Speaker
Description
Targeted optogenetic perturbations are key to investigating functional roles of sub-populations within neural circuits, yet their effects in recurrent networks may be difficult to interpret. Previous work has
shown that optogenetic stimulation of excitatory cells in macaque motor cortex creates large perturbations of task-related activity, but has only subtle effects on ongoing or upcoming behaviour, or the future dynamical evolution of neural population activity. We show that such behaviour can be accounted for within a low-dimensional dynamical
system framework if the dynamics are nonnormal with a nullspace that is well-aligned with the optogenetic perturbation pattern. How might such alignment might arise? We hypothesize that circuit-level features such as E/I balance might contribute crucially. To evaluate this hypothesis from neural recordings, we develop a novel approach to fit a high-dimensional discrete-time balanced E/I network that
expresses the low-dimensional and smooth dynamics observed in the recorded population responses. We indeed find that balanced networks can naturally create the appropriate non-normal structure to generate robustness to perturbation, while retaining the expressive capacity to recapitulate movement-related dynamics. Ultimately, techniques to establish more explicit links between circuit-level properties and population-level dynamics will be necessary to link neural perturbations, which are delivered in circuit coordinates, to the dynamics of computations.
