Topic: multi-task computation

Cortical neuronal networks exhibit a rich dynamical repertoire and are capable of performing many different computations, for instance the generation of multiple distinct dynamical patterns in motor cortex. However, we do not know what connectivity structures support this capability, nor the mechanism for selecting among the dynamics required for different tasks. We develop an analytical theory describing a network model capable of multi-task computation, where the connectivity is generated as a sum over a large number of low-rank matrices, each of which is specialized to perform one low-dimen