly found in non-Western traditions such as West African drumming and Slavic folk music in which the basic, repetitive patterns may not be built on isochronic sound sequences.

Moreover, once established and stabilized, the sense of pulse will not be easily nullified by temporary rests or syncopations of the surface stimuli. Rather, it “tends to be continued in the mind and musculature of the listener, even though the sound has stopped” (Cooper & Meyer, 1960, p. 3). Instead of being a direct result of the surface stimuli, “pulse provides a stable, dynamic referent with respect to which a complex musical rhythm is experienced” (Large, 2008, p. 192). 25

Preferred Pulse Tempo

Typically, the sense of pulse is confined to a temporal span roughly between 0.1

(100 milliseconds) and 2 seconds (London, n.d.; Clark, 1999; McAuley et al., 2006), although these limits may be identified differently by among different researchers (e.g.,

Mates et al., 1994; Repp & Doggett, 2007). However defined, within this range there is the preferred tempo around which people feel and respond to the pulse most strongly and naturally. This phenomenon of preferred tempo is found both when a stimulus is present

(e.g., showing preference for responding to stimuli at a certain rate) and when it is not

(i.e., autonomous pulse). Recent studies from music psychology have found the maximal peak of the preferred tempo to be 500 ms (2Hz, 120 bpm—beat per minute) (Will &

Berg, 2007; MacDougall & Moore, 2005), while earlier literature placed it closer to 600 ms (1.67 Hz, 100 bpm) (Parncutt, 1994; Fraisse, 1978). Despite the variations, all these researchers accepted that there is a preferred periodicity range and that this range is not directly determined by the surface rhythm, especially when the stimuli’s articulated intervals are largely divergent from it. For example, when the surface rhythm goes “too fast” or “too slow,” instead of entraining at a faster or a slower rate, the perceived pulse tends to stay around the preferred periodicity. People naturally do so by grouping rapid sounds into single pulses or by dividing large intervals into smaller ones, and this is reflected in humans’ musical behavior and movement. For example, when the music is too fast, people usually switch from tapping on every beat to every two or three beats (in the context of Western music); when the music is too slow to maintain a sense of continuation, they tend to fill in the temporal intervals with more referential pulses. In

26 fact, researchers such as McAuley et al. (2006) did find a positive association between humans’ temporal perception and motor system. This association will be examined more thoroughly in a later section devoted to the sensory-motor theory, but now we will first consider the difference between the aforementioned terms beat and pulse.

Pulse–Beat Distinction

Most scholars use pulse and beat as interchangeable terms, but in the current study, the two will be used to refer to different ideas; and it is pulse, not beat, that this research is mainly concerned with. In my opinion, the term pulse has relatively broader connotations that pertain to one’s perception. The pulse concept may be applied more freely in cross-cultural contexts, whereas the concept of beat is a product of the Western metrical notation and is a theoretical basic temporal unit, not necessarily akin to the pulse one truly perceives. In other words, it seems that pulse is mind-oriented, whereas beat is notation-oriented. Fitch (2013) also tried to differentiate between the two, proposing that the former entails “periodicity detection and extraction,” while the latter involves

“situations in which a stream of musical pulses have had a metrical structure assigned to them by a listener” (p. 3). Such “metrical structure” is usually culture-specific.

Unfortunately, other theorists have rarely recognized or taken an interest in the distinction between pulse and beat, especially before cognitive musicology started to develop. Given the literate tradition, typical pulse (or more precisely, beat) theories developed in Western musicology suppose that the time span between pulses (beats) are mechanically equal to how they are notated. Cooper and Meyer (1960) described pulses

(beats) as “regularly recurring and precisely equivalent” (p. 3). However, later 27 researchers with an embodied perspective have argued that such precision exists only in the mind as a theoretical ideal, not in real music experiences. Epstein (1995) asserted that instead of absolute periodicity, pulse is responsive to tempo change (e.g., rubato, ritardando), which is important for music expressiveness. Fitch (2013), too, indicated that pulse does not usually unfold as perfectly regular intervals, and he described it to be quasi-periodic. Even so, most of the terminology adopted today has still failed to clarify the theoretical beat from the perceptual pulse. For example, although McAuley (2010) regarded pulse as perceptual responses that interact with the temporal changes of the stimuli, he called the process of interaction “beat-based” entrainment, while he was in fact referring to, according to his arguments elsewhere in the same article, “pulse-based” entrainment. Likewise, the Large et al. (2015) article is titled “Neural Networks for Beat

Perception in Musical Rhythm,” but throughout the study, the researchers used the term pulse and discussed pulse perception instead. To avoid such confusion in this thesis, I will distinguish between the two terms clearly in the following sections, using “pulse” to specify the percept and “beat” as a theoretical unit.

Contemporary Pulse Theories

Most of the contemporary pulse theories, tested and supported by neuroscience research since the late 20th century, entail the concept of entrainment. Jones first proposed the dynamic attending theory (DAT) in 1976, and then followed it up with several studies with her colleagues (Jones & Boltz, 1989; Large & Jones, 1999). DAT explains the coordination between the endogenous, attentional oscillations and the stimuli in the environment, illustrating that these attentional oscillations are flexible and 28 can become synchronized with the external stimuli through entrainment—the coupling process in which the attentional oscillators adjust toward the regularity of the external events in order to reduce the time difference between each other. Such process “provides a mechanism by which a perceiver can come to anticipate the nature and precise timing of a future event, thereby being attentionally prepared for the anticipated stimulus”

(Henry & Hermann, 2014, p. 64). As a result, synchronizing with the periodicity of external stimuli is achieved with the least effort when the stimuli coincide with the internal attentional pulse, namely “a concentration of attentional energy within each cycle of the oscillation” (Henry & Hermann, 2014, p. 63; Large & Jones, 1999).

Moreover, the greater the regularity of the stimuli is, the greater degrees of attentional energy will be assigned to the anticipated time points, and greater synchronization between stimuli and one’s expectancies will be made. Therefore, the “perceptual precision” (level of synchronization) is to some extent determined by the temporal structure (regularity) of the stimuli (Henry & Hermann, 2014). In neuroscience, evidence has suggested that the low-frequency neural oscillations in the delta-theta range (~0.5–8

Hz; 2000–125 ms) correspond to the activities of the attentional oscillations discussed in

DAT (Henry & Hermann, 2014). These neural oscillations can be entrained by the temporal sequences from the environment. During the external–internal interactions, stimuli occurring simultaneously with the neural excitation phase (as opposed to the inhibition phase) will be perceived more easily and cause stronger responses (Cravo et al., 2013; Henry & Obleser, 2012), and the neural excitation phase is consistent with the attentional pulse (Henry & Hermann, 2014).

The other theory that scholars in recent decades have considered to be important is the sensory-motor theory (SMT) (Todd et al., 1999; Todd, 2002), which puts equal emphasis on the sensory and the motor systems in temporal processing. Rather than considering pulse (and rhythm) as passive perception, Todd holds that it involves active interaction between the sensory representation of external stimuli and the motor representation of the body. Through practice and rehearsals, “the sensory systems . . . tune into the temporal-motional properties of the physical environment, whilst the motor control system . . . tunes into the dynamic properties of its musculoskeletal system”

(Todd et al., 1999, p. 26). When the properties of the two systems coordinate with each other, the resultant motions tend to synchronize with the source. That is to say, successful entrainment happens when the information represented in the sensory and the motor systems gradually become synchronized to each other.

This sensation-motion integration makes sense for many reasons. In a direct way, making music requires ongoing coordination between one’s movements and the auditory feedback from these movements. Almost all music-making activities around the world entail some kind of movements or gestures, to produce sound or to convey expressions.

On the other hand, it is interesting to observe that among all senses (e.g., visual, tactile), hearing seems to be the dominant (though not the only) one that induces bodily movements to synchronize with the periodicity of stimuli, such as to tap to the pulses. In fact, if we look at the development of music theory, we will find that the integration of bodily movement and temporal perception is not a novel idea. Back in the 15th and the

16th centuries, the notion of tactus, a rough equivalent to beat at that time, was measured

30 by hand movements, with a downbeat motion and an upbeat motion to create a tactus

(Brown & Bockmaier, n. d.). This is an indicator of the coordination between temporal perception and motor system, although people at that time had not formulated any concept related to the sensory-motor theory.

Todd (1999, 2002) proposed three main components concerning the SMT model:

1) a sensory system that translates the external information to the internal representation,

2) a controller in the nervous system that regulates the plant and handles information from the sensory system(s), and 3) the plant, which both generates the actions to be taken and sends feedback to the controller about the dynamics of locomotion (see Figure 2-1).

Therefore, through the plant’s mediation, the way one moves will modify what one hears

(Phillips-Silver, 2009), and because the plant constantly gives feedback to the controller

(even when no real movements are taken), the motor system continually plays an active role in temporal perception regardless of whether one is actively moving. In other words, either with or without our noticing it, our ability of temporal processing is continually shaped by the feedbacks from the motor system. This notion is supported by Phillips-

Silver (2009), whose research indicated that such interaction is developed early, since infancy, despite young babies’ initial inability to move in synchrony with external acoustic stimuli. This interaction will grow continually into adulthood and throughout life

(Phillips-Silver & Trainer, 2005). Such intrinsic feedback and continual development is important to the current research, because it means that through the sensory-motor systems, a person’s temporal perception has been rehearsed and shaped by its interaction

31 with the musical environment they have been exposed to, even if they have no actual music-making experiences in these styles or practices.

Figure 2-1. Simple control scheme for tempo tracking as a sensory-guided action, with the goal being synchronizing the plant with the external source. Adapted from Todd, 1999, p. 6; 2002, p. 28).

Instead of an “either–or” explanation between DAT and SMT, the two converge in some aspects. Evidence in neuroscience suggests that the neural oscillations of sensory-motor interaction are adequate to generate anticipation for pulse or temporal sequences, as discussed in DAT (Schroeder et al., 2010; Large et al., 2015). This endogenous, intrinsic mechanism also explains why regular, (quasi-)periodic pulses may arise from the surface stimuli that might be irregular and non-periodic. Echoing this from the behavioral perspective, Will et al. (2015) have gone further to discuss the importance

32 of one’s spontaneous pulse (as expressed in periodic behaviors without the presence of stimuli) in interpreting non-isochronous stimuli, proposing that pulse response is not necessarily dependent on the auditory stimuli. With three experiments based on Indian classical music, they discovered that even during the alap section, where no perception of regularity was expected, the subjects still demonstrated pulse expressions, although their response rates seemed to be associated with the spontaneous pulse (i.e., preferred tempo), which varies from individual to individual rather than according to the stimuli. The simple integer ratios between the two periodicities (of tapping to non-isochronous stimuli and spontaneous pulse) suggested an underlying mechanism shared by the two tasks. On the other hand, during the jor/jhala sections, when the regularity of the stimuli gradually increased, both stronger inter-subject agreement and better synchronization with the stimuli were achieved.

Therefore, Will et al. have proposed the following behavioral model on human pulse perception and entrainment to non-isochronous stimuli: “As long as the dispersion of the event sequence is large,” namely, when the stimuli contain little or no temporal regularity, “motor responses are determined by subject’s internal resonance frequency and slightly modified by interactions with the external signal” (Will et al., 2015, p. 22).

However, when the dispersion is reduced to a certain point, “the interaction between internal and external oscillators increases beyond a critical value,” and “[the subjects’] periodicity of the motor responses becomes attracted to that of the external signal and adjusts to it” (p. 22). That is, when the temporal features of the stimuli become regular

33 enough, the subjects’ pulse responses take an instant leap from their autonomous periodicity to synchronization with the stimuli’s periodicity (see Figure 2-2).

Figure 2-2. Will et al.’s motor model on non-isochronous/isochronous entrainment (2015, p. 22). inc. ε = increasing coupling between internal and external oscillators.

Summary

Pulse has been considered to be one of the fundamental elements in temporal processing. From SET to DAT and SMT, the theories of pulse have developed from a strict, quantitative model to more interactive, interdependent ones based on the entrainment between the internal and the external oscillators, and pulse is believed to be intimately associated with the motor system. This is reflected both in the behavioral and perceptual preference of tempi around 500 ms (2Hz, 120 bpm) and in the intrinsic, autonomous pulse of individuals.

The current study does not treat pulse and beat as synonyms. While the former is perceptually and physiologically oriented, the latter is (Western-)theoretically oriented.

The term rhythm, not to be confused with the concepts of pulse and meter, is used to 34 indicate the sound phenomenon or surface presentation of a temporal stream. These clarifications will aid in our discussions in the next chapter, regarding musical meter and the influence that cultural factors have on it.

Chapter 3. Meter and Culture

Different from pulse, the processing of and responses to meter are strongly influenced by musical training and require special attention (Geiser et al., 2008). This is one of the indicators suggesting that cultural influences may have a larger influence on meter than on pulse perceptions. Indeed, there is increasing evidence showing interactions between cultural factors and various aspects of temporal perception and cognition (for a review, see Will, in press-a). Many of them contribute to distinct metrical understanding in different musical cultures. Beginning with a brief introduction of the major Western meter theories, this chapter presents the problems of applying them in a non-Western context and expounds on the importance of awareness that metrical concept is culturally dependent.

Background vs. Surface

Meter is cognitively constructed when one listens to a rhythmic flow. Surface rhythm seems to be determinative in such mental construct, but it does not guarantee any fixed metrical interpretation at the listener’s end. Such “background vs. surface” notion is influenced by gestalt psychology, which regards the perceived entirety to be independent from the sum of the parts (Kolinsky, 1973). For example, in Figure 3-1 the perception of a triangle is not simply the sum of the three objects but is independent from them. It takes 36 both the objects and the viewer’s previous experience to work together in perceiving the triangle.

Figure 3-1 A subjective contour (Dewy, 2011).

Similarly, music theorists take the underlying perception of rhythmic cycle and the surface rhythm as different layers despite their inseparability from each other.

Through one’s perception and cognition, “meter is inferred subjectively from the rhythmic surface, which is itself then interpreted with reference to this very metrical framework” (Clayton, 2000, p. 30). Johansson (2010) stated, “meter is in some way related to how we organize the unfolding of musical events, as opposed to what is being organized” (p. 44). With different attending modes and perceptual attitudes, people may hear different meters even though the surface rhythm presented to them remains the same. Once established, the perceptual framework also guides how one listens to the ensuing rhythm. As Clarke put it, meter is “a cognitive framework around which events are organized” (as cited in Clayton, 2000, p. 35). That is, when listening to a rhythmic flow, one’s cultural-experiential background defines the way one interprets the rhythms and lead to the perception of meter. However, instead of an underlying structure pre- 37 given by the surface rhythm, background framework is the perceptual and cognitive skeleton that requires additional information such as cultural knowledge, training, and visualization, which are not part of the actual music. Metrical understanding is neither the result of one-way influences nor the sum of individual musical figures, but the outcome that is largely shaped by the listener’s subjectivity nurtured in his or her previous experience.

