Neural Networks: Artificial Intelligence and Industrial Applications

pp 37-40

Propagation of Synfire Activity in Cortical Networks: a Statistical Approach

  • Marc-Oliver GewaltigAffiliated withInstitut für Neuroinformatik, Ruhr-Universität Bochum
  • , Markus DiesmannAffiliated withCenter for Brain Research, The Weizmann Institute of Science
  • , Ad AertsenAffiliated withCenter for Brain Research, The Weizmann Institute of Science

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Recently it was demonstrated that the activity of frontal cortical neurons in the awake behaving monkey comprises excessive occurrences of highly accurate (~1–3 ms) spatio-temporal firing patterns. Moreover, these patterns can be related to the behavioral state of the animal [l, 10]. On the basis of the characteristic anatomy and physiology of the cortex, it was proposed that syn fire activity, propagating through the sparsely firing cortical neural network, presents a natural explanation for this phenomenon [2, 1]. In order to test this hypothesis, we investigated the dependence of reliable synfire propagation on the structural and the dynamical properties of a model cortical network, using the newly developed simulation tool SYNOD [6].