Information content analysis for spike trains of neuron and neural networks

Bibliographic Information

Other Title
  • 神経細胞および神経細胞集団の発火時系列に対する情報量解析

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Abstract

Traditionally, firing rates are considered informative signals represented by action potentials, and compared with observed behavioral or perceptual phenomenon. However, it is possible that the detailed temporal information of action potentials also contains important signals. Recently, many people attempt to understand how particular observed signal can be predicted by spike trains using supervised learning. In this work, we apply a unsupervised learning method, kernel principle component analysis methods, for extracting information from single- or multi-neuron spike trains and seek the most informative decoding scheme only using spike trains.

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Details 詳細情報について

  • CRID
    1573387451834179456
  • NII Article ID
    110008746481
  • NII Book ID
    AN10091178
  • Text Lang
    ja
  • Data Source
    • CiNii Articles

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