Cortical microcircuit determination through global perturbation and sparse sampling in grid cells

Under modern interrogation, famously well-studied neural circuits such as that for orientation tuning in V1 are steadily giving up their secrets, but quite basic questions about connectivity and dynamics, including whether most computation is done by lateral processing or by selective feedforward summation, remain unresolved. We show here that grid cells offer a particularly rich opportunity for dissecting the mechanistic underpinnings of a cortical circuit, through a strategy based on global circuit perturbation combined with sparse neural recordings. The strategy is based on the theoretical insight that small perturbations of circuit activity will result in characteristic quantal shifts in the spatial tuning relationships between grid cells, which should be observable from multisingle unit recordings of a small subsample of the population. The predicted shifts differ qualitatively across candidate recurrent network mechanisms, and also distinguish between recurrent versus feedforward mechanisms. More generally, the proposed strategy demonstrates how sparse neural recordings coupled with global perturbation in the grid cell system can reveal much more about circuit mechanism as it relates to function than can full knowledge of network activity or of the synaptic connectivity matrix.