Effects of noise correlations on population coding

Keiji Miura

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

2 Citations (Scopus)

Abstract

Neural responses show trial-to-trial variability (=noise) even if the same sensory stimulus is presented. Therefore the brain is considered to average and reduce the noises in order to obtain accurate sensory representations. However, Zohary et al. (1994) theoretically showed that the noises cannot be reduced when inter-neuronal correlations in noises, if any, exist in the simulation of a simple mathematical model. Here we analyze the effects of noise correlations on population coding in extended, but still simple, mathematical models.

Original languageEnglish
Title of host publication6th International Conference on Soft Computing and Intelligent Systems, and 13th International Symposium on Advanced Intelligence Systems, SCIS/ISIS 2012
Pages1072-1075
Number of pages4
DOIs
Publication statusPublished - 2012 Dec 1
Event2012 Joint 6th International Conference on Soft Computing and Intelligent Systems, SCIS 2012 and 13th International Symposium on Advanced Intelligence Systems, ISIS 2012 - Kobe, Japan
Duration: 2012 Nov 202012 Nov 24

Publication series

Name6th International Conference on Soft Computing and Intelligent Systems, and 13th International Symposium on Advanced Intelligence Systems, SCIS/ISIS 2012

Other

Other2012 Joint 6th International Conference on Soft Computing and Intelligent Systems, SCIS 2012 and 13th International Symposium on Advanced Intelligence Systems, ISIS 2012
CountryJapan
CityKobe
Period12/11/2012/11/24

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software

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