ML Anthology

Computing with Self-Excitatory Cliques: A Model and an Application to Hyperacuity-Scale Computation in Visual Cortex

Steven W. Zucker, Douglas Miller
NeCo 1999 pp. 21-66
doi:10.1162/089976699300016782 /neco/1999/zucker1999neco-computing/

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 efficent; (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.

NeCo Semantic Scholar

Cite

Text

Zucker and Miller. "Computing with Self-Excitatory Cliques: A Model and an Application to Hyperacuity-Scale Computation in Visual Cortex." Neural Computation, 1999. doi:10.1162/089976699300016782

Markdown

[Zucker and Miller. "Computing with Self-Excitatory Cliques: A Model and an Application to Hyperacuity-Scale Computation in Visual Cortex." Neural Computation, 1999.](https://mlanthology.org/neco/1999/zucker1999neco-computing/) doi:10.1162/089976699300016782

BibTeX

@article{zucker1999neco-computing,
  title     = {{Computing with Self-Excitatory Cliques: A Model and an Application to Hyperacuity-Scale Computation in Visual Cortex}},
  author    = {Zucker, Steven W. and Miller, Douglas},
  journal   = {Neural Computation},
  year      = {1999},
  pages     = {21-66},
  doi       = {10.1162/089976699300016782},
  volume    = {11},
  url       = {https://mlanthology.org/neco/1999/zucker1999neco-computing/}
}