Computational modeling of orientation tuning dynamics in monkey primary visual cortex

In the primate visual pathway, orientation tuning of neurons is first obser ved in the primary visual cortex. The LGN cells that comprise the thalamic input to V1 are not orientation tuned, but some yl neurons are quite select ive. Two main classes of theoretical models have been offered to explain or ientation selectivity: feedforward models, in which inputs from spatially a ligned LGN cells are summed together by one cortical neuron; and feedback m odels, in which an initial weak orientation bias due to convergent LGN inpu t is sharpened and amplified by intracortical feedback. Recent data on the dynamics of orientation tuning, obtained by a cross-correlation technique, may help to distinguish between these classes of models. To test this possi bility, we simulated the measurement of orientation tuning dynamics on vari ous receptive field models, including a simple Hubel-Wiesel type feedforwar d model: a linear spatiotemporal filter followed by an integrate-and-fire s pike generator The computational study reveals that simple feedforward mode ls may account for some aspects of the experimental data but fail to explai n many salient features of orientation tuning dynamics in V1 cells. A simpl e feedback model of interacting cells is also considered. This model is suc cessful in explaining the appearance of Mexican-hat orientation profiles, b ut other features of the data continue to be unexplained.