Shaul Druckmann

Stanford University
Session: Building a framework for understanding circuit function


Relating circuit dynamics to computation: robustness and dimension-specific computation in cortical dynamics

Neural dynamics represent the hard-to-interpret substrate of circuit computations. Advances in large-scale recordings have highlighted the sheer spatiotemporal complexity of circuit dynamics, portraying in detail the difficulty of interpreting such dynamics and relating it to computation.

Considering motor preparatory activity in a delayed response task we utilized neural recordings performed simultaneously with optogenetic perturbations to probe circuit dynamics. First, we revealed a remarkable robustness in the detailed evolution of certain dimensions of the population activity, beyond what was thought to be the case experimentally and theoretically. Second, the robust dimension in activity space carries nearly all of the decodable behavioral information whereas other non-robust dimensions contained nearly no decodable information, consistent with the circuit being setup to make informative dimensions stiff, i.e., resistive to perturbations, leaving uninformative dimensions sloppy, i.e., sensitive to perturbations. Third, our data suggests that this stability arises from the interaction of multiple brain areas, namely the two hemispheres. Finally, we discuss our findings in the more general context of understanding neural computation by population recordings.