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Difficulty of singularity in population coding.

Authors
  • Amari, Shun-ichi
  • Nakahara, Hiroyuki
Type
Published Article
Journal
Neural computation
Publication Date
Apr 01, 2005
Volume
17
Issue
4
Pages
839–858
Identifiers
PMID: 15829091
Source
Medline
License
Unknown

Abstract

Fisher information has been used to analyze the accuracy of neural population coding. This works well when the Fisher information does not degenerate, but when two stimuli are presented to a population of neurons, a singular structure emerges by their mutual interactions. In this case, the Fisher information matrix degenerates, and the regularity condition ensuring the Cramér-Rao paradigm of statistics is violated. An animal shows pathological behavior in such a situation. We present a novel method of statistical analysis to understand information in population coding in which algebraic singularity plays a major role. The method elucidates the nature of the pathological case by calculating the Fisher information. We then suggest that synchronous firing can resolve singularity and show a method of analyzing the binding problem in terms of the Fisher information. Our method integrates a variety of disciplines in population coding, such as nonregular statistics, Bayesian statistics, singularity in algebraic geometry, and synchronous firing, under the theme of Fisher information.

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