Nonlinear Dynamics Emerging in Large Scale Neural Networks with Ontogenetic and Epigenetic Processes

  • Javier Iglesias
  • Olga K. Chibirova
  • Alessandro E. P. Villa
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4668)


We simulated a large scale spiking neural network characterized by an initial developmental phase featuring cell death driven by an excessive firing rate, followed by the onset of spike-timing-dependent synaptic plasticity (STDP), driven by spatiotemporal patterns of stimulation. The network activity stabilized such that recurrent preferred firing sequences appeared along the STDP phase. The analysis of the statistical properties of these patterns give hints to the hypothesis that a neural network may be characterized by a particular state of an underlying dynamical system that produces recurrent firing patterns.


Spike Train Spatiotemporal Pattern Excitatory Input Overlap Factor Raster Plot 
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© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Javier Iglesias
    • 1
  • Olga K. Chibirova
    • 1
  • Alessandro E. P. Villa
    • 1
  1. 1.Grenoble Institut des Neurosciences-GIN, Centre de Recherche, Inserm U 836-UJF-CEA-CHU, NeuroHeuristic Research Group, University Joseph Fourier, GrenobleFrance

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