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Título:	Mesoscopic Segregation of Excitation and Inhibition in a Brain Network Model
Autor/a:	Malagarriga Guasch, Daniel; Villa, Alessandro; García Ojalvo, Jordi; Pons Rivero, Antonio Javier
Otros autores:	Universitat Politècnica de Catalunya. Departament de Física i Enginyeria Nuclear; Universitat Politècnica de Catalunya. DONLL - Dinàmica no Lineal, Òptica no Lineal i Làsers
Abstract:	Neurons in the brain are known to operate under a careful balance of excitation and inhibition, which maintains neural microcircuits within the proper operational range. How this balance is played out at the mesoscopic level of neuronal populations is, however, less clear. In order to address this issue, here we use a coupled neural mass model to study computationally the dynamics of a network of cortical macrocolumns operating in a partially synchronized, irregular regime. The topology of the network is heterogeneous, with a few of the nodes acting as connector hubs while the rest are relatively poorly connected. Our results show that in this type of mesoscopic network excitation and inhibition spontaneously segregate, with some columns actingmainly in an excitatory manner while some others have predominantly an inhibitory effect on their neighbors.We characterize the conditions under which this segregation arises, and relate the character of the different columns with their to- pological role within the network. In particular, we show that the connector hubs are preferentially inhibitory, the more so the larger the node's connectivity. These results suggest a potential mesoscale organization of the excitation-inhibition balance in brain networks.
Abstract:	Peer Reviewed
Materia(s):	-Àrees temàtiques de la UPC::Física -Brain -Dynamics -Brain -Dynamics -Cervell -Dinàmica
Derechos:	Attribution-NonCommercial-NoDerivs 3.0 Spain http://creativecommons.org/licenses/by-nc-nd/3.0/es/
Tipo de documento:	Artículo - Versión publicada Artículo
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