Topological insights into the neural basis of flexible behavior
Marlene Cohen, University of Pittsburgh
Tuesday September 14, 12-1pm
Zoom Link: https://mcgill.zoom.us/j/85428056343
Abstract: It is widely accepted that there is an inextricable link between the function of a neural circuit, the biological mechanisms that can modulate the computations it performs, and the flexible behavior it produces. However, the nature of that link has proven elusive because we lack a framework that is comprehensive yet general enough to simultaneously explain neural computations, biological mechanisms, and behavior. I will talk about our new work showing that topological data analysis (TDA), an emerging field of mathematics and data science that is typically used very differently to characterize large data sets in mostly non-neuroscientific fields, provides that necessary bridge between different levels of experimental and theoretical neuroscientific study. We demonstrate that cognitive processes like attention change the topological description of the shared activity of groups of neurons in visual cortex (specifically, the extent to which trial-to-trial fluctuations in responses to the same stimulus are correlated, which is known to depend on cognition). These topological changes provide uniquely strong constraints on a mechanistic model, explain the concomitant behavioral changes, and, via a link with network control theory, reveal that visual attention entails a tradeoff between improving the ability of the network to respond to subtle changes in the visual stimulus and increasing the chance that the subject will stray off task (increasing the lapse rate). In addition to these discoveries about the biological and computational mechanisms by which cognition affects behavior, our study provides a blueprint for novel uses of TDA to understand the huge variety of normal behavioral processes and disorders of the nervous system that involve the shared activity of large groups of neurons.