First author: Voges, Nicole (poster)
Poster board A43 - Mon 14/07/2008, 12:15 - Hall 1
Session 075 - Patterning 2
Abstract n° 075.14
Publication ref.: FENS Abstr., vol.4, 075.14, 2008
||Voges N. (1), Kremkow J. (1, 2) & Perrinet L. (1)
||(1) INCM, CNRS & Aix-Marseille Universite, Marseille, France; (2) Inst. of Biology III, Albert-Ludwigs University, Freiburg, Germany
||Dynamics of cortical networks based on patchy connectivity patterns.
||The architecture of the complex network constituted by the primary visual cortex is an essential determinant of its function. Currently, most simulations of cortical network dynamics are either based on randomly connected networks (Brunel'00) or focus on locally coupled artificial neurons (Mehring'03). However, several neuroanatomical publications (Binzegger'07, Kisvarday'92) demonstrate that the projection patterns of cortical neurons are much more complex than these rather simple assumptions: A number of synapses is established to cells located at a distance from the presynaptic neuron much longer than the typical local range. In addition, there is more and more evidence that the special feature of 'patchy'projections (spatially clustered projection targets) is not a rare exception but rather the general case, also valid for inhibitory cortical cells. Here, we analyze the dynamical behavior of various types of spatially embedded 2D networks.
Considering spiking integrate-and-fire-neurons with conductance based synapses, we investigate whether different connection strategies influence the resulting network activity. For example, specifically structured networks presumably lead to changes in the parameters describing the dynamical state space of neuronal network activity (Brunel'00). Moreover, the assumption of patchy connections could facilitate the the possibility of a synchronous group-wise signal propagation, i. e., cortical information processing by so-called synfire chains (Mehring'03). The aim of our analysis is to relate simulated network dynamics to the results of optical imaging experiments. This work is supported by EU Grant 15879 (FACETS). Network dynamics are simulated with NEST/PyNN.
||A - Development
Copyright © 2008 - Federation of European Neuroscience Societies (FENS)