A population approach to cortical dynamics with an application to orientation tuning

A typical functional region in cortex contains thousands of neurons, theref ore direct neuronal simulation of the dynamics of such a region necessarily involves massive computation. A recent efficient alternative formulation i s in terms of kinetic equations that describe the collective activity of th e whole population of similar neurons. A previous paper has shown that thes e equations produce results that agree well with detailed direct simulation s. Here we illustrate the power of this new technique by applying it to the investigation of the effect of recurrent connections upon the dynamics of orientation tuning in the visual cortex. Our equations express the kinetic counterpart of the hypercolumn model from which Somers et al (Somers D, Nel son S and Sur M 1995 J. Neurosci. 15 5448-65) computed steady-state cortica l responses to static stimuli by direct simulation. We confirm their static results. Our method presents the opportunity to simulate the data-intensiv e dynamical experiments of Ringach et al (Ringach D, Hawken M and Shapley R 1997 Nature 387 281-4), in which 60 randomly oriented stimuli were present ed each second for 15 min, to gather adequate statistics of responses to mu ltiple presentations. Without readjustment of the previously deiined parame ters, our simulations yield substantial agreement with the experimental res ults. Our calculations suggest that differences in the experimental dynamic al responses of cells in different cortical layers originate from differenc es in their recurrent connections with other cells. Thus our method of effi cient simulation furnishes a variety of information that is not available f rom experiment alone.