Informational limits of neural circuits

Lav R. Varshney, Devavrat Shah

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

With the growing amount of connectome data being gathered, it behooves us to develop systems-theoretic methods to analyze this data so as to provide insights into the function of neuronal circuits. Here, we develop models and compute capacities for gap junction synapses. We develop information-theoretic lower bounds on computation speed arising from limitations of anatomical connectivity and physical noise. For the nematode Caenorhabditis elegans, these bounds are predictive of biological timescales. Moreover, the hub-and-spoke architecture of C. elegans functional subcircuits are optimal under constraint on number of synapses.

Original languageEnglish (US)
Title of host publication2011 49th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2011
Pages1757-1763
Number of pages7
DOIs
StatePublished - 2011
Externally publishedYes
Event2011 49th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2011 - Monticello, IL, United States
Duration: Sep 28 2011Sep 30 2011

Publication series

Name2011 49th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2011

Other

Other2011 49th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2011
CountryUnited States
CityMonticello, IL
Period9/28/119/30/11

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Control and Systems Engineering

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