Talk Title: Biophysics for Neural Computation

Abstract

The biological implementation of cortical computation remains elusive. Remarkable recent progress in artificial neural systems has generated many important new insights into cortical dynamics, but connecting these observations to the underlying wetware of the brain has proven challenging. One key difference between artificial and biological systems is that brains are physical systems, operating under physical constraints, such as space and energy. As brains process information via ion channels, synapses, cells, and circuits, they must optimize for real-world spatial and energetic costs in parallel with computational performance. This disparity between artificial and biological systems has not been well-explored, despite its clear significance for understanding brain computation and how it goes awry in disease states. I will present work from a range of projects in our lab that address this concept of physical influences on cortical organization and function. These projects range across spatial scales, from network level to single synapses. They include our recent evidence for vectorized error signaling in cortical dendrites, multiple new mechanisms for adult cortical synaptic plasticity, and a formal modeling framework for evaluating how space and energy costs are balanced against computational demands in neural networks.

Bio

Mark Harnett studies the biophysical basis of cortical computation. His lab evaluates how different biological features, including ion channels, receptors, synapses, and membrane electrical properties, shape the information processing and learning capabilities of cortex. Mark joined the Department of Brain and Cognitive Sciences as faculty in 2015. He received his B.A. in Biology from Reed College in Portland, Oregon and his Ph.D. in Neuroscience from the University of Texas at Austin, and he did his postdoctoral research at the Howard Hughes Medical Institute’s Janelia Research Campus in Ashburn VA.

Zoom Webinar (for MIT Touchstone only): https://mit.zoom.us/j/95127361638