Direct neural perturbations reveal a dynamical mechanism for robust computation

Lea Duncker

Stanford University
Wednesday, November 2, 2022 at 12:00pm
Evans Hall Room 560 and via Zoom (see below to obtain Zoom link)

The rich repertoire of skilled mammalian behavior is the product of neural circuits that generate robust and flexible patterns of activity distributed across populations of neurons. Decades of associative studies have linked many behaviors to specific patterns of population activity, but association alone cannot reveal the dynamical mechanisms that shape those patterns. Are local neural circuits high-dimensional dynamical reservoirs able to generate arbitrary superpositions of patterns with appropriate excitation? Or might circuit dynamics be shaped in response to behavioral context so as to generate only the low-dimensional patterns needed for the task at hand? Here, we address these questions for primate motor cortex activity associated with rapid reaching movements, by delivering optogenetic and electrical microstimulation perturbations during behavior. Computational models that capture the dynamical effects of these perturbations show that motor cortical activity during reaching is shaped by a self-contained low-dimensional dynamical system. Combining a novel analytic approach that relates measured activity to dynamical models of excitatory and inhibitory neurons with theoretical analysis of such systems, we find that the dynamical subspace is oriented so as to be robust to strong non-normal amplification within cortical circuits, and that stimulation only perturbs behavior to the extent that it alters activity within this subspace. Our results resolve long-standing questions about the dynamical structure of cortical activity associated with movement, and point the way to the dynamical perturbation studies needed to understand how neural circuits throughout the brain generate complex behavior.

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