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

Fingerprint

Adaptive Threshold
Threshold Model
Spike
Neurons
Neuron
Encoding
Energy
Encoder
Neurology
Fidelity
Linear Filter
Action Potential
Optimal Parameter
Timing
Coding
Trade-offs
Directly proportional

Keywords

  • Energy Constrained
  • Neural Decoding
  • Optimal Neural Coding

ASJC Scopus subject areas

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

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

Minimum squared-error, energy-constrained encoding by adaptive threshold models of neurons. / Johnson, Erik C.; Jones, Douglas L; Ratnam, Rama.

Proceedings - 2015 IEEE International Symposium on Information Theory, ISIT 2015. Institute of Electrical and Electronics Engineers Inc., 2015. p. 1337-1341 7282673 (IEEE International Symposium on Information Theory - Proceedings; Vol. 2015-June).

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

Johnson, EC, Jones, DL & 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., 7282673, IEEE International Symposium on Information Theory - Proceedings, vol. 2015-June, Institute of Electrical and Electronics Engineers Inc., pp. 1337-1341, IEEE International Symposium on Information Theory, ISIT 2015, Hong Kong, Hong Kong, 6/14/15. https://doi.org/10.1109/ISIT.2015.7282673
Johnson EC, Jones DL, Ratnam R. Minimum squared-error, energy-constrained encoding by adaptive threshold models of neurons. In Proceedings - 2015 IEEE International Symposium on Information Theory, ISIT 2015. Institute of Electrical and Electronics Engineers Inc. 2015. p. 1337-1341. 7282673. (IEEE International Symposium on Information Theory - Proceedings). https://doi.org/10.1109/ISIT.2015.7282673
Johnson, Erik C. ; Jones, Douglas L ; Ratnam, Rama. / Minimum squared-error, energy-constrained encoding by adaptive threshold models of neurons. Proceedings - 2015 IEEE International Symposium on Information Theory, ISIT 2015. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 1337-1341 (IEEE International Symposium on Information Theory - Proceedings).
@inproceedings{146f67e8e11d451bb38ecf3627159d45,
title = "Minimum squared-error, energy-constrained encoding by adaptive threshold models of neurons",
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.",
keywords = "Energy Constrained, Neural Decoding, Optimal Neural Coding",
author = "Johnson, {Erik C.} and Jones, {Douglas L} and Rama Ratnam",
year = "2015",
month = "9",
day = "28",
doi = "10.1109/ISIT.2015.7282673",
language = "English (US)",
series = "IEEE International Symposium on Information Theory - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1337--1341",
booktitle = "Proceedings - 2015 IEEE International Symposium on Information Theory, ISIT 2015",
address = "United States",

}

TY - GEN

T1 - Minimum squared-error, energy-constrained encoding by adaptive threshold models of neurons

AU - Johnson, Erik C.

AU - Jones, Douglas L

AU - Ratnam, Rama

PY - 2015/9/28

Y1 - 2015/9/28

N2 - 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.

AB - 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.

KW - Energy Constrained

KW - Neural Decoding

KW - Optimal Neural Coding

UR - http://www.scopus.com/inward/record.url?scp=84969769439&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84969769439&partnerID=8YFLogxK

U2 - 10.1109/ISIT.2015.7282673

DO - 10.1109/ISIT.2015.7282673

M3 - Conference contribution

AN - SCOPUS:84969769439

T3 - IEEE International Symposium on Information Theory - Proceedings

SP - 1337

EP - 1341

BT - Proceedings - 2015 IEEE International Symposium on Information Theory, ISIT 2015

PB - Institute of Electrical and Electronics Engineers Inc.

ER -