Neural field model of receptive field restructuring in primary visual cortex

Receptive fields (RF) in the visual cortex can change their size depending on the state of the individual. This reflects a changing visual resolution according to different demands on information processing during drowsiness. So far, however, the possible mechanisms that underlie these size changes have not been tested rigorously. Only qualitatively has it been suggested t hat state-dependent lateral geniculate nucleus (LGN) firing patterns (burst versus tonic firing) are mainly responsible for the observed cortical rece ptive field restructuring. Here, we employ a neural field approach to descr ibe the changes of cortical RF properties analytically. Expressions to desc ribe the spatiotemporal receptive fields are given for pure feedforward net works. The model predicts that visual latencies increase nonlinearly with t he distance of the stimulus location from the RF center. RF restructuring e ffects are faithfully reproduced. Despite the changing RF sizes, the model demonstrates that the width of the spatial membrane potential profile (as m easured by the variances of a gaussian) remains constant in cortex. In cont rast, it is shown for recurrent networks that both the RF width and the wid th of the membrane potential profile generically depend on time and can eve n increase if lateral cortical excitatory connections extend further than f ibers from LGN to cortex. In order to differentiate between a feedforward a nd a recurrent mechanism causing the experimental RF changes, we fitted the data to the analytically derived point-spread functions. Results of the fi ts provide estimates for model parameters consistent with the literature da ta and support the hypothesis that the observed RF sharpening is indeed mai nly driven by input from LGN, not by recurrent intracortical connections.