Information content analysis for spike trains of neuron and neural networks

TAKEKAWA Takashi, ISOMURA Yoshikazu, FUKAI Tomoki

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

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.

Journal

IEICE technical report. Neurocomputing

IEICE technical report. Neurocomputing 111 (96), 1-2, 2011-06-16

The Institute of Electronics, Information and Communication Engineers

Keywords

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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