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Classification of the spike sequences by distinguishing their sources of temporal correlations

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Abstract

Irregular spike sequences of the cerebral cortex in vivo have been observed in numerous previous studies. These spike sequences generally differ from an entirely random sequence, and exhibit temporal correlations. There are at least two possible sources producing the temporal correlations: (1) temporal correlations of the incoming synaptic inputs; (2) a neuronal integration mechanism. The temporal correlation of the neuronal output is produced by (1) or (2) or a mixture of these. In this article, we propose an algorithm that distinguishes the sources of the temporal correlations of spike sequences. The statistical characteristics of the spike sequences play a key role in this algorithm, which helps to classify the spike sequences by discriminating between their sources of temporal correlations.

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Authors and Affiliations

  1. Department of Mathematical Informatics, Graduate School of Information Science and Technology, University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo, 153-8505, Japan

    Kantaro Fujiwara & Kazuyuki Aihara

  2. Institute of Industrial Science, University of Tokyo, and ERATO, JST, Tokyo, Japan

    Kazuyuki Aihara

Authors
  1. Kantaro Fujiwara
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  2. Kazuyuki Aihara
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Corresponding author

Correspondence to Kantaro Fujiwara.

Additional information

This work was presented in part at the 11th International Symposium on Artificial Life and Robotics, Oita, Japan, January 23–25, 2006

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Cite this article

Fujiwara, K., Aihara, K. Classification of the spike sequences by distinguishing their sources of temporal correlations. Artif Life Robotics 11, 167–170 (2007). https://doi.org/10.1007/s10015-007-0423-2

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  • DOI: https://doi.org/10.1007/s10015-007-0423-2

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