Universität zu Köln

Rost, Thomas, Deger, Moritz ORCID: 0000-0002-2775-2611 and Nawrot, Martin P. (2018). Winnerless competition in clustered balanced networks: inhibitory assemblies do the trick. Biol. Cybern., 112 (1-2). S. 81 - 99. NEW YORK: SPRINGER. ISSN 1432-0770

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Abstract

Balanced networks are a frequently employed basic model for neuronal networks in the mammalian neocortex. Large numbers of excitatory and inhibitory neurons are recurrently connected so that the numerous positive and negative inputs that each neuron receives cancel out on average. Neuronal firing is therefore driven by fluctuations in the input and resembles the irregular and asynchronous activity observed in cortical in vivo data. Recently, the balanced network model has been extended to accommodate clusters of strongly interconnected excitatory neurons in order to explain persistent activity in working memory-related tasks. This clustered topology introduces multistability and winnerless competition between attractors and can capture the high trial-to-trial variability and its reduction during stimulation that has been found experimentally. In this prospect article, we review the mean field description of balanced networks of binary neurons and apply the theory to clustered networks. We show that the stable fixed points of networks with clustered excitatory connectivity tend quickly towards firing rate saturation, which is generally inconsistent with experimental data. To remedy this shortcoming, we then present a novel perspective on networks with locally balanced clusters of both excitatory and inhibitory neuron populations. This approach allows for true multistability and moderate firing rates in activated clusters over a wide range of parameters. Our findings are supported by mean field theory and numerical network simulations. Finally, we discuss possible applications of the concept of joint excitatory and inhibitory clustering in future cortical network modelling studies.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Rost, Thomas UNSPECIFIED UNSPECIFIED UNSPECIFIED Deger, Moritz UNSPECIFIED orcid.org/0000-0002-2775-2611 UNSPECIFIED Nawrot, Martin P. UNSPECIFIED UNSPECIFIED UNSPECIFIED
URN:	urn:nbn:de:hbz:38-190832
DOI:	10.1007/s00422-017-0737-7
Journal or Publication Title:	Biol. Cybern.
Volume:	112
Number:	1-2
Page Range:	S. 81 - 99
Date:	2018
Publisher:	SPRINGER
Place of Publication:	NEW YORK
ISSN:	1432-0770
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language SYNAPTIC CONNECTIVITY; NEURAL VARIABILITY; SPIKING NEURONS; VISUAL-CORTEX; DYNAMICS; STATE; MODEL; INTERNEURONS; RAT; MEMORY Multiple languages Computer Science, Cybernetics; Neurosciences Multiple languages
Refereed:	Yes
URI:	http://kups.ub.uni-koeln.de/id/eprint/19083