Guiding Synchrony through Random Networks

Publikation: Beitrag in FachzeitschriftForschungsartikelBeigetragenBegutachtung

Beitragende

  • Sven Jahnke - , Max Planck Institute for Dynamics and Self-Organization, Bernstein Center for Computational Neuroscience Göttingen, Georg-August-Universität Göttingen (Autor:in)
  • Marc Timme - , Max Planck Institute for Dynamics and Self-Organization, Bernstein Center for Computational Neuroscience Göttingen, Georg-August-Universität Göttingen (Autor:in)
  • Raoul Martin Memmesheimer - , Radboud University Nijmegen (Autor:in)

Abstract

Sparse random networks contain structures that can be considered as diluted feed-forward networks. Modeling of cortical circuits has shown that feed-forward structures, if strongly pronounced compared to the embedding random network, enable reliable signal transmission by propagating localized (subnetwork) synchrony. This assumed prominence, however, is not experimentally observed in local cortical circuits. Here, we show that nonlinear dendritic interactions, as discovered in recent single-neuron experiments, naturally enable guided synchrony propagation already in random recurrent neural networks that exhibit mildly enhanced, biologically plausible substructures.

Details

OriginalspracheEnglisch
Aufsatznummer041016
FachzeitschriftPhysical Review X
Jahrgang2
Ausgabenummer4
PublikationsstatusVeröffentlicht - 13 Dez. 2012
Peer-Review-StatusJa
Extern publiziertJa

Externe IDs

ORCID /0000-0002-5956-3137/work/142242481

Schlagworte

ASJC Scopus Sachgebiete

Schlagwörter

  • Biological physics, Complex systems