Contemporary Western Meter Theories

Most of the contemporary Western metrical theories are based on a hierarchical model that uses pulse or beat as its referential unit. Cooper and Meyer (1960) recognized pulse as the “primary rhythmic level” (p. 2) and defined meter as “the measurement of the number of pulses between more or less regularly recurring accents” (p. 4). For them, accent is “an event that is marked for consciousness” (p. 8). Another approach to understanding meter was proposed by Lerdahl and Jackendoff (1981), who described metrical structure as “the regular, hierarchical pattern of beats to which the listener relates musical events” (p. 485). For them, meter is characterized by the “periodic alternation of strong and weak beats” (p. 487), namely the salience of pulse. Notions like this are also found in Yeston (1976) and London (2004), both of whom believed that for meter perception to take place, there needs to be a hierarchical structure that contains at least two pulse levels (Lerdahl & Jackendoff, 1981, 1983; London, 2004). Yeston (1976) further proposed that meter is the result of the interaction of two or more temporal levels, and one of them must be on the pulse level.

The models of Cooper and Meyer (1960) and Lerdahl and Jackendoff (1981,

1983) are alike in that they both organize similar elements into larger units on increasingly higher levels of the hierarchy. However, they apply different principles and choose different elements for grouping. First, Cooper and Meyer (1960) associated rhythmic groupings with prosody by recognizing and marking the relative prominence of these units. These organizations comprise either two or three components, with the mark

“-” representing a strong unit and “ᴗ” a weak one (e.g., labelling “strong-weak-weak” dactyl as “- ᴗ ᴗ” and “weak-strong” iamb “ᴗ - ”). Notably, the metrical units (feet) are defined by accentual contrast (as in the English language) and not durational contrast (as in classical languages and many non-Western cultures). After the “lower level” units are grouped according to the prosodic units (i.e., trochee, iamb, dactyl, anapaest, spondee, tribrach), the groups will again be grouped into a higher level based on the same principle. By repeating this process, the depth of the hierarchy increases. Figure 3-2 shows an example of Cooper and Meyer’s (1960) hierarchical analysis.

Figure 3-2. Example of Cooper and Meyer’s hierarchical analysis approach. Adapted from The rhythmic structure of music (p.23). by G. Cooper and L. B. Meyer, 1960. Chicago: University of Chicago Press. Copyright 1960 by University of Chicago Press. Reprinted with permission.

Lerdahl and Jackendoff (1981) also considered meter to be an accentual pattern— the periodic sequence of stressed and un-stressed abstract beats—but they conceptualized it differently. By arguing that beats are “points in time,” Lerdahl and Jackendoff (1981) conceived of them as abstract units and introduced a distinction between musical groupings and metrical structures, with the former composed of concrete musical elements such as motives and themes, and the latter based on abstract beats. Instead of considering groupings of beats, they claimed that “groups do not receive metrical accent; and beats do not possess any inherent grouping” (p. 494). Although there appear to be interactions between the beats and accents, Lerdahl and Jackendoff treated them separately in musical analysis. In the example of Figure 3-3, one can see that the slurs are used to mark the groups, whereas the dot notation is for metrical structures. Based on this distinction, Lerdahl and Jackendoff (1981) criticized Cooper and Meyer’s approach to assign accents to the entire group and treat beats as if they had durations.

This problem is more prominent in the higher levels, about which Lerdahl and

Jackendoff (1981) argued: “[it] is not that a given group is stronger or weaker than another group, but rather that the strongest beat in a given group is stronger or weaker than the strongest beat in another group” (p. 495). They also disagreed with Cooper and

Meyer on the use of prosodic units that place strong and weak beats together, which effectively mixes two levels in one and blurs the prominence of accents. For example, instead of analyzing a pattern of “strong-weak-weak” beats at two levels, they are considered at one single level, i.e. as the prosodic foot “dactyl (- ᴗ ᴗ).” Moreover, since the prosodic feet are all composed of either two or three units (one strong accent plus one

40 or two weak accents), they have limited Cooper and Meyer’s metrical analysis to groups that have precisely these organizations. Lastly, unlike Cooper and Meyer, who expanded the hierarchical structure to the extent of form, Lerdahl and Jackendoff (1981) recognized metrical structures to be local phenomenon. Other scholars such as Clarke (1999) have also made such a distinction, proposing that structural levels exceeding the capacity of direct perception should be considered as form, not to be confused with meter. Despite

Lerdahl and Jackendoff’s disagreement with Cooper and Meyer on the above approaches, one should keep in mind that they, like most theorists, consider accentual patterns—the periodic sequence of stressed and un-stressed abstract beats—as the core feature of meter.

Figure 3-3. Example of Lerdahl and Jackendoff’s analytic approach. Adapted from “On the theory of grouping and meter” by F. Lerdahl and R. Jackendoff, 1981, The Musical Quarterly, 67(4), p. 497. Copyright 1981 by Oxford University Press.

While agreeing with the hierarchical model in which “pulse” is the necessary, basic level, London (2004) proposed a different view from a psychological perspective and suggested that meter is a form of entrainment—“a synchronization of some aspect of

41 our biological activity with regularly recurring events” (p. 4). He defined meter as “a structured attending to time which allows the listener to have precise expectations as to when subsequent musical events are going to occur” (n.d.). London’s view that meter requires attention is compatible with results from experimental studies (e.g., Geiser et al.

2008), but so far there is hardly any evidence that meter perception is based on entrainment. Clearly, the perception of different quantitative meter in Greek, Latin,

Chinese, African, or Australian aboriginal poetry is based on the distinction of durational values and proportions, not different forms of entrainment. The relationship between meter, pulse, and entrainment requires further research, and the experiment in the current study is designed in such a way as to shed some new light on this question (see chapter

4).

London (2004), with a hierarchical model in mind, theorizes meter through gestalt principles by replacing Yeston’s (1976) claim that meter arises from the interaction of at least two periodic strata with the notion that it is “the integration of several strata into a single, coherent attentional framework” (p. 17). Meanwhile, he reiterats the distinction between meter and rhythm—the sound events in the foreground—although the former is frequently inferred from the latter through the listener’s interpretation. Agreeing with

Gjerdingen’s (1989) notion of meter being a mode of attending, London (n.d.) stated that

“Metre is a mode of attending, whereas rhythm is that to which we attend.” Other than rhythm, namely the temporal elements, he emphasizes that its interaction with other non- temporal components, such as harmony, timbre, and melody, would also make some pulses more or less salient than others in one’s perception.

Recent studies have challenged the relationship between pulse and meter. For instance, Fitch (2013) proposed that pulse perception entails the extraction of constant pulsations from a series of sound events, while meter perception involves grouping the strong and weak pulses into hierarchical structures. One is able to extract the pulses from a rhythmic stream that has no unambiguous metrical organizations and to infer the meter from a rhythmic sequence even though there are no isochronic pulses. Fitch described rhythms as “trees in time” –––even though he sees tree as spatial phenomena (graphs)–– and calls metrical trees “headed hierarchies.” From a tree, one infers meter by selecting a certain place in the stream as the “head node” (downbeat), around which the hierarchical structure is built and will be applied to the ensuing rhythms. Assimilating music to language, Fitch believed that the prominence of the head node or other secondary events of the hierarchical structure is not due to their serial locations in the rhythmic cycle (e.g., the first and the third beats of a measure), but rather to “[their] place[s] in the overall hierarchy of that measure” (Fitch, 2013, p. 3). As he put: Metrical induction involves

“conversion of an event stream or unaccented pulse stream to a hierarchically-grouped metrical tree structure; the height of each metrical stem indicates the relative prominence of that event” (p. 2). The ability to perceive head nodes, according to Fitch, seems to be universal and does not require special knowledge in Western musical theory.

Despite differences in detail, the meter theories presented above all share in their definition of meter in terms of hierarchical structures and processing. However, there is no evidence that hierarchical structures are used in auditory processing of meter. Indeed, they are not necessary: Because of auditory (echoic) memory, sequential processing is

43 sufficient to explain the functioning of metrical patterns in oral communications. The events of an auditory stream are not simultaneously available for processing as in their visual, notated versions. To detect periodicities, acoustic features are extracted and combined using auditory memory and the psychological present. The fact that auditory processing is foremost linear sequential raises questions about the origin of purported hierarchical structures. For Fitch, “a tree is defined as an acyclic, connected graph”

(2013, p.4); for Lerdahl and Jackendoff, the hierarchical relationships are analyzed on the basis of music notation (see Figure 3-3). These hierarchical structures have been revealed only in the analysis of visual representations of music and the question arises as to whether and to what extent these structures have any relevance for the perception of performed (not written) music. This question will be addressed in the experiment of the current study.

If the hierarchical structures associated with meter in Western musical theory turn out to be of no relevance for metrical perception in non-Western musics (e.g., Indian and

Middle-Eastern music), what then is the relationship between rhythm and meter when they listen to a rhythmic stream? What distinguishes rhythm from meter processing?

Electrophysiological research seems to support the idea that meter is processed distinctively from rhythm. Kuck et al. (2003) found in an EEG study that although meter and rhythm have largely overlapping networks, the locations of responses to them are somewhat distinct. In another EEG experiment, Geiser et al. (2008) demonstrated that meter processing requires particular attention and is more influenced by musical training than rhythm processing is. This suggests that, in contrast to rhythm and pulse processing,

44 meter processing can be influenced by certain types of learned behavior, such as by cultural factors. Therefore, the following section examines the question of cultural influences on temporal perception and cognition, with particular emphasis on the metrical aspect.

Cultural Influences on Metrical Understanding

This section presents the problems of applying Western meter theories in non-

Western context. The Western metrical concept has been developed through a distinct path that has greatly shaped Western temporal perception, but is not found in cultures unfamiliar with it.

Problems of Applying Western Meter Theories in Non-Western Contexts

There has been increasing research supporting the influence of enculturation on temporal processing. Cultural factors or experience in a particular environment may shape one’s understanding of time in various aspects. For example, research shows that the languages one speaks can influence the duration-pitch interaction because individual’s listening experience (e.g., Lehnert-Houillier, 2007; Gussenhoven & Zhou,

2013; Šimko et al., 2015), the choice of listening strategies may lead to distinct neural network and activities (Grahn & McAuley, 2009; Portugal et al., 2011), and previous musical experience may affect the processing of temporal information (Aleman et al.,

2000; Palmer & Krumhansl, 1990). In a study based on Bolivian songs sung in Quechua and Aymara languages, Stobart and Cross (2000) found that people of different cultures may perceive downbeat and upbeat in distinct ways: what was perceived as anacrustic

(beginning with offbeat) by the Western European listeners was perceived as downbeat 45 by the Bolivian listeners. The authors speculated that this phenomenon is related to

Quechua’s prosodic structure. In this language, the second syllable of words, although being a secondary stress, is the only fixed location for accents, whereas the softer, first syllable serves as a referential starting point. This might have made Quechua speakers take what Western listeners perceive as a “pick-up to a downbeat” as the beginning

(downbeat) of melody. Such interpretation is further supported by the musicians’ movements, in that their footfalls (marking downbeats) and the charango1 players’ downstrokes both occur at the first sound events of the melodies. Likewise, in discussing the construction of long, complex meters with irregular subdivisions, such as those commonly found in Middle-Eastern, Balkan, and Indian music, Clayton (2000) suggested that they are frequently associated with the prosody of the indigenous languages (e.g., length, pitch, and stress of syllables) or dance movements (e.g., heavy vs. light steps).

Indeed, it makes sense in an oral culture that people tend to perceive musical features in relation to things more concrete and tangible in real life. Through language or bodily movements (see discussion on sensory-motor theory in chapter 2), music ability and memorization are enhanced and reinforced. Distinct environments therefore nurture distinct listening strategies.

Among many temporal aspects, meter seems to involve more complex processing and is more heavily influenced by cultural factors (Geiser et al., 2008). Clayton (2000) asserted that “Metre . . . is clearly not a universal concept, nor is it a phenomenon observable in all world musics” (p. 41). While it may not be impossible to develop a

1 Charango is a small guitar-shaped instrument commonly found in the Andean region. 46 cross-cultural concept of meter, such a concept should not and cannot be derived from that of modern Western music. The reason for this is that, as shown in a host of comparative and ethnographic studies on both language and music, the modern Western stress-based meter is an idiosyncratic form of metrical organization not found in other cultures. Even in the European context, it is a relatively recent phenomenon: Greek and

Latin meters were, until the end of the medieval period, defined by contrastive durations, not by stress pattern. In classical Chinese poetry, meter was governed by specific numbers of syllable per group and by the contrast of level and deflected speech tones, which also implies a durational contrast (Watson, 1971). The arrangement of these speech tone contrasts was initially free and only became fixed in later forms. In the poetry of Australia’s aboriginal language groups, in which syllable length is a contrastive language feature, meter is organized in terms of groups of short/long contrasts and specific numbers of syllables. Notably, the length contrasts, similar to classical Chinese poetry, are not assigned fixed proportional values (Will, 2004). On the other hand, stress, although not unknown in either culture, is not used as an organizing principle for meter in

Chinese or Aboriginal Australian poetry.

Problems associated with the cross-cultural application of a Western-oriented metrical concept have been repeatedly presented in contemporary literature. As an ethnomusicologist who focuses on Central African music, Arom (1991) criticized the application of stress-based meter models to Central African polyrhythms as ill-suited. He argued that although Central African rhythm is carried out in a circular, periodic manner, the patterns usually repeat and interlock around only one pulse level without any

47 implication of strong–weak hierarchy as implied by the Western meter concept. In fact, even in cultures that have solid metrical theories (e.g., classical Indian music), people may not listen to rhythms in a hierarchical way, but by grouping similar components together according to gestalt principles (Clayton, 2000). Clayton also found Lerdahl and

Jackendoff’s (1983) metrical approach, while widely accepted by Western music theorists, to be inapplicable in many non-Western complex meters comprising subdivisions of unequal length (e.g., Jhaptāl, a 10-beat Indian pattern featuring 2+3+2+3 subdivisions). He pointed out that because Lerdahl and Jackendoff considered pulse as time points separated by equal intervals, rhythmic patterns with irregular subdivisions will not fit this framework. When played in a medium tempo, for example, such patterns of “non-isochronous pulses”2 would not properly serve as the referential level of metrical organization. Going further than Clayton, Magill and Pressing (1997) even suggested that in music like West African drumming, the perception and cognition of meter may be built upon irregular timeline instead of regular pulse.

In my opinion, these issues are in fact caused by conflating the concepts of pulse, beat (see the “Pulse-Beat Distinction” section in chapter 2), and grouping. The above scholars have failed to distinguish between these concepts, namely, that 1) pulse is a

(quasi-)isochronous response to external stimuli, 2) beats are abstract, cognitive units that may be grouped together by a listener in the actual listening experience, and 3) grouping can be done on the basis of several sound features—accents being merely one possibility—and, as such, does not create a hierarchical structure. Clayton’s notion of

2 Clayton uses pulse and beat as interchangeable terms. 48

“non-isochronous pulses” and Magill and Pressing’s “irregular timeline” can probably be better understood as grouping phenomena. That would help clarify the confusion and bring cross-cultural meter discussions to a common ground. However, the above arguments by these scholars have shown exactly the problems that surface when one attempts to apply Western metrical models to non-Western rhythms.

