Entrainment of cortical rhythms to acoustic rhythms has been hypothesized to be the neural correlate of pulse and meter perception in music. Dynamic attending theory first proposed synchronization of endogenous perceptual rhythms nearly 40 years ago, but only recently has the pivotal role of neural synchrony been demonstrated. Significant progress has since been made in understanding the role of neural oscillations and the neural structures that support synchronized responses to musical rhythm. Synchronized neural activity has been observed in auditory and motor networks, and has been linked with attentional allocation and movement coordination. Here we describe a neurodynamic model that shows how self-organization of oscillations in interacting sensory and motor networks could be responsible for the formation of the pulse percept in complex rhythms. In a pulse synchronization study, we test the model's key prediction that pulse can be perceived at a frequency for which no spectral energy is present in the amplitude envelope of the acoustic rhythm. The result shows that participants perceive the pulse at the theoretically predicted frequency. This model is one of the few consistent with neurophysiological evidence on the role of neural oscillation, and it explains a phenomenon that other computational models fail to explain. Because it is based on a canonical model, the predictions hold for an entire family of dynamical systems, not only a specific one. Thus, this model provides a theoretical link between oscillatory neurodynamics and the induction of pulse and meter in musical rhythm.

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Studies of pulse perception in rhythms often ask what periodicity describes the pulse, e.g., tempo identification. In studies of pulse attribution, irregular rhythmic sequences are rated for the degree to which a pulse percept is elicited, if at all. Here, we investigate how a resonance approach to pulse perception may explain the reduction in pulse attribution ratings for jittered sequences while also predicting perceived tempo. We use a signal processing approach to predict perceptual ratings and behavioral performance measures (i.e., tapping data). Measures of resonance are evaluated using both FFT and a network of neural oscillators. The stimuli were isochronous sequences modified with varying levels of pseudorandom Kolakoski jitter. In separate blocks, participants were asked to provide pulse attribution judgments and to tap at the pulse rate. As levels of jitter increased, pulse attribution ratings decreased and participants tapped periodically at the mean sequence rate. At certain high levels of jitter, pulse attribution ratings increased and participants entrained at a new tapping rate. Resonance measures account for both mean tapping rate and pulse attribution ratings, suggesting that these two behavioral measures may be different aspects of the same resonant phenomenon.

A growing body of evidence is consistent with the possibility of nonlinear oscillation in both the peripheral and central auditory nervous systems. This talk will introduce a model of nonlinear time-frequency transformation via an array of neural oscillators, each tuned to a distinct frequency, organized along a frequency gradient. Transformation of sound stimuli by neural oscillators is characterized. Predictions about general properties of nonlinear time-frequency transformation, such as frequency detuning and higher-order resonance, are derived. The model is consistent with nonlinear resonance approaches to pitch perception. The perception of tonality is predicted as a global pattern of resonance regions at small integer ratio frequency relationships. Neural oscillation provides a substantive potentially universal principle underlying the basic materials of music, namely, pitch and tonality. [Work supported by AFOSR FA9550-07-C0095.]