Neural field description of state-dependent visual receptive field changes

Receptive elds (RFs) in V1 were found to be wider during synchronized than during non-synchronized EEG states, where, in addition, they can sharpen over time. These changes were suggested to be mainly driven by state-dependent LGN-ring patterns. Here we employ a neural eld approach to analytically describe the changing cortical RFs. For pure feedforward networks expressions for spatio-temporal RF are given, as well as expected time-courses of RF-sizes. It turns out that, although the RF-size depends on time, the width of the underlying spatial potential proole is constant. The analytically derived point-spread functions are tted to experimental data. Fit results provide estimates for model parameters consistent with literature data and support the hypothesis that the observed RF-sharpening is mainly LGN-driven.