Minimum squared-error, energy-constrained encoding by adaptive threshold models of neurons

Erik C. Johnson, Douglas L. Jones, Rama Ratnam

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

Abstract

In the nervous system, sensory neurons encode signals as a sequence of action potentials (spikes). However, spike generation is metabolically expensive. Achieving high coding fidelity may require a high spike rate. Here we propose that neurons achieve a trade-off by optimally timing spikes so that maximum fidelity is achieved for a given spike rate. The proposed neural encoder generates spikes which are reconstructed by a linear filter, with energy modeled as a constraint proportional to the average spike-rate. We develop expressions for the encoding error and derive the optimal parameters in the limit of high spike-firing rates. The energy-constrained neural encoder is compared with experimental spike-times from two sensory neurons, one cortical and one peripheral. The proposed energy-constrained neural encoder closely approximates the experimentally recorded spike-times, and the decoded experimental inputs are within 2dB of the predicted distortion-energy curve for both neurons.

Original languageEnglish (US)
Title of host publicationProceedings - 2015 IEEE International Symposium on Information Theory, ISIT 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1337-1341
Number of pages5
ISBN (Electronic)9781467377041
DOIs
StatePublished - Sep 28 2015
EventIEEE International Symposium on Information Theory, ISIT 2015 - Hong Kong, Hong Kong
Duration: Jun 14 2015Jun 19 2015

Publication series

NameIEEE International Symposium on Information Theory - Proceedings
Volume2015-June
ISSN (Print)2157-8095

Other

OtherIEEE International Symposium on Information Theory, ISIT 2015
CountryHong Kong
CityHong Kong
Period6/14/156/19/15

Keywords

  • Energy Constrained
  • Neural Decoding
  • Optimal Neural Coding

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Information Systems
  • Modeling and Simulation
  • Applied Mathematics

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  • Cite this

    Johnson, E. C., Jones, D. L., & Ratnam, R. (2015). Minimum squared-error, energy-constrained encoding by adaptive threshold models of neurons. In Proceedings - 2015 IEEE International Symposium on Information Theory, ISIT 2015 (pp. 1337-1341). [7282673] (IEEE International Symposium on Information Theory - Proceedings; Vol. 2015-June). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISIT.2015.7282673