Dr. Large’s research areas include nonlinear dynamical systems, auditory neuroscience, and music psychology. He uses theoretical modeling in conjunction with behavioral, comparative, neurophysiological and neuroimaging techniques to understand how people respond to complex, temporally structured sequences of sound such as music and speech. He and his colleagues have pioneered the idea that attention is a dynamic, and inherently rhythmic process. He has applied these ideas to explain the rhythmic structure of music, and its interaction with brain dynamics. His current research projects include studies of driven nonlinear oscillator networks, nonlinear cochlear models, auditory brainstem neurodynamics, cortical dynamics of attention, perception of rhythm in music and speech, perception of tonality in music, auditory pattern recognition and learning, emotional communication in music, and rhythmic interactions in nonhuman primates.
Dr. Large directs the Music Dynamics Laboratory at University of Connecticut, where he is a Professor of Psychological Sciences and Professor of Physics. He is Associate Editor at Frontiers in Auditory Cognitive Neuroscience and Music Perception and he recently completed a three year term as President of the Society for Music Perception and Cognition. Dr. Large received his Ph.D. from The Ohio State University in 1994, and he did his postdoctoral work at University of Pennsylvania. He has published over 70 articles in journals such as Psychological Review, Physics, Journal of the Acoustical Society of America,Music Perception, and Journal of Computational Neuroscience and he has been awarded five patents. He is the recipient of numerous awards including a National Science Foundation CAREER Award and a Fulbright Visiting Chair in the Science and Technology of Music at McGill University.
Tichko, P., Kim, J. C., Large, E., & Loui, P. (2020). Integrating music‐based interventions with Gamma‐frequency stimulation: Implications for healthy ageing. European Journal of Neuroscience.
Farokhniaee, A., Almonte, F. V., Yelin, S., & Large, E. W. (2020). Entrainment of Weakly Coupled Canonical Oscillators with Applications in Gradient Frequency Neural Networks Using Approximating Analytical Methods. Mathematics, 8(8), 1312.
Roman, I. R., Roman, A. S., & Large, E. W. (2020). Hebbian learning with elasticity explains how the spontaneous motor tempo affects music performance synchronization. bioRxiv.
Roman, I. R., Washburn, A., Large, E. W., Chafe, C., & Fujioka, T. (2019). Delayed feedback embedded in perception-action coordination cycles results in anticipation behavior during synchronized rhythmic action: A dynamical systems approach. PLoS computational biology, 15(10), e1007371.
Tichko, P., & Large, E. W. (2019). Modeling infants’ perceptual narrowing to musical rhythms: neural oscillation and Hebbian plasticity. Annals of the New York Academy of Sciences, 1453(1), 125-139.
Lerud, K. D., Kim, J. C., Almonte, F. V., Carney, L. H., & Large, E. W. (2019). A canonical oscillator model of cochlear dynamics. Hearing research, 380, 100-107.