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Hidden Assembly Dynamics and Correlated Neuronal Responses

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ICANN ’93 (ICANN 1993)

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Abstract

Oscillatory neuronal responses have been suspected to reveal assembly formation by synchronization. We analyse these data in terms of a hidden-state model, the parameters of which are estimated directly from experimental spike trains. The model characterizes the excitation dynamics of the network which is only stochastically reflected by the activity of the observed neurons. Our approach reproduces the observed spike dynamics and predicts the cross-correlations of units which belong to the same assembly. The application of our method to multi-unit activities from cat visual cortex reveals that for certain stimuli the recorded neurons indeed participate in a common dynamics, i.e. belong to the same assembly.

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Author information

Authors and Affiliations

  1. Institut für Theoretische Physik, Universität Frankfurt, Robert-Mayer-Str. 8, D-6000, Frankfurt/Main 11, Germany

    K. Pawelzik, J. Deppisch & T. Geisel

Authors
  1. K. Pawelzik
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  2. J. Deppisch
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  3. T. Geisel
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Editor information

Editors and Affiliations

  1. Dutch Foundation for Neural Networks, University of Nijmegen, Geert Grooteplein 21, 6525 EZ, Nijmegen, The Netherlands

    Stan Gielen  & Bert Kappen  & 

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© 1993 Springer-Verlag London Limited

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Pawelzik, K., Deppisch, J., Geisel, T. (1993). Hidden Assembly Dynamics and Correlated Neuronal Responses. In: Gielen, S., Kappen, B. (eds) ICANN ’93. ICANN 1993. Springer, London. https://doi.org/10.1007/978-1-4471-2063-6_36

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  • DOI: https://doi.org/10.1007/978-1-4471-2063-6_36

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  • Publisher Name: Springer, London

  • Print ISBN: 978-3-540-19839-0

  • Online ISBN: 978-1-4471-2063-6

  • eBook Packages: Springer Book Archive

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