Identifying Oscillatory and Stochastic Neuronal Behavior with High Temporal Precision in Macaque Monkey Visual Cortex

  • U. Ernst
  • A. Kreiter
  • K. Pawelzik
  • T. Geisel

Abstract

We characterize the network dynamics underlying multi-unit activities from area MT of macaque monkey in terms of a hidden markov model (HMM) and compare our results to those previously obtained from cat visual cortex. We find that the collective dynamics acts like a stochastic oscillator with a broad range of frequencies. Oscillatory and stochastic periods in the spike trains are detected with high temporal precision, and synchronous network events are identified and localized.

Keywords

Hide Markov Model Spike Train Renewal Process Macaque Monkey Synchronous State 
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References

  1. [1]
    A. Kreiter and W. Singer, Oscillatory neuronal responses in the visual cortex of the awake macaque monkey, Europ. J. Neurosci., 4, 369 (1992).CrossRefGoogle Scholar
  2. [2]
    J. Deppisch, K. Pawelzik, and T. Geisel, Uncovering the synchronization dynamics from correlated neuronal activity quantifies assembly formation, Biol. Cyb. 71, 387 (1994).CrossRefGoogle Scholar
  3. [3]
    L.E. Baum and T. Petrie, Statistical inference for probabilistic functions of finite state Markov chains, Ann. Math. Stat. 37, 1554 (1966).CrossRefGoogle Scholar
  4. [4]
    J. Deppisch, H.-U. Bauer, T.B. Schillen, R. König, K. Pawelzik, and T. Geisel, Alternating oscillatory and stochastic states in a network of spiking neurons, Network 4, 243 (1993).CrossRefGoogle Scholar
  5. [5]
    K. Pawelzik, H.-U. Bauer, J. Deppisch, and T. Geisel, How oscillatory neuronal responses reflect bistability and switching of the hidden assembly dynamics, In: J.E. Moody, S.J. Hanson, and R.P. Lippmann (eds), Proceedings of the NIPS’93, 5, Morgan Kaufmann, San Mateo.Google Scholar
  6. [6]
    C.M. Gray, R. König, A.K. Engel, and W. Singer, Oscillatory responses in cat visual cortex exhibit inter-columnar synchronization which reflects global stimulus properties, Nature 338, 334 (1989).PubMedCrossRefGoogle Scholar
  7. [7]
    C.v.d. Malsburg, The correlation theory of brain function, Internal report 81-2, MPI for Biophysical Chemistry, Göttingen.Google Scholar
  8. [8]
    L.R. Rabiner, A tutorial on hidden-Markov models and selected applications in speech recognition, Proc. IEEE 77, 257 (1989).CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 1997

Authors and Affiliations

  • U. Ernst
    • 1
  • A. Kreiter
    • 2
  • K. Pawelzik
    • 1
  • T. Geisel
    • 1
  1. 1.Institut f. Theor. PhysikFrankfurtGermany
  2. 2.MPI für HirnforschungFrankfurtGermany

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