Bridging Rate Coding and Temporal Spike Coding by Effect of Noise

Naoki Masuda and Kazuyuki Aihara
Phys. Rev. Lett. 88, 248101 – Published 30 May 2002
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Abstract

It is controversial whether temporal spike coding or rate coding is dominant in the information processing of the brain. We show by a two-layered neural network model with noise that, when noise is small, cortical neurons fire synchronously and intervals of synchronous firing robustly encode the signal information, but that the neurons desynchronize with moderately strong noise to encode waveforms of the signal more accurately. Further increase of noise just deteriorates the encoding. A positive role of noise in the brain is suggested in a meaning different from stochastic resonance, coherence resonance, and deterministic chaos.

  • Received 20 November 2001

DOI:https://doi.org/10.1103/PhysRevLett.88.248101

©2002 American Physical Society

Authors & Affiliations

Naoki Masuda1,* and Kazuyuki Aihara1,2

  • 1Department of Mathematical Engineering and Information Physics, Graduate School of Engineering, the University of Tokyo, 7-3-1, Bunkyo-ku, Tokyo, 113-8656, Japan
  • 2Core Research for Evolutional Science and Technology, Japan Science and Technology Corporation, 4-1-8, Hon-cho, Kawaguchi, Saitama, 332-0012, Japan

  • *Email address: masuda@sat.t.u-tokyo.ac.jp

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Issue

Vol. 88, Iss. 24 — 17 June 2002

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