Spike count distributions, factorizability, and contextual effects in area V1.
Neural models of contextual integration typically incorporate a mean firing rate representation. We examine representation of the full spike count distribution, and its usefulness in explaining contextual integration of color stimuli in primary visual cortex. Specifically, we demonstrate that a factorizable model conditioned on the number of spikes can account for both the onset and sustained portions of the response. We also consider a simplified factorizable model that parametrizes the mean of a Gaussian distribution and incorporates a logistic nonlinearity. The model can account for the sustained response but does not fair as well in accounting for onset nonlinearities. We discuss implications for neural coding.
Howard Hughes Medical Institute, The Salk Institute for Biological Sciences, Computational Neurobiology Lab, 10010 North Torrey Pines Road, La Jolla, CA 92037, USA.
Odelia
O
Schwartz
Javier R
JR
Movellan
Thomas
T
Wachtler
Thomas D
TD
Albright
Terrence J
TJ
Sejnowski