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A neuronal network model of primary visual cortex explains spatial frequency selectivity

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Abstract

We address how spatial frequency selectivity arises in Macaque primary visual cortex (V1) by simulating V1 with a large-scale network model consisting of O(104) excitatory and inhibitory integrate-and-fire neurons with realistic synaptic conductances. The new model introduces variability of the widths of subregions in V1 neuron receptive fields. As a consequence different model V1 neurons prefer different spatial frequencies. The model cortex has distributions of spatial frequency selectivity and of preference that resemble experimental findings from the real V1. Two main sources of spatial frequency selectivity in the model are the spatial arrangement of feedforward excitation, and cortical nonlinear suppression, a result of cortical inhibition.

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Acknowledgements

This work was supported by a grant from the Swartz Foundation, and by grants from the National Eye Institute R01EY-01472 and T32EY-07158. Thanks to Drs. Dajun Xing, Patrick Williams, and Chun-I Yeh for helpful comments on the manuscript.

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Authors and Affiliations

  1. Courant Institute of Mathematical Sciences, New York University, 251 Mercer Street, New York, NY, 10012, USA

    Wei Zhu & Michael Shelley

  2. Center for Neural Science, New York University, 4 Washington Place, New York, NY, 10003, USA

    Robert Shapley

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  1. Wei Zhu
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  2. Michael Shelley
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Correspondence to Wei Zhu.

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Action Editor: Jonathan D. Victor

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Zhu, W., Shelley, M. & Shapley, R. A neuronal network model of primary visual cortex explains spatial frequency selectivity. J Comput Neurosci 26, 271–287 (2009). https://doi.org/10.1007/s10827-008-0110-x

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  • DOI: https://doi.org/10.1007/s10827-008-0110-x

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