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Rhythms at Small and Large Scales: the Neural Mechanisms of Rhythm Perception and the Recurrence Dynamics of Large Group Interaction

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Recognizing that understanding the full scope of human cognition and behavior is intractable for any one discipline, the field of cognitive science has embraced the approaches and theoretical background of a diversity of fields, commonly listed as: philosophy, linguistics, anthropology, neuroscience, artificial intelligence, and psychology. This dissertation takes a similarly diverse approach to the study of music cognition and social interaction. In the first chapter, I review major theories in the neuroscience of musical rhythm perception. In the second, I conduct an experiment to determine how electrophysiological responses to musical rhythm are impacted by a brain stimulation method that down-regulates target regions of the brain. In the third chapter, I highlight how social interaction might involve coordination from low-level physiological signals up to high-level movement and acoustic signals that can be measured at the individual and group levels. In chapter four, I present a natural experiment applying nonlinear statistical analysis methods to acoustic data generated by a musical ensemble, identifying differing recurrence patterns dependent upon their mode of interaction. In chapter five, I extend these methods to a less scripted social interaction through analyzing the acoustic data generated by crowd sounds at a collegiate basketball game. This dissertation presents theoretical and experimental work spanning sensorimotor neuroscience, coordination dynamics, and complex systems. This work is intended to showcase a multiscale approach to the understanding of human cognition, applying multidisciplinary tools to questions within domains of music and social cognition.

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