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This article is part of the supplement: Twentieth Annual Computational Neuroscience Meeting: CNS*2011

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Theory of neural communication based on spatio-temporal coding

Myoung Won Cho1* and Moo Young Choi2

Author Affiliations

1 Korea Institute for Advanced Study, Seoul 130-722, Korea

2 Department of Physics and Astronomy and Center for Theoretical Physics, Seoul National University, Seoul 151-747, Korea

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BMC Neuroscience 2011, 12(Suppl 1):P38  doi:10.1186/1471-2202-12-S1-P38

The electronic version of this article is the complete one and can be found online at:

Published:18 July 2011

© 2011 Won Cho and Young Choi; licensee BioMed Central Ltd.

This is an open access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Poster presentation

Pattern coding is a general concept for neural coding, which indicates that the objective meaning of information can be represented by spatio-temporal firing patterns of a group of neurons [1]. We introduce a feasible way through which spatio-temporal firing patterns represent complex information systematically. Provided that neural codes represent features in a vector space, neural communication channels can be characterized by independent pattern components constituting basis functions in the Hilbert space. Specific applied forms of the method, depending on the choice of basis functions, reduce to the traditional coding schemes, including rate coding, temporal coding, correlation coding, independent-spike coding, population coding, phase coding, and so on. In addition, it is suggested that the ordinary neural code in the brain might take a more elaborate form, in such a way that neural networks can send or receive complex information effectively and robustly through mutable spike trains. We discuss corresponding statistics of neural codes based on the theory. Finally, we present the scheme of a cortical module as the processing unit of communication and computation based on spatio-temporal coding. It may also be applied to modelling the stimulus-response of cortical neurons.


We present a theory as to how neural modules communicate with each other effectively via spatio-temporal firing patterns, and propose, based on the theory, how to phrase neural codes from observed firing patterns and how to model the stimulus-response relationship for cortical neurons.


This work was supported by NAP of Korea Research Council of Fundamental Science & Technology and by NRF through the BSR program.


  1. Fujii H, Ito H, Ichinose K, Tsukada M: Dynamical cell assembly hypothesis - theoretical possibility of spatio-temporal coding in the cortex.

    Neural Networks 1996, 9:1303-1350. PubMed Abstract | Publisher Full Text OpenURL