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Circuitry and the Classification of Simple and Complex Cells in V1

Laboratory for Intelligent Imaging and Neural Computing, Department of Biomedical Engineering, Columbia University, New York, New York

Submitted 3 April 2006; accepted in final form 15 June 2006

Based on a large-scale neural network model of striate cortex (V1), we present a simulation study of extra- and intracellular response modulations for drifting and contrast reversal grating stimuli. Specifically, we study the dependency of these modulations on the neural circuitry. We find that the frequently used ratio of the first harmonic to the mean response to classify simple and complex cells is highly insensitive to circuitry. Limited experimental sample size for the distribution of this measure makes it unsuitable for distinguishing whether the dichotomy of simple and complex cells originates from distinct LGN axon connectivity and/or local circuitry in V1. We show that a possible useful measure in this respect is the ratio of the intracellular second- to first-harmonic response for contrast reversal gratings. This measure is highly sensitive to neural circuitry and its distribution can be sampled with sufficient accuracy from a limited amount of experimental data. Further, the distribution of this measure is qualitatively similar to that of the subfield correlation coefficient, although it is more robust and easier to obtain experimentally.

This article has been cited by other articles:

				J. Wielaard and P. Sajda Dependence of Response Properties on Sparse Connectivity in a Spiking Neuron Model of the Lateral Geniculate Nucleus J Neurophysiol, December 1, 2007; 98(6): 3292 - 3308. [Abstract] [Full Text] [PDF]