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Strongly maximal intersection-complete neural codes on grids are convex

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  • Williams, Robert

Abstract

The brain encodes spatial structure through a combinatorial code of neural activity. Experiments suggest such codes correspond to convex areas of the subject’s environment. We present an intrinsic condition that implies a neural code may correspond to a collection of convex sets and give a bound on the minimal dimension underlying such a realization.

Suggested Citation

  • Williams, Robert, 2018. "Strongly maximal intersection-complete neural codes on grids are convex," Applied Mathematics and Computation, Elsevier, vol. 336(C), pages 162-175.
    • Handle: RePEc:eee:apmaco:v:336:y:2018:i:c:p:162-175
    DOI: 10.1016/j.amc.2018.04.064
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    References listed on IDEAS

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    1. Carina Curto & Vladimir Itskov, 2008. "Cell Groups Reveal Structure of Stimulus Space," PLOS Computational Biology, Public Library of Science, vol. 4(10), pages 1-13, October.
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