UC Merced

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.