Western Musical Meter as a Distinct Concept

Literary tradition. As mentioned in chapter one, one of the fundamental issues in applying Western theories to non-Western rhythms is that the former are predominantly nurtured in a literary tradition, while most of the latter are not. The literary approaches that attempt to “visualize time” may result in significantly different metrical understanding. First, without transcribing sound into a visual–spatial domain, acoustic information can be processed only sequentially at the psychological present. Since the psychological present is limited to about two to three seconds (Michon, 1978; Pöppel,

2004), it is unlikely for humans to perceive a deep hierarchy of expanded length in actual listening experiences. Without written music, none of the above-described concepts of

Western meter could exist. Even for those who are knowledgeable of Western musical theories, unfortunately, such knowledge does not enable them to “perceive” musical rhythm hierarchically, but only to hear such structure through the acquired and learned concepts (e.g., proportional duration values, mental representations, abstract analyses) that allow the listeners to anticipate and interpret the incoming linear streams of auditory events. Secondly, the visual–spatial representation presented in Western notation plays no role in orally transmitted musics. In most cultures, people tend to process musical time in 49 a manner that is closer to everyday life, such as relating it to language or bodily movements instead of treating it as absolute proportional values as Western music theories do. Although there are indeed metrical concepts in many non-Western and oral cultures, the meanings behind them may be very different from that in Western music.

Meter originated as a type of memory aid for spoken language (Rubin, 1995) rather than a measurement system in the Western sense. In order to improve the memory of oral performers, that is, to overcome the limits of auditory memory and psychological present, it restructures the temporal sequence of speech by placing together certain numbers of syllables of contrastive prosodic features. These features, such as the tones or lengths of syllables, are contrastive in that they are comparatively longer/shorter or higher/lower than the adjacent syllables. That is, the prosodic relationship between syllables is presented in a relative, not absolute, manner. These mnemonic features are largely found in the temporal organizations of orally transmitted music.

Meanwhile, one should be aware that, despite the absolute proportional values, modern Western notation also originated from an oral tradition and that the metrical organizations of Western music were derived from formerly prosodic relationships as well. Given the literary tradition of the Western world and miscellaneous conditions that have shaped Western music history, the notation system gradually evolved from presenting flexible durational relationships to recording fixed proportional values. Below

I will turn to a brief review of such development.

Historical development of Western notation. During the 12th and 13th centuries, the composers of the Notre Dame School developed a modal notation,

50 gradually replacing the even and unmeasured rhythm of early polyphony and plainchant with patterns derived from the metric feet of classical poetry. As already mentioned, the metrical organization in classical Greek and Latin was based on contrasts of syllable length, not on accentual patterns. The introduction of these metrical principles was not only a major leap toward mensural notation (Hoppin, 1978, p. 221), but also an adaptation of metrical principles of vocal performances into the domain of instrumental music. However, with the rise of polyphony, the fact that contrasting lengths of metrical feet did not imply defined durational proportions between long and short values caused difficulties in the coordination and regulation of multiple voices. Increased attempts at specifying the durational relationships between notational symbols led to the development of mensural notation by the 13th century. It used note shapes in a systematic manner to denote their durational values by defining numerical proportions between notes. In practice, however, notes could take on various durations and could be subdivided in several ways depending on context and specification by the rhythmic modes (DeFord, 2015).

For performance purposes, the proportional values of mensural notes needed to be given a unit of real time as a common reference for all performers. This was achieved by what was most commonly called mensura or morula (in the sense of beat, for mensuration also had other meanings) in the 15th century and tactus in the 16th century.

At that time, tactus meant touching something with hand, foot, or a baton. It also referred to a visible beat, such as the motion of the hand in the air, with tempus perfectus indicated with three “finger” touches (or beats) and tempus imperfectus with two. As

Ornithoparchus (1517) wrote in Musicae activae micrologus on the interpretation of the mensural system, the “tactus [was] a successive motion in song that direct[ed] measure in an equal manner; or, it [was] the motus3, signaled by the hand of the chief singer, which direct[ed] the measure of song in accordance with the [mensuration] signs” (cited in

Grant, 2014, p. 31; footnote added). Using mensuration signs (O, C, ʘ, Ͼ, which were first introduced in the 14th century) in combination with numbers 2 and 3,

Ornithoparchus’ Musicae activae micrologus explained the hierarchies of proportional values between adjacent levels, with the semibreve being a reference that organized the system (Grant, 2014). However, tactus could be applied at different mensural levels such as breves, semibreves, or minims.

Although tactus was not unambiguously defined in mensural notation (DeFord,

2015), the underlying idea was that notes could be given specific durations by comparing and/or synchronizing them to continuous periodic actions like hand gestures or foot movements. Reflecting a feature of periodic movements, tactus was considered to contain subcomponents, namely up and down strokes, with equal or unequal proportions.

Relating these proportions to prosodic feet in Le istitutioni harmoniche, Zarlino (1558)

“account[ed] for some of the rhythmic patterns that each meter [could] measure,” with short syllables having half of the values of long syllables, and they were embodied in the raising and lowering of the hand. In a later text, Synopsis musicae, Lippius (1612) also related the two equal or unequal parts of tactus with prosody, and more explicitly asserted that “all sound is quantity” (cited in Grant, 2014, p. 34) measured through motions. On

3 Motus: motion; change.

52 the other hand, there was initially no visual information indicating distinct groups of tactus. That is, there seemed to have been no special marker or sign to indicate, for example, the start of perfect breves when the tactus was semibreves, even though performers were likely aware of such groups as a part of the mensural structure.

The modern concept of meter evolved from the tactus of mensural notation, a development reflected in the German term for meter, Takt (i.e., tactus), with the semibreve being equivalent to the duration of a measure or meter. By the late 17th century, the two formerly corresponding concepts, measure (mesure) and beat (tactus, temps, or battement) started to have different meanings. As Loulié (1696) put in Éléments ou principles de musique: “The measure is a number of equal beats [battements] that serve to regulate the duration of sounds” (cited in Grant, 2014, p.37). Furthermore, since it was the touches—the end points of down strokes—that were the reference for determining durations, he used the term temps distinctively from battement to indicate durations. The ideas of mesure and temps “create[d] the possibility for an abstracted mesure hierarchically divided into the temps that mark the duration from one beat to the next;” “the idea of the measure as an entity independent from the beat is latent in the arrangement of terms employed” (Grant, 2014, p. 38). Gradually, the notation representing divisions of tactus motions had given way to a new concept in which the divisions became (abstract) markers of the time span of a measure (Maier, 1984;

Dahlhaus, 1961).

The main factors that drove this rather complex transformation went back to developments to increase the range of temporal expressions in the mensural notation

53 system. Within a mensural composition, a new meter could be indicated in two ways— either by using numeric proportions or inserting corresponding mensuration signs.

Numeric proportions had the effect of changing the duration of notes with regard to the corresponding duration of the preceding meter. For example, a 3:1 (or short “3”) indicated that all notes will now be reduced to one-third of their former value; a 2:1 indicated halving of durations, and 3:2 indicated that three notes had the duration of two previous ones, and so forth. Another practice was the use of diminution signs (ɸ, ₵) to indicate that the tactus shifted up one level (e.g., from semibreve to breve), which caused the same note values to have half the value of their previous duration. M. Bent (1996) reported that the perfect diminution sign ɸ was first a multipurpose sign, often used non- mensurally as an insertion point or place-finder. Initially, both the sign for tempus perfectum prolation minor (Ο) and the same with a diminution stroke (ɸ) had meant the same mensuration, except when a proportional use was intended, as was the case when they occurred together with other mensuration signs in the other voices.

In the 16th century, proportions and diminutions obtained a new, non-mensural meaning: They began to indicate tempo changes. For example, if the ₵ sign shifted the tactus from the semibreve to the breve, the new semibreve was twice as “fast” as the old one, and the proportion signs became reinterpreted as fractions. Meanwhile, the concept of tactus started to change from a fixed to a flexible temporal unit: Diminutions and proportions came to be used to indicate change in the speed of the tactus, and the change was less than that indicated by associated proportions. This change was found in cases where the diminution sign appeared on its own, namely, not simultaneously with other mensuration 54 signs. Among other complications, this led to a situation where diminution signs could be interpreted in two ways, indicating either a ratio change of tempo (e.g., twice as fast) or a change independent of the ratios between note values in order to increase the temporal expressivity of the music (for a discussion of the different interpretation of the diminution signs and the question of whether in the latter case the new tempo has a rational or irrational relationship to the previous one, see Dahlhaus, 1961; Brainard, 1991).

In the current context, it is significant that the 16th century brought about a reinterpretation of mensuration signs in a non-mensural way, and the emergence of a temporally changeable tactus—both suggesting the emergence of a concept of expressive tempo different from what mensural notation had offered. In the 17th century, the tactus became somewhat slower, and performances were regulated by subdivisions of the tactus-measure, such as beats or groups of beats. In addition, tempo words often helped to clarify the “temporal” meaning of mensural signs.

The developments outlined here are reflected in the accompanying changes in the notation: Bar lines were eventually used as markers of rhythm units, and musical sequences were divided into a number of equal measures with a fixed location of accents.

The earliest markers resembling bar lines were found in keyboard and vihuela music in the 15th and 16th centuries. They did not reflect a regular meter at all but were only section divisions, or in some cases marked off every beat. They were subsequently introduced into ensemble music to aid alignment of parts and had nothing to do with the

“metrical structure” of the music. They were generally absent in music presented in partbooks, but became more frequent with the increasing number of score presentations

55 in the late 16th century. Not until the mid-17th century were bar lines used in the modern style, with every measure being the same length, and they began to be associated with time signatures. For M. Praetorius (1619), in the first half of 17th century, the tactus lines still delineated mensural units and served only as a visual aid to mark divisions.

However, in the writings of W. C. Printz in the second half of the 17th century

(Heckmann, 1953), the concept of measure or bar had been transformed from mensural proportions to fractions in which the denominator indicated the base units and the numerator the number of base units per measure/bar/takt. Furthermore, Printz made quantitas temporalis a central term in his music theory and divided it into quantitas extrinseca and intrinseca, with the former referring to the external, physical duration of sound events, namely the “true value,” whereas the latter referred to the apparent length, their “subjective value.” Printz then used this distinction to explain note groupings within a measure, thereby formulating the core idea of a new concept of metrical accents

(Heckmann, 1953). Though accentuation had not been a constituent part of mensural notation, it was an established practice since the 13th century, in which harmonically important time units, at least at the start of mensural units, were carriers of accents (or vice versa, that the accents led to harmonic importance; see, e.g., Boone, 2000).

However, Printz’s writings express the new principle of regular alternation of accented and non-accented units within a measure that forms the basis of the modern Western concept of meter. Accents have now been turned into an inner quality (quantitas intrinseca) of notes, a phenomenon of subjective perception and interpretation, in which the mere position of a note within a measure imparts accentuation.

The development of Western notation of temporal organization began with attempts to visualize the durational contrast of syllables, an organizational principle of many oral traditions. However, with the introduction of tactus (a motional aid to bring inter-personal time to a common ground) and later the use of barlines, meter has gradually evolved from flexible, relative durations to fixed proportional values assigned with relatively stronger or softer accents. Having departed so far from the initial prosodic principles, such a notation system makes Western meter “act as a framework for the actual (melodic) rhythms that may or may not be congruent with the underlying meter”

(Will, in press-a). Given that they are so distinct from the meter concepts of other cultures, Western meter and notation have shaped how Westerners process musical time and enabled it to be analyzed in a way only possible through visual-spatial representation.

Culturally Shaped Perception of Rhythm and Meter

As discussed, the development of the Western notational system, with its small integer-ratio durational values, has changed the way we listen to and think about music.

A large body of research has shown that Western listeners have a preference for simple integer ratios and tend to “straighten” the non-integers into simple integer ratios (Grahn

& Brett, 2007). In a listening experiment, Clarke (1987) presented the participants with a series of 3-tone stimuli with various interval ratios between 1:1 and 1:2. In spite of the varying ratios, participants showed a pronounced preference for categorical perception of

1:1 or 1:2. Likewise, in Stobart and Cross’ (2000) study on Bolivian songs, the Western listeners tended to perceive the complex ratios as simple integer ones for their “culturally incorrect” anacrustic interpretation. In a tapping experiment, Snyder et al. (2006) also

57 discovered that participants raised in North America achieved higher accuracy in reproducing integer than non-integer rhythms and had difficulties producing complex metrical patterns (p. 135).

Will’s (2011) study on Australian aboriginal music has challenged previous claims that categorical small integer-ratio perception of durations is universal by showing that Aboriginal Australians showed no preference for simple integer rhythms in real-life performances. Instead, the comparison of rhythm interval production from various areas showed that the preferred interval ratios differed from region to region. The geographic locations investigated predominantly preferred non-integer (rather than simple integer) ratios (Will, 2004, 2011). This is clear evidence that Westerners’ preference for categorical, small integer ratios is culturally distinct, and this is likely a cognitive habit cultivated in and based on the Western literary tradition (i.e., a notation system based on small integer-ratios).

Recent research has investigated more specifically the cultural differences in metrical understanding. The results support the idea that human perception and cognition of meter are shaped greatly by cultural factors and that such cultural differences are particularly prominent in response to complex meters. For example, Hannon et al. (2012) found that culture-specific listening experience and acquired musical knowledge are crucial to the perception of complex rhythms. Kalender et al. (2012) proposed that exposure to diverse musical cultures will enhance one’s ability to perceive complex meters. In an experiment, they recruited two groups of participants to listen to unfamiliar rhythmic patterns of complex meters—one familiar with only Western music (i.e., simple

58 meter) and the other group having experience of musics from two or more cultures. The result showed that subjects of the latter group are more responsive to novel complex meters and therefore more capable of understanding foreign rhythmic patterns. Hannon and Trehub (2005a) also found similar results in an experiment that tested participants’ ability to detect metrical variants of simple and complex meters. The result showed that while both the North American and native Bulgarian/Macedonian groups were able to detect the variants of simple meter, only the latter did so with complex meters.

Interestingly, despite such differences, which have been consistently found in adults, reports have shown that human infants initially have generic perceptual abilities for simple and complex meters. In an experiment using the same stimuli as in the study involving American, Bulgarian, and Macedonian subjects, Hannon & Trehub (2005a) found that infants of six to seven months old are able to detect variants in both simple and complex meters with equal ease. However, Soley and Hannon (2010) reported that infants younger than nine months old, although capable of discriminating among variants in both metrical conditions, already show perceptual preferences for rhythms of their own culture. As for infants of twelve months old, their responses display cultural preferences similar to those found in adults. Although brief exposure to foreign music enables them to perceive rhythmic (metrical) distinctions in foreign musical contexts, such ability is not found in adults (Hannon & Trehub, 2005b). These reports have confirmed that by growing up in a particular culture—that is, by being exposed to certain music types, metrical idioms, and languages—one interacts with the environment both consciously and subconsciously and develops preferences for features present in the environment

59 while at the same time losing sensibilities for features one is not frequently exposed to and that are not relevant for one’s interactions with the world. Such enculturation begins in an early stage of life, and infancy seems to be a crucial period for the formation of metrical perception and cognition, because the human mind is highly flexible in adapting to any rhythmic organizations during this time.

