Marc Velasco

Ph.D. Student,

Complex Systems & Brain Sciences, Music Dynamics Laboratory,
Florida Atlantic University.

Current Researches and Interests: 

CORTICAL DYNAMICS OF RHYTHM PERCEPTION

The experience of musical rhythm is remarkable in part because the perception of periodicities, namely pulse and meter, can arise from stimuli that are not periodic. One possible function of such a transformation is to enable attentional and behavioral synchrony among individuals through perception of a common abstract temporal structure. Thus, understanding the brain processes that underlie rhythm is fundamental to explaining musical behavior. Here, we ask whether a model of neural resonance can account for important aspects of human rhythm perception, rhythmic attending and perception-action coordination. We have derived a canonical model of neural oscillation and used it to define a gradient frequency neural oscillator network (GFNN). A GFNN is a one dimensional network of neural oscillators, tuned to different natural frequencies, and arrayed along a frequency gradient. Such networks are conceptually similar to banks of bandpass filters, except that the resonating units are nonlinear rather than linear. We are stimulating the networks with a variety of rhythms from simple isochronous sequences to complex rhythmic patterns. We are asking how well the behavior of the network matches certain well-known features of human behavior, and also comparing the predictions of the nonlinear model with those of linear model. We are running experiments to test the predictions of our models.

Marc is the co-author of the Circular Statistics Toolbox, and he collaborating on the development of a computer toolbox for signal analysis by gradient frequency nonlinear resonator networks.

Publications & Presentations: 

Large, E. W., Almonte, F. & Velasco, M. (2010). A canonical model for gradient frequency neural networks. Physica D, 239, 905-911.

Velasco, M. & Large, E. W.  (2010). Entrainment to complex rhythms: Tests of a neural model. Society for Neuroscience Abstracts, 36, 324.3.

Large, E. W. & Velasco, M. J. (2010). Neural oscillation: Implications for pulse and meter in complex rhythms, Podium Presentation at the West Coast Sequencing and Timing Workshop, UC Santa Barbara, Santa Barbara, CA, Jan 16.

Large, E. W. & Velasco, M. J. (2009). Modeling pulse and meter as neural oscillation, Podium Presentation at the Biennial Conference of the Society for Music Perception and Cognition, Indianapolis, IN, Aug 3-7.

Velasco, M. & Large, E. W. (2008). Time-frequency transformation by networks of neural oscillators: Implications for musical structure, Journal of the Acoustical Society of America, 124, (4), 2432.

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