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Synchronization effects between striatal fast-spiking interneurons forming networks with different topologies
KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.ORCID iD: 0000-0002-0550-0739
2008 (English)In: Frontiers in Neuroinformatics, ISSN 1662-5196Article in journal (Other academic) Published
Abstract [en]

The basal ganglia are involved in executive functions of the forebrain, such as the planning and selection of motor behavior. In the striatum, which is the input stage of the basal ganglia system, fast-spiking interneurons provide an effective feedforward inhibition to the medium-sized spiny projection neurons. Thus, these fast-spiking neurons are able to control the striatal output to later stages in the basal ganglia. Recently, in modeling studies it has been shown that pairs of cells as well as randomly connected networks of electrically coupled fast-spiking cells are able to synchronize their activity. Here we want to investigate the influence of network topology and network size on the synchronization in a simulated network of striatal fast-spiking interneurons. We use a biophysically detailed single-cell model of the fast-spiking interneuron with 127 compartments (Hellgren Kotaleski et al., J Neurophysiology, 95: 331-41, 2006; Hjorth et al., Neurocomputing 70: 1887–1891, 2007), and parallelize the network model of electrically coupled fast-spiking cells using PGENESIS running on a Blue Gene/L supercomputer. General network statistics and synaptic input is constrained by published data from the striatum. Network topology is varied from ’regular’ over ’small-world’ to ’random’ (Watts & Strogatz, Nature 393: 440–442, 1998). Using common statistical measures, we will determine the extent of local and global synchronization for each network topology. Furthermore, we investigate the interactions in the network by means of Ising models (Schneidman et al., Nature 440: 1007–1012, 2006). We are particularly interested in the relation between the ’interaction’ – as obtained by the Ising model – and the underlying network topology; e. g., do directly coupled fast-spiking interneuron pairs synchronize most?So far, the small amount of fast-spiking cells in the striatum (less than 2 %) makes experimental studies on the network level difficult or even impossible. With our study we hope to gain a better understanding of interaction effects in the feedforward inhibitory network of the striatum.

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Computer and Information Science
URN: urn:nbn:se:kth:diva-58770DOI: 10.3389/conf.neuro.11.2008.01.041OAI: diva2:473964
1st INCF Congress of Neuroinformatics
QC 20120113. Conference: Neuroinformatics 2008, Stockholm, Sweden, 7 Sep - 9 Sep, 2008Available from: 2012-01-08 Created: 2012-01-08 Last updated: 2012-01-13Bibliographically approved

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