Summary

Contemporary Western meter theories have been well-developed in the past decades. From Cooper and Meyer’s (1960) prosodic principles and Lerdahl and

Jackendoff’s “points in time” (1981), to London’s (2004) entrainment approach and

Fitchs’s “head node” and tree in time (2013), all these metrical concepts have been built on a hierarchical model in a more or less similar way. However, imposing these models on non-Western musics has often caused problems because meter in the Western sense is not a universal concept. The Western metrical concept has developed in a literary tradition, which, through music notation, attempts to make a precise visual–spatial representation of time based on proportional values of small integers. The hierarchical metrical structure results from analyses of visuo-spatial representations of music (i.e., notations, transcriptions), whereas hearing is based on sequential processing of acoustic information. In oral cultures, to overcome these limits of auditory memory and psychological present, music is frequently associated with activities such as languages and bodily movements that are available in everyday life. As such, their metrical concepts are mostly built upon relative relationships, rather than defined, fixed proportions of durational values. 60

Revisiting meter in the history of Western classical music, one will find that its development is distinct from that of other cultures. Using a system that divides time into equidistant segments (bars), each containing fixed accentual patterns and to be filled with fixed proportional durations, music notation has largely shaped the metrical preference of Westerners and how they process acoustic information, leading to perception and cognition of meter (especially complex meters) different from that of other cultures. Such metrical enculturation of metrical perception starts in an early age.

Chapter 4. Design of a Cross-Cultural Experiment on Pulse and Complex-Meter

Perception and Cognition

Recent research has challenged the hierarchical meter theories developed in

Western art music and proposed that humans process meter and pulse in distinct ways, with the former influenced more heavily by cultural contexts. The present research explored the bodily responses to pulse and meter to ascertain whether there are behavioral indicators for pulse and meter perception to be processed distinctively, and, if so, how they are related to each other and whether there are cultural factors that influence these differences. The experiment included a short questionnaire to gather qualitative data. This chapter describes the rationale and design of the study, and the next chapter will discuss the results.

Cultural Factors

Today’s research on music perception and cognition is predominantly Western- oriented. For a long time it was common practice in this field to either exclude cultural considerations altogether or simply ignore them in the experimental design. In most studies, both the researchers and the recruited participants were restrictively of Western culture or Western musical background, in which music is different than in other cultures in the world (Will & Turow, 2011). Although in the past few decades, there has indeed 62 been some cross-cultural research in music cognition, most of it concerns the harmonic and tonal aspects of music (Will, in press-a); only a few studies have been interested in the temporal domain. The dearth of research on the temporal aspects of cross-cultural music cognition is striking, because there is increasing evidence that how one processes time is highly influenced by cultural factors. Since human beings have no specific organs to sense time, time is a mental construct and as such it is shaped both culturally and biologically (Will, in press-b).

Temporal perception is a cognitive constructive process, with input from various senses and multiple channels of information, and as such it is not independent of sociocultural factors, whose influence has been identified in areas from duration discrimination

(Jeon & Fricke, 1997), language-specific duration–pitch interaction effects (Lehnert-

Houillier, 2007; Šimko et al., 2015), micro-timing in rhythm production (Iyer, 2002;

Polak & London, 2014), to entrainment (Will et al., 2015). In addition to hearing, people perceive temporal features also through visual and tactile inputs, and they coordinate with the motor system (see chapter 2), which in fact serves as a crucial underlying mechanism for temporal processing. It is through such complex detection of similar temporal structures in the environment and their coordination with one’s experience that certain culturally specific customs of temporal processing are established. Metrical understanding is one of them. Rather than a direct percept (Clayton, 2000), it is shaped by one’s previous musical experience and therefore socio-culturally specific.

If cultural influences have significant effects on temporal perception in music, what criteria can we use to operationalize the influence of culture in empirical research?

What criteria can meaningfully define cultural groups? If culture involves one’s experience and finds its expression in reciprocal interactions between body, mind, and environment, it would challenge the traditional view that culture is “an observable, empirical reality, an irreducible entity formed by an enumerable set of components, with clearly identifiable boundaries and stability across time” (Will, in press-a). For example, to categorize cultural groups by one’s nationality, birthplace, or long-time residency—as it is unfortunately often done—is clearly inadequate, for as time unfolds, enculturation constantly occurs in all aspects of life on miscellaneous levels. Criteria like nationality or birthplace assume a uniformity of cultural factors in a regional or local population, country or municipality, that is rarely warranted (Will, in press). In contrast, “culture” is constantly modified over time, having ambiguous and flexible boundaries (Frijda &

Jahoda, 1966) and can never be fully categorized by a complete inventory of components.

Therefore, to make it applicable in empirical inquiries, culture needs to be re- conceptualized. When defining cultural groups, researchers need to keep in mind the mutable nature of culture and then break it down into more embodied and specific factors that represent aspects of one’s socially transmitted knowledge, values, and behaviors

(Frijda & Jahoda, 1966; Tomasello, 1999; Breugelmans, 2011). For example, many cross-cultural studies use factors like “being a musician” (i.e., having formal and/or continuous training in a type of music for a certain period of time; having practiced or performed regularly) and/or “speaking (a) certain language(s)” as indicators of (cultural) group membership. Nevertheless, in cross-cultural studies, special care has to be taken that the selected factors, or their criteria, do indeed designate equivalent behavior,

64 otherwise a comparison across cultural groups will be problematic (Will, in press-a). For example, “being a musician” in Western classical music suggests the ability to read music, whereas in jazz music, “musicians” do not necessarily read music but most likely possess great improvisatory skills. In such a case, simply “be a musician” cannot specify and ensure that the recruited participants have equivalent musical abilities and experience.

In the current study, cultural groups are going to be distinguished by their listening experience according to the criterion of having grown up in a musical environment with exposure to and experience with specific types of music (or not). The listening experience is further specified through additional information about the musical environment, which is obtained from a questionnaire each participant completed at the end of the experiment (see “Participant Recruitment” section below).

Rationale and Hypotheses

As pointed out in the previous chapter, the Western hierarchical meter theories have been challenged by the notion that pulse and meter are processed distinctively, with the latter more influenced by cultural factors. The abstract concept of meter in the

Western tradition has shaped people’s rhythmic-metrical processing differently than in cultures where music is transmitted in other fashions (e.g., oral transmission, tablature notation). For example, experienced Indian music listeners may process the rhythmic cycles according to Gestalt principles rather than in a “metrical way” (Clayton, 2000; see chapter 3).

The purpose of the current study is to bring cultural factors into the discussion and explore the relationship between pulse, grouping, and metrical structure, in order to 65 determine whether this relationship is influenced by one’s previous experience in a particular musical culture. It also inquires, if pulse and meter are processed differently, as suggested in chapter 3, how the differences are reflected in behavioral responses.

Among non-Western cultures, both Indian classical music and traditional Middle-

Eastern music are known for their complex metrical structures, which have long rhythmic cycles and consist of additive subunits. Among the Middle-Eastern and Indian rhythmic patterns that comprise the same beat numbers per cycle, some are composed of the same subdivision structure, while some are not. For example, the Indian Rupak and the Arab

Nawakht are both 7-beat patterns composed of 3+2+2 subdivisions. As for the Indian

Jhaptal and the Middle-Eastern Samai Thaqil, both of which have 10 beats in the pattern, the former is composed of 2+3+2+3 subdivisions, and the latter, 3+2+2+3, as illustrated in Table 4.1. As specified in the discussions on previous experience influencing metrical processing (see chapter 3, “Culturally Shaped Perception of Rhythm and Meter”), when listeners from two cultures listen to each other’s patterns that comprise the same beat number but different subdivisions, they might be guided by their previous experience and interpret the patterns in a “culturally incorrect” way—interpreting the sequence of subunits according to their own cultural experience rather than that cultural practice from which the pattern originates—while still entrain smoothly to the rhythm. Using Fitch’s

(2013) notion of “head node,” the two cultures perceive the same acoustic pattern but place the head nodes differently (see chapter 3).

Table 4-1. Examples of Indian and Middle-Eastern subdivisions of rhythmic patterns

Pattern Type Culture Pattern Number Subdivision

Rupak Indian 7 3+2+2

Nawakht Middle-Eastern 7 3+2+2

Jhaptal Indian 10 2+3+2+3

Samai Thaqil Middle-Eastern 10 3+2+2+3

To determine if cultural differences influence metrical and pulse perception and

synchronization differently, this study compared the pulse and meter perception and

cognition of people who have the following listening and/or performing experience:

1) Middle-Eastern music (metrically and culturally familiar group),

2) Indian music (metrically familiar but culturally unfamiliar group), or

3) no experience with music of complex meters (unfamiliar group).

By presenting all three cultural groups with a set of Turkish rhythmic patterns that

represent the Middle-Eastern metrical structures, I hypothesized that there would be

significant cultural differences in the response performance to the meter task, but not to

the pulse task. Furthermore, I hypothesized that the three groups would respond to the

metrical structures with different levels of difficulties. That is, the closer the listening

experience of a group is to that of the group to which the rhythmic patterns belong, the

better their performance was expected to be. Differences may be manifested by how

successful the three groups perform the required tasks, as well as the uniformity with

which they synchronize to the rhythmic patterns. In other words, I hypothesized that the

Middle-Eastern group would exhibit the highest rate of successful performance; the

Indian group, while unfamiliar with the Middle-Eastern rhythms, would perceive the complex meters with ease but likely in a “non-Middle-Eastern way,” That is, not necessarily indicating the culturally correct metrical organizations; the “unfamiliar group,” namely the control group, would struggle the most in responding to these complex meters. If the above hypothesis proved true, it would cohere with Kalender et al.’s (2012) finding that experiences in complex meter enhance one’s ability to synchronize with foreign complex meters, yet I further analyzed the consistency with and the distinction between groups using the data collected in the questionnaire and the verbal feedback. On the other hand, from the subjects’ bodily responses (tapping) to the stimuli,

I also inquired whether there is entrainment phenomenon in both the pulse and the meter tasks, as London (2004) proposed. If there is (or is not) entrainment in the metrical responses, how is the phenomenon of synchronization different from that in the pulse task?

In order to test whether shifts in reference levels occur in both the pulse task and the meter task, all rhythmic patterns were presented in two temporal conditions, one around the mean preferred tempo (120 beat per minute; 2 Hz) and the other at double that tempo. The human body has a strong 2Hz resonance for repetitive movements

(MacDougall & Moore, 2005), therefore there is a strong preference for musical pulse perception at around 120 bpm (van Noorden & Moelants, 1999; Moelants, 2002).

Although the preferred tempo varies from person to person, the differences are limited. I expected that with the doubled tempi, the participants would switch their response

68 reference to a “higher level,” representing their pulse perception in reduced motor responses at a simple integer ratio (e.g., 2:1). For instance, if one taps the perceived pulse of a rhythmic stream at the rate of 120 bpm, it is highly possible that when the tempo of the rhythmic stream is doubled, he or she would “move up to a higher referential level”

(every other beat) and still tap at the same rate (120 bpm). This is because 240 bpm is out of the temporal range that one may comfortably entrain to. One can imagine this with a fast-tempo march in which a conductor needs to count and move by bars instead of by beats.

Therefore, the current study hypothesized that if meter is a hierarchical structure based on the pulse level, it would be reflected in the differences in the behavioral responses to the two tempo versions of the rhythmic patterns. With the switched

“reference” (pulse level), a proportional correlation between meter and pulse responses and between the two tempi should be found. It was of particular interest to test how the participants would respond to pulse and meter of complex metrical structures with odd- number beats (e.g., 7- and 9-beat structures) when the tempo is doubled. When the tempo is doubled and the listener entrains to a “higher level pulse” by tapping on every other beat instead of every beat, he or she would encounter a shift at the end/beginning of every rhythmic cycle regarding which beats to tap on. For example, to respond to the second level pulse of a fast 7-beat pattern, one would tap alternatively on beats 1, 3, 5, 7 or 2, 4,

6, 8. If this were the response to fast-tempo, odd-beat patterns in the pulse task, how then would one respond in the meter task? Would the pulse–meter relationship between the

69 two temporal conditions be proportional or not (suggesting their correlation or dissociation)?

Method

To test cross-culturally the participants’ pulse and meter perception and cognition of rhythm that has complex metrical structures, ten Turkish rhythmic patterns representing Middle-Eastern metrical structures were created to be the experiment stimuli. Among the ten patterns, seven were complex meters (7-beat, 9-beat, and 10- beat); the other three were simple meters (3-beat and 4-beat). The experiment sessions contained two parts, in which the participants were asked to tap to the acoustic stimuli.

The first part tested the participants’ response to pulse (P), and the second part tested their tapping responses to the metrical or grouping structure of the patterns (M). In both the pulse and the meter tests, all ten rhythmic patterns were played in two temporal conditions (see “Rationale” above about mean preferred tempo for testing two tempi), one in the range of the mean preferred tempo (P) of humans’ pulse perception and the other in a faster range where the pace is doubled (F). Thus, a total of forty stimuli were presented to each participant.

Stimuli

The Middle-Eastern rhythmic patterns presented to the experiment subjects were extracted from the audio examples on the webpage of Maqam World (2007), which were played on Middle-Eastern instruments darbuka and riq, a single-headed goblet drum and/or a tambourine. On these instruments, the metrical structures are indicated by the distinctive sounds made through particular strokes. From every metrical type selected for 70 this research (e.g., Aqsaq, Dawr Hindi, Nawakht, etc.), one metrical cycle was selected and copied from the original recordings for further edition. The temporal manipulation was made by recreating the patterns in a different tempo. From the original patterns, the sound waves of different types of strokes (i.e., “Dum,” “Tak,” and the other softer embellishments) were recognized and extracted separately for later rearrangement. The individual sound events were then pasted together according to the desired arrangement and tempi. If the original patterns already fell in the desired temporal range, no edition was needed. In the experiment, the cycle was looped and presented to the participants as repetitive cycles. Figure 4-1 shows the sound wave example of Dawr Hindi, a 7-beat pattern with the 3+2+2 subdivisions that feature the pattern “D T T D tt T tt,” with D as the downbeat “Dum,” T as the stronger up-stroke “Tak,” and the lowercase t as the softer improvisatory strokes. More specific information about the rhythmic patterns used may be found in the table of Appendix-A.

Figure 4-1. Sound wave example of Dawr Hindi (7-beat pattern with the 3+2+2 subdivisions) in the doubled-tempo condition.

In both the pulse and meter tests, all ten rhythmic patterns were played in two temporal conditions, one in the range of the mean preferred tempo (P) of humans’ pulse perception (around 500 ms, 120 bpm) and the other in a faster range, where the pace is doubled (F). The P tempi in this experiment ranged from 100 to 140 bpm; the F tempi, therefore, from 200 to 280 bpm. These temporal variations within the P and F stimuli were set intentionally so that the participants would not become used to one specific tempo regardless of which patterns were played to them. The 1:2 temporal difference between the P and the F variants was a variable to manipulate the participants’ choice of reference level when extracting a pulse or grouping. As mentioned, the two temporal conditions were introduced to test whether tempo changes lead to changes in the selection of referent levels in both the pulse and the meter tasks.

