Mechanisms of self-sustained oscillatory states in hierarchical modular networks with mixtures of electrophysiological cell types

In a network with a mixture of different electrophysiologicaltypes of neurons linked by excitatory and inhibitory connections,temporal evolution leads through repeated epochs of intensive global activity separated by intervals with low activity level. This behavior mimics ``up'' and ``down...

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Bibliographic Details
Main Authors: Petar eTomov, Rodrigo Felipe De Oliveira Pena, Antonio C Roque, Michael A Zaks
Format: Article
Language:English
Published: Frontiers Media S.A. 2016-03-01
Series:Frontiers in Computational Neuroscience
Subjects:
Online Access:http://journal.frontiersin.org/Journal/10.3389/fncom.2016.00023/full
Description
Summary:In a network with a mixture of different electrophysiologicaltypes of neurons linked by excitatory and inhibitory connections,temporal evolution leads through repeated epochs of intensive global activity separated by intervals with low activity level. This behavior mimics ``up'' and ``down'' states, experimentally observed in cortical tissues in absence of external stimuli. We interpret global dynamical features interms of individual dynamics of the neurons. In particular, weobserve that the crucial role both in interruption and in resumptionof global activity is played by distributions of the membrane recovery variable within the network. We also demonstrate that the behavior of neurons is moreinfluenced by their presynaptic environment in the networkthan by their formal types,assigned in accordance with their response to constant current.
ISSN:1662-5188