Mark Goldman, Ph.D.

Professor, University of California, Davis

Mark S. Goldman received a Ph.D. in physics from Harvard University in 2000 and did his postdoctoral work in theoretical neuroscience at the Massachusetts Institute of Technology. He was an assistant professor of physics and computational neuroscience at Wellesley College from 2003 to 2007 before moving to the University of California, Davis in 2008, where he is currently a professor in the Department of Neurobiology, Physiology and Behavior and the Department of Ophthalmology and Vision Science. Professor Goldman’s research uses mathematical modeling and computer simulations to address the cellular, synaptic and circuit mechanisms underlying neurobiological functions such as memory storage and motor control. His work has spanned problems ranging from cellular biophysics to neural coding and network dynamics. A major interest of his has been addressing the cellular and network mechanisms by which neural circuits can maintain a running total of signals (temporal integral) over time in a short-term memory buffer — this work spans scales and approaches ranging from the cellular biophysics of individual dendritic branches of neurons, to identifying circuit motifs subserving short-term memory and neural integration in cortical networks, and modeling whole-circuit-level dynamics of short-term memory storage in the eye movement control system of zebrafish. A more recent focus of his work has been on modeling how synaptic plasticity rules interact with recurrent circuit dynamics to mediate error-driven learning in the cerebellum and striato-cortical systems.

His service to the neuroscience community includes serving as an action editor for the Journal of Computational Neuroscience, review editor for Frontiers in Computational Neuroscience and as a former co-director of the Marine Biological Laboratory’s Methods in Computational Neuroscience Course. He is a former Alfred P. Sloan Research Fellow (2007) and was appointed a Howard Hughes Medical Institute Professor in 2014.

Current Project:

Plasticity of global brain dynamics: tunable neural integration

Neural Circuit Dynamics Underlying Sequence and Variability

Past Project:

Mechanisms of Context-Dependent Neural Integration and Short-Term Memory

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