As the patterns were selected from real performance recordings, the inter-onset intervals (IOIs) within each patterns are not set to be exactly isochronic. The IOI variability (see SD columns in Table 4-2) was retained in order to keep the stimuli as close as possible to the original performed versions. Table 4-2 lists the mean IOIs and the standard deviations (SDs) of each pattern in both temporal conditions. The overall means for each group are also included.

Table 4-2. Individual mean inter-onset intervals (IOIs), standard deviations (SDs), and overall mean IOIs of all stimuli

Pattern Unit(s) / IOI (P) SD (P) IOI (F) SD (F) Number: Cycle (ms) (ms) (ms) (ms) Pattern Type 1, 2: Samai Taer 3 460 12 242 14 3, 4: (Tt T T) 3 502 13 258 8 5, 6: (D t T t) 4 457 12 228 11 7, 8: Dawr Hindi 7 492 16 244 12 9, 10: Nawakht 7 571 17 287 13 11, 12: Aqsaq 9 447 22 220 16 13, 14: Awnak 9 544 25 282 20 Turki 15, 16: Karsilama 9 495 11 259 15 17, 18: Jurjuna 10 607 19 297 9 19, 20: Samai 10 497 28 255 13 Thaqil Overall Mean (P) Overall Mean (F) 507 257

Participant Recruitment

Thirty undergraduate and graduate students at the Ohio State University aged between 17 and 38, both male and female, were recruited to participate in this behavioral experiment, with ten participants in each of the following categories:

 Middle-Eastern (Arab) group (A): being familiar with and having previous

experience in traditional Middle-Eastern music, including music typically

found in areas such as West Asia, North Africa, some of East Europe, and the

Arabian Peninsula

 Indian group (I): being familiar with and having previous experience in

classical Indian music, including music typically found in India, Bangladesh,

Sri Lanka, and some parts of Pakistan

 Unfamiliar/other group (O): being unfamiliar with and having minimal

previous experience with the music of the A and I groups

By “being familiar with and having previous experience in” certain musics, one needed to have either hands-on experiences in them such as singing, playing an instrument, dancing, etc., or exposure to such musical environments on a regular basis, such as growing up in a household that listens to these musics or goes to such performances. The criterion of listening experience was based on SMT, which indicates that one’s temporal perception has been rehearsed and shaped by its interaction with the musical environment one has been exposed to, even if he or she has no actual music- making experiences in these styles or practices (see chapter 2). The discovery of mirror neuron has also indicated that the neurons firing in the perception of real performances and in mental rehearsals are largely overlapping (Rizzolatti & Craighero, 2004). It is suggested that participating in music activities in both active and passive ways shapes one’s perceptual and cognitive processing within a particular context.

Volunteers with sensory or motor impairments were excluded from participating, as such impairments are not compatible with the design of the project. Three of the participants initially recruited for groups A and I were excluded from analyses because

74 according to their answers in the questionnaire, their listening interests and experiences turned out to feature no complex meters. The analyses of this study were based on the data collected from thirty participants. This research was approved by The Ohio State

University Institutional Review Board for Human Research.

Experiment Procedure

Informed consent was obtained from each participant after they were informed about the general nature of the experiment. The participants clearly understood that they could terminate the procedure and exit the study at any time. Prior to both parts of the experiment, participants were acquainted with the tests and practiced the experimental tasks with a set of stimuli that were not part of the experiment.

During the experiment the participants wore a pair of headphones to listen to the rhythmic patterns. Each of the patterns was looped continually and presented to the participants as repetitive cycles. Participants were asked to tap with their right hand to the heard sound patterns. They did so by tapping with a small metal pen on a wooden board, in front of which a microphone was placed to record the tap responses. In the first part of the experiment, the participants were instructed to tap to the perceived pulse. To specify the pulse task, the participants were asked “to tap regularly along with the played rhythms like a metronome, and to do so in the most comfortable and natural way they felt.” Their tapping and the presented rhythmic patterns were recorded simultaneously as two parallel sound tracks for further analysis. The participants were also videotaped from the side. For every rhythmic pattern, after the participant had synchronized regularly with

75 at least three consecutive cycles, the present pattern would be stopped and, after a brief gap, the presentation of the next pattern commenced.

Following the pulse test, a short break took place before the second part (meter test) started. In this part, all the conditions stayed the same as in the first part, except the required task. The participants were instructed to tap out the meter and/or the subgroups they perceived. It was described as “tapping at places where the pattern repeats, namely the most prominent places of the cycle that help them synchronize with the rhythmic flow.” It was explained to the subjects that depending on their perception, they had the choice to tap only once or more than once (if they heard any subdivisions) per cycle, but they were not expected to copy exactly the surface rhythm. After the participant’s tapping pattern became stable and the taps fell on the same places of a pattern for at least three consecutive cycles, the present pattern was stopped and the next pattern commenced. If the participant could not perform the task after the pattern was looped fifteen time, namely tapping regularly on fixed places for three consecutive cycles, the task was considered as not successfully performed.

In both the pulse and the meter tasks, the order of the rhythmic pattern presentation was randomized. Subjects’ tapping responses and the sound stimuli were recorded simultaneously on separate, synchronized tracks through Adobe Audition for future analysis. The participants were also videotaped from the side so that the bodily movements and the other visual information that were not recordable through the microphone could be documented as a supplementary reference. Each of the two parts contained twenty rhythmic stimuli and took about fifteen minutes, although this duration

76 varied according to the time each participant needed before they became able to tap regularly for at least three rhythmic cycles.

In addition to the behavioral responses, participants gave verbal feedback about their strategy for synchronizing and filled out a brief questionnaire at the end of the experiment session. At the end of both parts, the participants gave verbal feedback describing their strategies and difficulties with performing the tasks. At the end of the experiment, the participants filled out a questionnaire regarding the qualitative data to specify their musical cultural background (Appendix-B). The flow of the experiment session is summarized in Figure 4-2.

Figure 4-2. Flowchart of experiment procedure.

Analysis

The onset times for events in both the recorded sound event track and the tap response track were extracted using PRAAT (Boersma & Weenink, 2015) and a script was developed from a previous study (Will et al., 2015). The script determined the maxima of the first derivative of the intensity function of the signals, measured every millisecond with a 10-ms sliding window. A response event was attributed to a stimulus event if it occurred within ±1/2 IOI of that event. After the data extraction, the following three types of analysis were conducted.

Task Performance

There were two analyses in the “task performance” part. For each participant and each stimulus pattern, task performance was coded as “yes” (1) or “no” (0) according to the criteria given below. To assess the relationship between performance and experimental variables, I used a generalized linear mixed model (GLM) with binomial error distribution and a log link function to compare the percentage of correct performance, with group, task, tempo, and complexity (simple or complex meter) as fixed factors.

Pulse-periodicity analysis (Analysis I). The first analysis compared the correct performance in the pulse task and the performance showing perception of any pattern periodicity in the meter task. A response was counted as successful in the pulse task when the subject was able to tap continually and isochronously (e.g., tapping on every beat or every other beat within ± ½ IOI) for at least three consecutive cycles of the pattern. For the meter (periodicity) task, a response was considered as successful when at least one 78 tap was given at a fixed location within a pattern for at least three cycles, no matter whether it was a “metrically correct” location. For example, although the 7-beat Dawr

Hindi pattern featuring 3+2+2 subdivisions (D T T D tt T tt) has beats 1, 4, and 6 as its metrical accents, tapping regularly on the second beat (metrically incorrect beat) for three or more cycles is counted as a successful performance. However, in the meter

(periodicity) task, if the subject tapped on every pulse as in the pulse task, it was not considered a successful response even though the taps were given at the fixed locations within a pattern, because such a tapping response did not indicate any grouping or metrical comprehension of the pattern.

Pulse-meter analysis (Analysis II). The second analysis compared more specifically the correct performance in the pulse task and the performance showing correct understanding of the metrical structure in the meter task. For the complex meters, a response was counted as showing comprehension of the metrical structure when at least two taps were given at the fixed locations within a pattern. The taps needed to represent the correct subdivisions of the pattern. For example, for a 10-beat cycle having 3+2+2+3 subdivisions, with beats 1 and 6 as “Dum” strokes, and 4 and 8 as “Tak” strokes, the response successfully representing its metrical structure would be two taps on beats 1 and

6, or taps on beats 1, 6, and/or 4 and 8 (i.e., 1,4,6; 1,6,8; 1,4,6,8). As for the simple meters, at least one tap needed to be given at the fixed location where a “Dum” stroke was played. The only exception is pattern number three, a 3-beat pattern featuring “Tt T

T.” A response to this pattern was counted as successful performance as long as at least one tap was given at a fixed location, for there was no “Dum” stroke in this pattern.

Pattern of Tapping Response

The following part investigated the relationship between the subjects’ tapping response, task, and tempo. It analyzed how the overall tapping responses aligned with the stimuli for both the pulse and the meter tasks under both temporal conditions. In the first analysis, the tapping responses were split by the factor tempo. The tapping level of pulse task and the tapping frequency of meter task under two temporal conditions were compared. The second analysis split the tapping response by the factors tempo and group for further observation and interpretation. More details about these two analyses below.

Pulse vs. meter responses under two tempi (Analysis III). This analysis compared the subjects’ overall tapping response levels (i.e., intervals between taps) in the pulse and meter task. The changes of behavior caused by tempo manipulation within tasks were then compared across tasks. This comparison was to find out whether the behavioral changes caused by tempo manipulation in the two tasks were correlated to

(e.g., being proportional to) or disassociated with each other.

Tapping frequencies in relation to tempo and cultural group (Analysis IV).

Analysis IV further explored the tapping responses by splitting the first set of responses

(i.e., pulse vs. meter responses under two tempi) by the factor group. All the responses of the three groups to each pattern in both tempi were listed separately. The tapping frequency each beat received was plotted for further analysis and comparison. The following figure (Figure 4-3) is an example that shows the three cultural groups’ (from left to right: Middle-Eastern, Indian, other) tapping frequency of each beat for a 3-beat

80 pattern in the fast temporal condition (F) in both the pulse (upper row) and the meter tasks (lower row). Such analysis was performed for all ten rhythmic patterns.

Histogram Histogram Histogram Split By: patno, group Split By: patno, group Split By: patno, group Cell: 2, i Cell: 2, o Cell: 2, a 120 160 160

140 100 140 120 120 80 100 100

80 60 80

Count

Count Count 60 60 40 40 40 20 20 20

0 0 0 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 beatLabel beatLabel beatLabel

Histogram Histogram Histogram Split By: patno, group Split By: patno, group Split By: patno, group Cell: 2, a Cell: 2, i Cell: 2, o Inclusion criteria: phase+-90 from s1-30_meter.ssd Inclusion criteria: phase+-90 from s1-30_meter.ssd Inclusion criteria: phase+-90 from s1-30_meter.ssd 140 120 180 160 120 100 140 100 80 120 80 100

Count Count Count 60 80 40 60 40 40 20 20 20 0 0 0 0 1 2 3 4 5 6 7 8 9 10 0 1 2 3 4 5 6 7 8 9 10 0 1 2 3 4 5 6 7 8 9 10 beatLabel beatLabel beatLabel

Figure 4-3. (from left to right) Tapping frequencies of Groups A, I, and O of a 3-beat pattern to the pulse (upper row) and the meter (lower row) tasks in the fast temporal condition.

Synchronization (Analysis V)

This part analyzed the synchronization, or the phase relationship, between the stimuli’s sound events and the subjects’ responses. The instantaneous phase between them was calculated by the location of response events within stimulus event cycles, and the distribution of the response phases were visualized in circular plots. The angles between the stimuli and the response events presented the degree of synchronization.

When the two oscillatory systems are highly synchronized as simultaneous events, they show relative phase 0˚ (“in phase”) on the circular charts. If they are presented as precise off-beats from each other as alternative events set apart by equal periodicity, they show relative phase 180˚ (“antiphase”). Besides the mean synchronization angle (µ), the mean vector length (r) and the circular variance were also examined. The latter two were indicators of the degree of consistency of the subjects’ responses: the longer the r, the smaller the circular variance and the less variable the responses are.

This analysis investigated group differences within the pulse and the meter tasks, respectively, before comparing them across tasks. The three groups’ degrees of synchronization were compared using the µ angles, and their intra-group consistency was compared using the mean vector length and circular variance.

Chapter 5. Experiment Outcome

This chapter summarizes the outcome of the experiment and the analyses, which were based on the responses from 30 subjects (n=30), with 10 from each cultural group:

A (Middle-Eastern), I (Indian), and O (Others). This chapter presents the results of the analyses outlined in chapter 4, and a discussion of the results will follow in the next chapter.

Task Performance

Pulse-Periodicity Analysis (Analysis I)

In this analysis, which used generalized linear models (GLM) to compare the correct responses of pulse and periodicity, the main factors group and tempo were both significant. The I group performed significantly better (p=0.006) than the other two groups, but no significant difference was found between the O and the A groups (p=

0.17). The overall better performance of group I is likely due to the advanced experience and training of the recruited subjects in complex metrical structures. The significant effect of tempo (p=0.029) shows that overall performance at the fast (F) tempo was better than at the preferred (P) tempo of 120 bpm (Figure 5-1).

.8 F P

%correct .7

.5 A, M A, P I, M I, P O, M O, P

Figure 5-1. Analysis I: Task performance (mean % correct) for Pulse (P) vs. Periodicity (M). F= fast tempo; P= preferred tempo. A=Middle Eastern; I=Indian; O=Other.

Regarding the interactions between factors, significance was found between group and complexity and between task and complexity (Figure 5-2). Regarding the interaction between group and complexity, the I group performed significantly better for the simple meter than for the complex meter in both pulse and periodicity tasks (p=0.0078). Though the other groups did not show significant performance differences between simple and complex meters, there was the strong interaction between task and complexity

(p<0.0001): Both the A and O groups performed better for the complex meter in the periodicity task but performed better for the simple meter in the pulse task. These differences were especially prominent in A, which suggests that, in relative terms, participants are more familiar with the complex meter than with the simple meter. The O group showed similar results, though there were smaller performance differences between simple and complex meters. In absolute terms, however, the I group showed best

84 performance, followed by the O and the A group. Table 5-1 is a summary of the results in the pulse-meter analysis.

.8 C S

%correct .7

.5 A, M A, P I, M I, P O, M O, P

Figure 5-2. Analysis I: Task performance (mean % correct) for Pulse (P) vs. Periodicity (M). C=complex meter; S=simple meter; A=Middle Eastern; I=Indian; O=Other.

Table 5-1. Results for the fixed factors from the GLM analysis, showing parameter estimates, standard errors, Z statistics, and the associated probabilities for main factors and their interactions.

