Computing with self-excitatory cliques: A model and an application to hyperacuity-scale computation in visual cortex.

D A Miller; S W Zucker

doi:10.1162/089976699300016782

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Computing with self-excitatory cliques: A model and an application to hyperacuity-scale computation in visual cortex.

D A Miller·S W Zucker

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Abstract

We present a model of visual computation based on tightly inter-connected cliques of pyramidal cells. It leads to a formal theory of cell assemblies, a specific relationship between correlated firing patterns and abstract functionality, and a direct calculation relating estimates of cortical cell counts to orientation hyperacuity. Our network architecture is unique in that (1) it supports a mode of computation that is both reliable and efficient; (2) the current-spike relations are modeled as an analog dynamical system in which the requisite computations can take place on the time scale required for an early stage of visual processing; and (3) the dynamics are triggered by the spatiotemporal response of cortical cells. This final point could explain why moving stimuli improve vernier sensitivity.

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Models, Neurological Neural Networks, Computer Visual Acuity Visual Cortex Journal Article Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S.Review

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D A Miller, S W Zucker. 1999-01-01. Computing with self-excitatory cliques: A model and an application to hyperacuity-scale computation in visual cortex.. https://doi.org/10.1162/089976699300016782

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