Event:

The recurrent nature of the neural substrate can be directly related to the receptive-field view of neurons’ activity only in a small number of well-studied circuits. We addressed this problem in a general nonlinear network model by extending our recent results for networks with cell-type-specific connectivity (Aljadeff et al., 2015). Given the connectivity structure we predict the network’s leading principal components in the space of neurons’ autocorrelation functions, providing a direct link between the structure and functional characteristics such as receptive-field symmetries, size, dimensionality and overlap.
Joint work with David Renfrew (UCLA) and Tatyana Sharpee (Salk)