Estimate Std. Error z value Pr(>|z|) (Intercetp) 2.0955 0.4371 4.794 1.63e-06 *** groupI 1.8864 0.6881 2.742 0.00611 ** groupO 0.8681 0.6284 1.381 0.16716 tempP -0.4458 0.2037 -2.189 0.02859 * taskP 0.4563 0.2916 1.565 0.11759 groupA:compS 0.2603 0.3609 0.721 0.47082 groupI:compS 1.7245 0.6485 2.659 0.00784 ** groupO:compS 0.8400 0.4546 1.848 0.06462 tempP:taskP 0.5364 0.4067 1.319 0.18718 taskP:compS 3.6038 0.5884 6.125 9.07e-10 ***

Pulse-Meter Analysis (Analysis II)

In this analysis I compared the correct responses to pulse and metrical structure as assigned in the Middle-Eastern tradition. Again, a general linear model was used as in the previous analysis, and the results showed that the main factors task (p<0.001) and complexity (p=0.0014) were highly significant. In all three cultural groups and both temporal conditions, better performance was achieved in the pulse task than in the meter task (Figure 5-3), and in the simple meters than in the complex meters (Figure 5-4). Table

5-2 is a summary of the results in the pulse-meter analysis.

1 .9 .8 .7 .6 M .5 P

%Cor .4 .3 .2 .1 0 A I O

Figure 5-3. Analysis II: Task performance (% correct) Pulse (P) vs. Metrical perception (M). A=Middle Eastern; I=Indian; O=Other.

.6 C

%Cor S .4

0 M, F M, P P, F P, P Cell Figure 5-4. Analysis II: Task performance (% correct) for Pulse (P) vs. Metrical perception (M). C=complex meter; S=simple meter; F=fast tempo; P=mean preferred tempo.

Table 5-2. Results for the fixed factors from the GLM analysis, showing parameter estimates, standard errors, Z statistics, and the associated probabilities for main factors and their interactions.

Estimate Std. Error z value Pr(>|z|) (Intercetp) 1.2757 0.3188 4.002 6.29e-05 *** groupI 0.7282 0.4645 1.568 0.11697 groupO 0.6750 0.4681 1.442 0.14932 taskP 1.5899 0.3096 5.136 2.81e-07 *** compS 1.0163 0.3189 3.187 0.00144 ** groupI:compS 1.1117 0.4705 2.363 0.01815 * groupO:compS 2.1006 0.5009 4.193 2.75e-05 *** groupI:taskP 1.2864 0.4064 3.165 0.00155 ** groupO:taskP 1.4479 0.3995 3.624 0.00029 *** taskP:compS 1.2171 0.5519 2.205 0.02745 *

Significant interactions were found between group and task, group and complexity, and task and complexity. For the interaction between group and task, O

(p<0.001) and I (p=0.0016) groups performed significantly better than A in the pulse task

(O>I>A). This is an interesting phenomenon because the most experienced group (A) performed worse in pulse tapping, especially for complex meters. It indicates that these experienced listeners may be more strongly drawn to the metrical organizations and/or are more used to respond to the metrical aspects of these patterns, so that they could not simply keep their responses to the pulse without being influenced by the metrical structures. This suggests that they may have a different listening strategy than the other groups. As for the interaction between group and complexity, the I group (p=0.018) and the O group (p<0.0001) performed better for the simple meter than the A group. Finally, 88 there was a significant interaction between task and complexity (p=0.027), which confirms that pulse responses are influenced by the metrical organizations of the patterns.

For example, Analysis III showed that in the 7-beat patterns in the pulse task, beats 1 and

4 received more responses than the other beats.

It is worth noticing that for complex meters (C) in the meter task (M), the A group performed best, followed by the I and the O groups (A>I>O). This demonstrates the effect cultural factors have on one’s complex metrical understanding (Figure 5-5). This result corresponds with the hypothesis that the A group, being culturally familiar with the rhythmic patterns, better understands the metrical organizations than the other groups. It is followed by group I, who has experience with complex meters but is not familiar with the rhythmic patterns, whereas group O, the non-experienced listeners, achieved the lowest performance rate.

1 .9 .8 .7 .6 C .5

%Cor S .4 .3 .2 .1 0 A, M A, P I, M I, P O, M O, P

Figure 5-5. Analysis II: Task performance (mean % correct) for Pulse (P) vs. Metrical perception (M). C=complex meter; S=simple meter; A=Middle Eastern; I=Indian; O=Other.

Pattern of Tapping Response

Pulse vs. Meter Responses under Two Tempi (Analysis III)

In this analysis, the tapping level of pulse task and the tapping pattern of the meter task were compared.

Pulse task responses. There is a clear shift in reference level under the two temporal conditions for the pulse task (Figure 5-6), from dominantly 1-beat distance

(tapping on every beat) at P (slower, mean preferred tempo), to 2-beat distance (tapping on every other beat) at F (faster, doubled tempo).

6000

5000

4000 f 3000

count s

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0 1 2 3 4 5 6 7 8 9 10 tapDist (beats)

Figure 5-6. Tapping distances (in beats) for the pulse task under the two tempo conditions (all patterns). f: fast tempo; s: preferred tempo.

Examining the responses to the individual stimulus patterns (with all 3, 4, 7, 9, and 10 beats per cycle), a reference level shift was found from 1-beat to 2-beat intervals for the fast condition in all complex meters, but not in the simple meters. Interestingly, while there was no reference level shift caused by tempo change in both the 3-beat and 90 the 4-beat patterns, subjects selected different reference levels in the two pattern types.

For the 3-beat patterns, the pulse is dominantly felt at the single-beat level in both tempi, while for the 4-beat pattern, subjects dominantly responded at the 2-beat interval in both tempi.

These results not only demonstrate that the participants correctly performed the required task (tapping to the felt pulse regardless of the metrical structure), but also indicate that the selection of a reference level in the pulse task is strongly influenced by the tempo and—at least for the relatively short, simple patterns—by the physical features of the sound sequences.

Meter task responses. In the meter task, unlike pulse, no comparable shift in reference level was detected. In the slow condition, the 2-beat tap distance was the most frequent one. If there were a reference level shift, in this case a doubling of the tap period, we would expect beat distance two and four to show the dominant peaks.

However, we find that 1-beat and 3-beat distances were the most frequent ones in the fast condition and there was no doubling of the tap distance compared with the slower tempo

(Figure 5-7).

2000 1800 1600 1400 1200 f 1000 s

Count 800 600 400 200 0 1 2 3 4 5 6 7 8 9 10 tapDist (beats)

Figure 5-7: Tap distances (in beats) for the meter tapping task. f: fast tempo; s: preferred tempo.

For the meter task, an analysis of the tap distribution, or their location, within each stimulus pattern revealed that the overall tapping patterns and the agreement across subjects remained basically the same in both temporal conditions. In almost all rhythmic patterns, while the subjects’ tapping level (interval) to pulse went up from 1 beat to 2 beats, the pairs of two tempi in the meter task showed no relational differences regarding the tapping frequencies each beat received. Only the absolute numbers of tap received, especially those that received less frequent responses, changed slightly (Figure 5-8).

These results suggest a clear disassociation of the response from the pulse and meter tasks––the tempo change led to a shift in the reference level for pulse, but not for meter tapping

Histogram Histogram Split By: patno Split By: patno Cell: 7 Cell: 8 Inclusion criteria: phase+-90 from s1-30_meter.ssd Inclusion criteria: phase+-90 from s1-30_meter.ssd 225 300 200 250 175 150 200 125

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Figure 5-8. Tapping frequency histograms for two complex patterns in the meter task. P (preferred tempo, left) vs. F (fast tempo, right). Cells 7 and 8: 7-beat Dawr Hindi pattern; Cells 13 and 14: 9-beat Awnak Turki pattern.

Additionally, there were no unambiguous “head nodes”––the beats that start a periodic sequence––as suggested in dominant Western meter theories (Fitch, 2013), especially in the complex meters. In the meter task, individual participants’ tapping frequencies showed disparity in their head nodes. For example, in the preferred-tempo 7-

93 beat Dawr Hindi pattern, five participants tapped only on the fourth beat and considered it their head node; two participants tapped completely or mostly on the first beat; one participant tapped mainly on the sixth beat. Three other participants tapped equally often on both the first and the fourth beats, and it is difficult to tell which beat they perceived as the beginning of sequence. The absence of unambiguous head nodes was also seen in the response pattern across cultural groups. This will be further discussed in the section below, “Response Split by Tempo and Cultural Group (Analysis IV).”

There are some other interesting observations. First, even in the pulse task, the surface features of rhythmic patterns seem to have a slight but noticeable influence on the tapping response. To compare the responses to the 3-beat Samai Taer (D T T) and the other 3-beat patterns having no Dum stroke (Tt T T) (pattern Nos. 5 and 6, respectively; see Appendix A), it was found that subjects preferred to tap on the first beat in the former but tapped more equally on every beat in the latter (Figure 5-9). It is worth noting that in the fast “Tt T T” pattern, the second beat received the most taps.

Histogram Histogram Split By: patno Split By: patno Cell: 1 Cell: 2 300 450 400 250 350 200 300 250

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Figure 5-9. Tapping frequency to the 3-beat patterns in the pulse task. Cell 1: Samai Taer (preferred tempo); Cell 2: Samai Taer (fast tempo). Cell 3: “Tt T T” (preferred tempo); Cell 4: “Tt T T” (fast tempo).

Second, depending on different surface features or metrical organization, tempo change may or may not cause a referential shift in people’s pulse conception. For the 4- beat pattern, in both temporal versions, the pulse was dominantly felt at the 2-beat level

(tapping on beats 1 and 3). For the 7-beat Dawr Hindi pattern, while in the preferred tempo no beat was clearly dominant, in the fast tempo beats 1 and 4 attracted more taps than the other beats (Figure 5-10). As for the 10-beat patterns, in the fast Jurjuna and the

Samai Thaqil in both tempi, instead of the first beat and the following odd-number beats, the even-number beats attracted more responses (Figure 5-11).

Histogram Histogram Split By: patno Split By: patno Cell: 7 Cell: 8 160 200

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Count Count 60 80 60 40 40 20 20 0 0 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 beatLabel beatLabel

Figure 5-10. Tapping frequency to the 7-beat Dawr Hindi pattern in the pulse task. Cell 7: perferred tempo; Cell 8: fast tempo.

Histogram Histogram Split By: patno Split By: patno Cell: 18 Cell: 19 200 160 180 140 160 120 140 120 100

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Count Count 80 60 60 40 40 20 20 0 0 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 beatLabel beatLabel

Histogram Split By: patno Cell: 20 250 225 200 175 150

125 Count 100 75 50 25 0 1 2 3 4 5 6 7 8 9 10 beatLabel

Figure 5-11. Tapping frequency to the 10-beat patterns in the pulse task. Cell 18: Jurjuna (fast tempo tempo); Cell 19: Samai Thaqil (preferred tempo). Cell 20: Samai Thaqil (fast tempo).

Response Split by Tempo and Cultural Group (Analysis IV)

Pulse response. Generally, the result showed no clear or consistent cultural differences in the pulse task regarding participants’ tapping frequency per beat (i.e., the number of taps each beat received). Compared to those in the meter task (discussed later in this section), the tapping frequencies of the pulse task showed relatively higher inter- group agreement despite some discrepancies. These discrepancies are due to the different 97 tapping distances (intervals) chosen by the participants in response to the rhythm, as well as the influence of the surface features of the patterns on participants’’ responses. Figure

5-12 shows two examples from a 3-beat pattern and a 7-beat pattern.

Histogram Histogram Histogram Split By: patno, group Split By: patno, group Split By: patno, group Cell: 3, a Cell: 3, i Cell: 3, o 120 90 100 80 90 100 70 80 70 80 60 60 50

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Count Count Count 40 40 40 30 30 20 20 20 10 10 0 0 0 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 beatLabel beatLabel beatLabel

Histogram Histogram Histogram Split By: patno, group Split By: patno, group Split By: patno, group Cell: 7, a Cell: 7, i Cell: 7, o 60 50 50 45 45 50 40 40 35 35 40 30 30

30 25 25

Count

Count Count 20 20 20 15 15 10 10 10 5 5 0 0 0 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 beatLabel beatLabel beatLabel Figure 5-12. Tapping frequency in the beat task split by groups. Cell 3: 3-beat “Tt T T” (preferred tempo); Cell 7: 7-beat Dawr Hindi (preferred tempo).

Tempo changes did not seem to significantly affect the tapping frequency distributions. However, in some patterns, especially patterns comprising even-number beats, fast tempi did cause some beats to receive more taps than in a slower tempo. This is most likely because when participants tapped at a “higher level” in an even-number- beat pattern, they always tapped on the fixed beats and did not need to shift their tapping between beats of odd numbers and even numbers (i.e., 1, 3, 5, 7, 2, 4, 6, 8, 1, 3, 5, 7, etc.)

(Figure 5-13).

Histogram Histogram Histogram Split By: patno, group Split By: patno, group Split By: patno, group Cell: 19, a Cell: 19, i Cell: 19, o Inclusion criteria: 10beat from s1-30_beat_B.ssd Inclusion criteria: 10beat from s1-30_beat_B.ssd Inclusion criteria: 10beat from s1-30_beat_B.ssd 50 60 60

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0 0 0 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 beatLabel beatLabel beatLabel Histogram Histogram Histogram Split By: patno, group Split By: patno, group Split By: patno, group Cell: 20, a Cell: 20, i Cell: 20, o Inclusion criteria: 10beat from s1-30_beat_B.ssd Inclusion criteria: 10beat from s1-30_beat_B.ssd Inclusion criteria: 10beat from s1-30_beat_B.ssd 80 70 80

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0 0 0 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 beatLabel beatLabel beatLabel Figure 5-13. Tapping frequency for 10-beat Samai Thaqil pattern in the pulse task, two temporal conditions, split by groups. Upper row: preferred tempo; lower row: fast tempo. Left to right: A, I, O.

Meter response. The comparison of the response patterns across cultural groups suggests that there are no unambiguous “head nodes” (see “Meter task responses” above).

Instead, cultural variability in the choice of head nodes was found in nearly all patterns of both simple and complex meters; the beat(s) that receive(d) the largest number of taps was (were) different from group to group. This phenomenon suggests that participants of different groups may rely on different cues to group the sound event sequence. Which beat receives most taps may be influenced by listeners’ experience, and is not determined by the Middle-Eastern metrical structure. For the 3-beat “Tt T T” pattern in the preferred tempo, the second beat received dominantly larger numbers of taps than the other two

99 beats in group I, whereas the same beat received the least beats in group A; in group O, all three beats received similar numbers of taps (Figure 5-12, upper row).

For the 4-beat pattern in the preferred tempo, the head node appeared to be the first beat in groups A and O, but the third beat in group I (later in Figure 5-16, upper row). In the fast 7-beat Dawr Hindi pattern, the first beat dominated in group A, whereas the fourth beat dominated in groups I and O. For the 9-beat Awnak Turki pattern in the preferred tempo, group A had almost equal taps on beats 1, 4, 6, and 8, whereas group I tapped most frequently on beat 4, and group O tapped most frequently on beat 1, followed by beat 4. In the fast tempo of the same pattern, beat 1 received more taps than beat 4 in group A, but the inverse was true in groups I and O. These examples are illustrated in Figure 5-14. Similar differences were also found in the following patterns:

7-beat Nawakht (fast), 9-beat Aqsaq (both tempi), 9-beat Karsilama (fast), 10-beat

Jurjuna (fast), and 10-beat Samai Thaqil (both tempi). All these examples indicate that there is no unambiguous head nodes (“downbeats” or beginning of a cycle; see chapter 3).

The head node perception varies from group to group.

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Count Count Count 40 30 30 30 20 20 20 10 10 10 0 0 0 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 beatLabel beatLabel beatLabel

Figure 5-14. Tapping frequency of the meter task. From left to right: groups A, I, O. Cell 8: 7-beat Dawr Hindi (fast tempo); Cell 13: 9-beat Awnak Turki (preferred tempo); Cell 14: 9-beat Awnak Turki (fast tempo).

Several patterns also showed that dominant head nodes may change with tempo, and the changes differ between groups. For the 3-beat “Tt T T” pattern, tempo change caused a clear shift in groups A and I, but not in group O (Figure 5-15). For the 4-beat pattern, the head node of group I switched from the third beat to the first beat when the tempo was doubled, whereas the other groups both perceived the first beat as the head

101 node in both tempi (Figure 5-16). For the 7-beat Nawakht pattern, the head node of group

I switched from beat 1 to beat 4 with the tempo change. While group A’s and O’s head nodes remained the same (beat 1) in both temporal conditions, the beats perceived to be secondarily prominent were significantly influenced by the tempo change (Figure 5-17).

More interestingly, in the 9-beat Aqsaq pattern, a doubled tempo made the prominent beat change from beat 5 to beat 1 in group A, but the inverse response was found in group I (from beat 1 to beat 5) (Figure 5-18). According to the distribution of tapping frequencies, group O’s responses seemed to be less influenced by tempo change than the other two groups, suggesting that the listeners with little experience of complex meters rely more on the surface rhythmic features to synchronize with such patterns, rather than on grouping pattern or metrical organization. This was confirmed by the interviews result with the participants; more on this will be elaborated in chapter 6 (Discussions).

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Histogram Histogram Histogram Split By: patno, group Split By: patno, group Split By: patno, group Cell: 3, i Cell: 3, o Cell: 3, a Inclusion criteria: phase+-90 from s1-30_meter.ssd Inclusion criteria: phase+-90 from s1-30_meter.ssd 90 70 100

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Histogram Histogram Histogram Split By: patno, group Split By: patno, group Split By: patno, group Cell: 4, a Cell: 4, i Cell: 4, o Inclusion criteria: phase+-90 from s1-30_meter.ssd Inclusion criteria: phase+-90 from s1-30_meter.ssd Inclusion criteria: phase+-90 from s1-30_meter.ssd 140 90 120 80 120 100 70 100 60 80 80 50

Count Count Count 60 40 30 40 40 20 20 20 10 0 0 0 0 1 2 3 4 5 6 7 8 9 10 0 1 2 3 4 5 6 7 8 9 10 0 1 2 3 4 5 6 7 8 9 10 beatLabel beatLabel beatLabel Figure 5-15. Tapping frequency to the 3-beat “Tt T T” pattern in the meter task. From left to right: groups A, I, O. Cell 3: perferred tempo; Cell 4: fast tempo.

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Histogram Histogram Histogram Split By: patno, group Split By: patno, group Split By: patno, group Cell: 5, a Cell: 5, i Cell: 5, o 80 70 90 80 70 60 60 70 50 60 50 40 50

Count Count Count 30 40 30 30 20 20 20 10 10 10 0 0 0 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 beatLabel beatLabel beatLabel

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Count Count Count 60 40 60 40 30 40 20 20 10 20 0 0 0 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 beatLabel beatLabel beatLabel Figure 5-16. Tapping frequency to the 4-beat pattern in the meter task. From left to right: groups A, I, O. Cell 5: perferred tempo; Cell 6: fast tempo.

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Histogram Histogram Histogram Split By: patno, group Split By: patno, group Split By: patno, group Cell: 10, a Cell: 10, i Cell: 10, o 90 80 70 80 70 60 70 60 50 60 50 50 40

Count Count Count 40 30 30 30 20 20 20 10 10 10 0 0 0 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 beatLabel beatLabel beatLabel Figure 5-17. Tapping frequency to the 7-beat Nawakht pattern in the meter task. From left to right: groups A, I, O. Cell 9: perferred tempo; Cell 10: fast tempo. 104

Histogram Split By: patno, group Histogram Histogram Cell: 11, a Split By: patno, group Split By: patno, group 90 Cell: 11, i Cell: 11, o 70 60 80 60 70 50 60 50 40 50 40

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0 0 0 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 beatLabel beatLabel beatLabel Figure 5-18. Tapping frequency to the 9-beat Aqsaq pattern in the meter task. From left to right: groups A, I, O. Cell 11: perferred tempo; Cell 12: fast tempo.

Synchronization (Analysis V)

In the synchronization phase analysis for the pulse task, the result showed that the angle of the mean vector (µ) did not vary significantly between groups. It was around 340 or –20 degrees, slightly ahead of the stimulus. This is accordant with the previous findings that people usually tap slightly earlier to quasi-isochronic stimuli, showing a slight anticipation of the upcoming sound events (for a review, see Repp & Su, 2013).

However, there was some variation between groups and conditions in the mean vector length (r) and the circular variance, which indicate the consistency of the responses and the strength of synchronization.

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Overall, in the pulse task, group O showed the smallest variance (O

Wheeler test showed that all the above differences were significant except for the complex meters, in which the difference between O and I was not significant. The least experienced group, O, showed the highest intra-group consistency, suggesting, again, that these participants may rely more uniformly on surface features of the stimuli. For groups

A and I, who are more familiar with long rhythmic cycles, there were larger variations in terms of consistency as a group.

In the meter task, the mean vector (µ) varied around 340~345 or –20~–15 degrees, minimally smaller than that in the pulse task. For the variance and vector length, group I showed the smallest variance and the longest r (I

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Figure 5-19. Circular charts of group response in the meter task. a: Middle-Eastern; i: Indian; o: other.

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Chapter 6. Discussions

The main aim of this experiment was to examine whether bodily responses to pulse and meter are influenced by cultural factors, with the former typically understood as a natural inclination and the latter a culturally dependent ability. If the Western hierarchical structure does not explain the relationship between responses to pulse and meter, will there be an alternative way to do so across cultures? Further, what roles do the two other concepts frequently linked to meter, grouping and entrainment, play in metrical comprehension? If cultural distinctions are found, how is the degree of intra-group agreement different for the three groups? The current chapter begins with discussions based on both the quantitative and qualitative results of this experiment and ends with general discussions and suggestions for future research.

Discussions Based on Quantitative Analyses

Analyses I and II

The experimental results indicated, in accordance with the hypothesis, that cultural factors do have an influence on participants’ rhythmic processing, which was reflected in their tapping responses, with the culturally familiar group (A) most successfully performing the meter task for complex meters (Analysis II), followed by the secondary familiar group (I), and then the unfamiliar group. However, at first glance the 108 finding of Analyses I and II seem to counter the hypothesis that cultural factors appear to be influential on both responses to meter and pulse, not meter alone, especially for Group

A. It is likely that the listening habit (i.e., grouping) of people who are familiar with the rhythmic patterns interfered with their response in the pulse task and prevented them from tapping isochronously. The results from each of the three groups will be discussed in turn below.

Group A. The culturally familiar group (A) had an overall low performance rate in Analyses I and II. In the pulse-periodicity comparison (Analysis I), Group A achieved the lowest performance in general. In the pulse-meter comparison (Analysis II), Group A showed the lowest achievement in the pulse task but was significantly more successful than the other two groups in the meter task for complex meters.

This result demonstrated Group A’s familiarity with Middle-Eastern rhythms and their metrical organizations. The low performance rate in the pulse task might be due to a tendency to perform grouping instead of tapping isochronously to pulse; this also lowered their overall rate of performance. Notably, in Analysis II, although the overall responses from all groups showed a better performance in the pulse than in the meter task, and in simple than in complex meters, Group A performed the best in the meter task for complex meters and worst in the pulse task. That is, there are significant differences between responses from the culturally familiar group and those from the other two. In addition, Group A’s performance in the periodicity task (in Analysis I) also suggested relatively higher familiarity with complex than with simple meters.

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If Group A’s low performance in the pulse task was indeed due to their tendency of grouping, this phenomenon would correspond to Clayton’s (2000) statement that experienced listeners perceive complex rhythmic cycles by grouping similar components together through gestalt principles. This could also explain why the concepts of pulse and grouping are easily and frequently confused in discussions of meter. From these two analyses, it seems that familiarity with the patterns and previous experience in complex meters have made grouping a significant listening strategy for listeners. The more familiar they are with the patterns, and the more experienced they are in complex meters, the more they rely on grouping for metrical understanding. In the case of Group A, the grouping effect was so strong that the participants were interfered and did not always tap isochronously to pulse. This phenomenon also serves as a hint that pulse and meter do not associate with each other in the Western sense: Their superior metrical comprehension of complex meters seemed to have nothing to do with pulse, on which task they did inferiorly. As already proposed in chapter 3, I would argue that it is important to distinguish pulse and grouping in order to discuss meter cross-culturally.

Group I. As the most successful group in the pulse-periodicity comparison

(Analysis I), which also performed the second best in the meter task for complex meters

(in Analysis II; second to Group A), Group I demonstrated a superior ability to perform tasks in complex rhythmic cycles, although they did not necessarily perform them in a

“culturally correct” manner (tapping on appropriate beats to reflect Middle-Eastern metrical organizations). Group I’s response coheres with Kalender et al.’s (2012) finding that experience in complex meter enhances one’s ability to understand foreign complex

110 meters. It is possible that they related the Middle-Eastern rhythms to patterns they already knew so as to perform the required tasks without perceiving the culturally correct metrical organizations.

On the other hand, unlike Group A, whose tendency of grouping was so strong that it interfered with their stability to tap isochronously to pulse, Group I was able to tap regularly in the pulse task regardless of the patterns’ metrical organizations. This suggests that although their experience in complex meters has improved their adaptation to unfamiliar complex rhythmic cycles, this does not affect their response in the pulse task. However, their solid musical training may also be a contributing factor in explaining these results (see later discussions under “Analysis V” and “Participants Recruitment”).

Group O. Group O appeared to be the most successful group in the pulse task in

Analysis II, suggesting that unfamiliarity with patterns and inexperience in complex meter seems to make one’s pulse perception less influenced by metrical structure of the stimuli. As for the meter task for complex meters, their performance ranked last.

However, in Analysis I, their overall performance was the second best. As discussed in chapter 1, humans naturally want to comprehend surrounding situations by interacting with them based on their previous experiences. Being unfamiliar with the presented rhythmic patterns, Group O participants seemed to look for acoustic features other than meters as perceptual cues. As shown in their performance in the periodicity task, this strategy did enable them to catch the repetition of cycles to a considerable degree, although the result from Analysis II showed their unawareness of the metrical organizations. This presumed listening strategy is confirmed by the information collected

111 from the participants in the follow-up interviews, which I will discuss more thoroughly in a later section of this chapter (see “Discussions Based on Qualitative Information”).

Analyses III and IV

Pulse-Meter Dissociation. Analysis III found a clear dissociation between responses to meter and pulse. First of all, a proportional correlation between pulse and meter as proposed in the Western theories does not seem present in participants’ actual listening experience. For all complex meters, tempo change has a strong influence on participants’ selection of pulse level. With the doubled tempi, their dominant reference level shifted from 1-beat to 2-beat intervals in the pulse task, but in the meter task, their tapping patterns remained basically the same and indicated no proportional relations between two tempi as found in the pulse task. Secondly, as hypothesized, pulse responses appear to be less affected by one’s familiarity with the presented rhythm, whereas meter requires additional knowledge and attention. As addressed in chapter 4, for patterns containing odd-number beats, the above-mentioned referential shift means that one taps on alternating beats for every consecutive cycle (e.g., from 1, 3, 5, 7, to 2, 4, 6, 8, and to

1, 3, 5, 7, etc.). Even so, the majority of participants successfully performed the pulse task regardless of the metrical structures. The phenomenon that participants from all groups tapped on different beats in successive cycles with ease suggests that pulse performance is an intuitive kind of response that does not require familiarity with the patterns and that it does not serve as the reference for metrical percept in a hierarchical relationship.

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The results indicate a clear distinction between perceptions of pulse and meter, with the former more universally and intuitively processed and the latter requiring more familiarity with the patterns and attention. The following portion will turn to how cultural factors have an influence on metrical understanding.

Unravelling “Metrical Entrainment.” The results from Analysis IV serve as a brilliant support for the pulse-meter dissociation and, at the same time, challenges Fitch’s

(2013) understanding of meter from a cross-cultural perspective. By arguing headedness

(i.e., having an initial downbeat) to be “a natural, pre-theoretic aspect of metrical structure” (p. 5), Fitch implied that metrical understanding is to some degree embedded in the rhythmic patterns and that it is a natural, shared ability among humans to discover the underlying structure without special training or knowledge. However, as demonstrated in chapter 5, inter-group disagreement on headedness is the norm in almost all patterns, including those of simple meters. It means that which beats participants perceived as head nodes is not determined by the Middle-Eastern metrical structures.

Rather, listeners rely on various features of the surface rhythm to extract recurring cycles, and which features stand out to become one’s perceptual cues may depend on the person’s previous experience, namely the cultural influences one has been exposed to.

This is an interesting discovery that coheres with London’s (2004) analysis of metrical entrainment. Among all three groups, there was indeed entrainment on different levels indicated by “some aspect of [the participants’] biological activity [being synchronized] with the regularly recurring events” (p. 4). However, there needs to be clarification for what it is that one entrains to. Different from London, who regarded

113 meter perception to be synchronization with the metrical organizations, I propose that what we understand as metrical entrainment is synchronization with a variety of components—metrical structure being only one of them and it involves the listeners’ familiarity with or prerequisite knowledge of such meters. In most of the cases, “metrical entrainment” is in fact synchronization with various components that are other than meter—namely, certain surface features, grouping of sound sequences, or some sort of combination of the two depending on miscellaneous cultural influences. If people of different cultures do not consent on the head nodes for even simple meters, something theorists rarely question, I would argue that there is no sign for a pre-given,

(hierarchically) underlying metrical structure for the listeners to uncover perceptually, as it is assumed in contemporary meter theories.

Analysis V

In analysis V, the phase angle did not vary significantly between groups.

However, there was some variation between groups and conditions in the mean vector length and the circular variance, which indicate the consistency of the responses and the strength of synchronization.

The inexperienced group, Group O, showed the highest intra-group agreement in the pulse task (O>I>A). In the meter task, Group I has the highest intra-group consistency

(I>O>A). The result nicely echoed the discussions of Analyses I through IV on pulse.

Accordant with my previous argument that people unfamiliar with complex meters and the stimulus patterns are less disturbed by the metrical organizations in pulse perception,

Group O had the highest intra-group consistency in the pulse task, followed by Group I.

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Group A showed the largest intra-group variance, and a factor contributing to this result is likely their tendency toward grouping, as mentioned above.

The outcome of Analysis V on meter is worth noticing. While Group I’s low variance obviously demonstrated their successful perception of recurring cycles and their confidence in responding to them, Group A, who was expected to have the best understanding of the patterns, achieved the lowest intra-group consistency. Group O, the unfamiliar group, had a middle level of variance between Groups I and A. However, these differences were not very prominent.

Discussions Based on Qualitative Information

Participants Recruitment

The challenge of conducting quantitative studies on cross-cultural topics has been discussed in chapter 4. Despite the effort to break down “culture” into more specific factors (i.e., exposure to certain musics) rather than defining it by nationalities or geographic boundaries, it is still difficult to ensure equivalent conditions across cultural groups. Take the issue of music training as an example, the same recruiting description

(“having hands-on experience on or regular exposure to” certain music types) has attracted participants with a large range of musical experience in their culture. In the

Columbus, Ohio, community,4 a large Indian population identifies strongly with Indian culture and intentionally provides their children with lessons such as Indian classical

4 The participants were all college or graduate students and scholars at Ohio State University, in Columbus, Ohio, because of IRB regulation.

115 music or dance, while the Middle-Easterners of the same community might not be preserving their culture in a comparable way.

This difference was noticed since the early stage of participant recruitment:

Almost all the Group I volunteers were well-trained Indian musicians or dancers, while many of the Middle-Eastern ones thought themselves qualified for this experiment merely because they listened to Arabic pop music, which is heavily Westernized and contains no traditional complex meters. To filter out unqualified participants, volunteers who expressed interest later in the recruitment period were asked to submit samples of the “traditional music” they listened to before scheduling an experiment session. Only those who regularly listened to the intended types of music were invited to participate in the experiment.

Even so, the recruited participants of Groups A and I still appeared to have a large disparity concerning musical ability. Although SMT and the research of mirror neurons do support that mental rehearsals through listening experience also shape one’s musical perception similarly as if one has hands-on experience of it (see chapter 4), musical training still affects participants’ perception and bodily response to a notably different extent. As research has implied, musical training enables musicians to have different mental conceptualization of time (e.g., Aleman, Nieuwenstein, Böcker, & de Haan, 2000;

Palmer & Krumhansl, 1990) that expedite their extraction of temporal information (Kraus

& Chandrasekaran, 2010).

According to their self-report, nine out of ten participants of Group I had training in Indian classical music or dance, and the other one was a performing musician in

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Western classical and jazz music; six out of ten participants of Group O were professional musicians, while the other four also had informal musical training sometime in the past. As for Group A, six out of ten reported themselves as non-musicians who had received no musical trainings at all; one was a self-taught amateur; only three of them explicitly reported themselves to be Greek dancers (for more discussions on participant recruitment, see the following section). With the listening experience in Middle-Eastern rhythms, Group A did demonstrate their distinctiveness as a culturally familiar group in the pulse-meter comparison (Analysis II). However, in the pulse-periodicity comparison

(Analysis I; Figure 5-1), they had the lowest overall performance rate when the criterion for a successful performance (i.e., periodicity recognition) was not so challenging to those who had been musically trained in the other two groups. Group A’s lack of musical training might have also lowered their intra-group agreement in the meter performance of

Analysis V.

Listening Strategies

The following discussions are based on my notes of observation during the experiment sessions and the qualitative data from post-experiment interviews. The data were in agreement with the quantitative results and supported their interpretation.

To begin with Group A, participants reported the pulse task to be easy, although a large number of them actually failed to perform the required task because they tapped to the perceived grouping instead of pulse. For the meter task, they generally needed a few trial-and-error cycles before being able to tap along with the patterns. On interviews about their listening strategies, most of them were unable to describe much but answered

117 briefly such as “didn’t think too much” and “just felt it.” These reports confirmed that experienced listeners seemed to synchronize with the patterns in an interactive, natural way and explained why in the pulse task, they entrained comfortably to the felt grouping, not pulse.

For Group I in the pulse task, while some of the participants simply responded without too much thinking, some reported to have felt a tendency to adapt to “the places that shift” in complex meters. However, because part of the instruction asked participants to tap regularly with the same intervals, they were able to keep it (quasi-)isochronous. For the meter task, many of them imagined playing on their instruments or related the rhythms to dance steps. Other than tapping, they employed abundant bodily movements such as hand gestures, head nodding, and foot tapping to aid their synchronization with stimulus patterns, especially during the meter task. They also had richer languages for describing their entraining strategies, which mostly concerned how they related the heard rhythms to the meters they already knew. These data correspond with their tendency to group, ability to tap to pulse, and successful synchronization with pattern periodicity based on their subjective understanding.

As for Group O, the participants had reported no difficulties for the pulse task, confirming that they could comfortably tap to the pulse without being disturbed by the metrical organizations. In the meter task, several participants relied on certain features to cue their attention for the upcoming “head nodes.” For example, the 9-beat Karsilama (D tt T tt D tt T T T) has three successive loud strokes on beats 7, 8, and 9. Some participants reported to have relied on them to find the following downbeat without

118 having any ideas about the metrical organizations. On the other hand, in the meter task of

Analysis IV, Group O was the least influenced by tempo change. I relate this phenomenon to the aforementioned listening strategy. Being less skillful in grouping, in which the other two groups had more experience, many Group O participants only waited for the cuing features that forecast the upcoming head nodes for longer rhythmic cycles.

Some other participants of the group did this more mechanically by recognizing a special sound feature at a fixed place of the pattern, counting the beats before it recurred, and then counting toward its next recurrence.

Lastly, all groups found the pulse task to be easier than the meter task and that it required more effort and consideration to fulfill the meter task. This is an explicit answer to the hypothesis that meter requires more attention. The participants’ self-reported listening strategies discussed above are consistent with the quantitative results that Group

A had a strong tendency for grouping; so did Group I, but this tendency only had limited influence on their response to pulse; Group O was the least interfered by grouping effect in the pulse task. For the meter task, both Groups A and I relied more on grouping and their past experience in Middle-Eastern and Indian music, respectively, whereas Group O relied more on the physical, surface rhythms.

Major Findings and General Discussions

The result of this behavioral experiment found no evidence of hierarchical processing between musical pulse and meter, and a proportional correlation between pulse and meter as proposed in contemporary Western meter theories does not seem present in the actual listening experience. This challenges not only theorists such as 119

Lerdahl and Jackendoff (1981, 1983) on the notion that meter is based on isochronous pulse, but also ideas of Clayton (2000) and Magill and Pressing (1997) about irregular pulse. In the experiment, participants of all cultural groups were able to tap (quasi-) isochronously to pulse regardless of the patterns’ metrical organizations. Only a few of those who were familiar with the patterns (in Group A) tended to be drawn by the meters during the pulse task and failed to tap regularly. Though pulse and meter are both cognitive constructs, they are different in that pulse appears to be a bodily reaction, and meter a theoretical construct that is culturally shaped. As pointed out in chapter 2, pulse as a bodily reaction might involve a resonance of human motor system that governs periodic movements. If that holds true, pulse cannot be non-isochronous, and it is relatively independent from meter. The results of the current experiment testify to this understanding of pulse.

With the results of this study, I propose grouping to be an important ability for metrical understanding, which is done through one’s entrainment to the surface sound features of a recurrent rhythmic cycle. What is understood as “meter perception” can all be explained differently as perceptual grouping based on synchronization with the physical features of sound sequences. In other words, what is assumed by Western theorists as metrical analysis is in fact analysis of responses to grouping phenomena as a result of a confusion of concepts—concepts of beat, pulse, grouping and meter. Such analytical confusion is due to the unawareness of the distinction between “music as mental representations” developed in a literary tradition, and “music as acoustic perceptions” that can only be processed linearly. All their research can be re-interpreted

120 in terms of linear-sequential processing and does not require the existence of hierarchical structures. This attests to the importance of my clarification between pulse, beats, and grouping (see chapter 3), and my proposal to understand meter through the grouping phenomenon will provide a solution to discuss this aspect of musical time in a cross- cultural context.

Cultural factors were found to have great influences on the ability for and the tendency of grouping, therefore make meter perception culturally specific. Generally, people having higher familiarity with specific patterns and more experience in complex meters show a notable tendency to group. Non-familiar listeners, in order to comprehend the foreign recurring cycles, also look for perceptual cues in the physical, auditory sound features to synchronize with. Given the fact that pulse is related to the physiological mechanisms of motor system, the ability reponding to pulse is less affected by cultural factors, but listeners who are familiar with the rhythms have relatively a stonger tendency to perceive them as groups of events through gestalt principles. Their listening strategies through grouping were reflected in the pulse performance to a notaciable extent.

Suggestions for Future Research

This dissertation began with an introduction of the mind–body, humanity–science integration, grounding the entire thesis on the necessity of incorporating biological and physiological considerations into cultural discussions. Culture, as neither an entity with clear boundaries nor a deconstructed concept as postmodernists pose, is constantly developed by interactions between mind and body within a given environment. Studying

“nurture” without reflecting on “nature” is therefore incomplete. 121

Contemporary musicology and music theories have been largely developed in and for Western music and may not be applicable to non-Western musics. Ethnomusicology has a cultural sensitivity that sets its focus on non-Western music; however, there is a lack of empirical studies, and those who rely heavily on the interpretive approach might have risked falling into postmodern extremes and loses the common ground for music as a universal phenomenon among humans. Recent developments of music psychology, music perception, and music cognition have embraced more interdisciplinary (e.g., scientific) methods into the studies of music, albeit mainly examining only Western music. Earlier chapters, by revisiting the concepts of pulse and meter from an integrated view of them, have already shown that it is crucial to place a balanced weight on all these fields for music studies. Giving undue emphasis to any of them may lead to misinterpretation or partial understanding in a cross-cultural context. As a relatively newly developed discipline, cognitive ethnomusicology is worth more attention, and the current study can be followed up with further inquiries.

In this study, cultural influences were broken down into factors such as musical environment one has been exposed to and types of musical training one has undergone, but these factors were used solely as qualitative data. In the future, I suggest to further break down “culture” into quantifiable factors and include them in statistical analysis.

There can be more specific conditions in participant recruitment as well: for example, frequencies and lengths of exposure to certain types of music, years of musical training, and age of beginning of training. Given that development of metrical perception (by now it may be more suitably termed “group detection”) and preference seems to start at

122 infancy and is largely decided at an early age (Soley & Hannon, 2010; Hannon & Trehub,

2005b), as discussed in chapter 3, it might also be important that a participant has been exposed to the acquired types of music early enough in their lives. For example, they need to have been raised in a household or environment listening to these musics; those who have developed their interests in these musics during college days, despite the large exposure of them, may not perceive the temporal components in the same way as “native listeners” do.

The group differences in the perception of head nodes suggest that listeners of different cultures may follow distinct cues for entrainment and grouping. It will be interesting to continue the study with research investigating which sound features listeners entrain to, and how these features are related to the listening experience or other experiences in their own culture, such as language and dance, since one’s musical perception and cognition may be so widely shaped by the entire package of life. There were also individual differences within groups. More thoroughly listed conditions for subject recruitment (as suggested above) and a post-experiment questionnaire with specifically designed questions may help understand both the relationship between participants’ cultural backgrounds and their preferred sound features as the perceptual cues. Since entrainment is a process, the “trial-and-error” phase before successfully synchronizing with the rhythmic patterns is also worth being studied, further inquiring whether there are distinct listening strategies by comparing the learning patterns between groups.

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On the other hand, the stimuli used in this experiment were percussion rhythms in which the pitch of strokes were only differentiated by a lower tone “Dum,” a higher tone

“Tak,” and some softer strokes of the combination of the two pitches. If group detection of a recurrent rhythmic cycle requires special attention and is dependent on several sound features other than accents, what would the listeners’ perception be modified when melodies (pitched sounds) or even harmonies are introduced to the patterns? Some research has gone in this direction based on Western music such as by Jones et al. (1982), but as far as I know, research has not yet examined this aspect in a non-Western or cross- cultural context. It again demonstrates the needs for and the importance of cognitive ethnomusicological studies, because culture, as shown in the current study, may be a decisive factor in temporal (and other) perceptions and lead to very different conclusions.

To test if the proposed interpretation of “metrical perception” is applicable across cultures, I suggest duplicating the current experiment with stimuli and participants of other cultures, such as musics and participants from African, Latin American, and some

Southeastern (e.g., Indonesian) traditions in which recurrent rhythmic cycles are frequently found as well. It may be interesting, too, to simply substitute the stimuli of

Middle-Eastern patterns with Indian ones and inquire if the result will be compatible with the result here. If findings from such studies align with the proposed interpretation here, it will be a major step forward in metrical understanding in the discourse of ethnomusicology, music theory, and music perception and cognition.

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Appendix A: List of Rhythmic Stimuli

Below is the complete list of rhythmic stimuli used in this study.

beat number pattern # pattern type 1 2 3 4 5 6 7 8 9 10 1 3_samai taer PT D T T 2 3_samai taer FT D T T 3 3_same tone PT T t T T 4 3_same tone FT T t T T 5 4_even beat PT D t T t 6 4_even beat FT D t T t 7 7_dawr hindi PT D T T D t t T tt 8 7_dawr hindi FT D T T D t t T tt 9 7_nawakht PT D t t T D (t)t T T 10 7_nawakht FT D t t T D (t)t T T 11 9_aqsaq PT D t T t D t T t t T 12 9_aqsaq FT D t T t D t T t t T 13 9_awnak turki PT D T T D t t T t t T t t 14 9_awnak turki FT D T T D t t T t t T t t 15 9_karsilama PT D t t T t t D t t T T T 16 9_karsilama FT D t t T t t D t t T T T 17 10_jurjuna PT D t t t T t t D t t T t t t t 18 10_jurjuna FT D t t t T t t D t t T t t t t 19 10_samai thaqil PT D t t t t T (t)t D D T t t t t 20 10_ samai thaqil FT D t t t t T (t)t D D T t t t t

D: lower-pitch accent T: higher-pitch accent t: non-accented stroke

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Appendix B: Experiment Questionnaire

Name: ______Today’s Date: ______

Year of Birth: ______

 General: 1. What is(are) the main culture(s) that define(s) your identity and influence(s) your upbringing experiences? (Eg. American, Italian, Indian, Turkish, Japanese, etc.) ______2. What types of music do your family of origin usually listen to? (Eg. country, jazz, western classical, Indian Classical, Chinese folk, etc.) ______

 Musical experiences: 3. What types of music do you listen to in your daily life? ______4. Are you a musician? (Y/N) ______(if your answer is “No,” go ahead to question #14 ) 5. Which instrument(s) do you play? ______

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6. What types of music playing have you been involved in? ______7. Have you received formal musical training in the above styles? (Eg. learning from a teacher/master or going to a music school) (Y/N) ______(if your answer is “No,” go ahead to question #9) 8. For how many years have you been trained? Specify the age range if you can. (then go ahead to question #11) ______9. Are you self-taught in this(these) musical style(s)? (Y/N) ______. If your answer is “Yes,” how have you learned them? ______10. For how many years have(had) you been learning the musical styles? Specify the age range if you can. ______11. Are you a performing musician? (Y/N) ______(If your answer is “No,” go ahead to question #14) 12. How frequently do you perform? ______13. In what locations and settings do you usually perform? ______14. Do you have any previous experiences of playing or listening to the Middle Eastern music? (Y/N) ______. If so, in what context was that? ______

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