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Analysis of Synchronization in a Neural Population by a Population Density Approach
Garenne A., Henry J., Tarniceriu C. O.
Mathematical Modelling of Natural Phenomena 5, 2 (2010) 5-25 - http://hal.inria.fr/inria-00482420
Articles in peer-reviewed journal
Mathematics/Analysis of PDEs
Life Sciences/Neurons and Cognition/Neurobiology
Analysis of Synchronization in a Neural Population by a Population Density Approach
André Garenne 1, Jacques Henry ( ) 2, 3, Carmen Oana Tarniceriu () 3
1:  Laboratoire Mouvement Adaptation Cognition (MAC)
Université Victor Segalen - Bordeaux II – CNRS : UMR5227
Zone nord Bat 2, 2e étage, 146, rue Léo Saignat, 33076 Bordeaux Cedex, France
France
2:  Institut de Mathématiques de Bordeaux (IMB)
http://www.math.u-bordeaux.fr/IMB/
CNRS : UMR5251 – Université Sciences et Technologies - Bordeaux I – Université Victor Segalen - Bordeaux II
351 cours de la Libération 33405 TALENCE CEDEX
France
3:  ANUBIS (INRIA Bordeaux - Sud-Ouest)
INRIA – Université Sciences et Technologies - Bordeaux I – Université Victor Segalen - Bordeaux II – CNRS : UMR
France
In this paper we deal with a model describing the evolution in time of the density of a neural population in a state space, where the state is given by Izhikevich's two - dimensional single neuron model. The main goal is to mathematically describe the occurrence of a significant phenomenon observed in neurons populations, the synchronization. To this end, we are making the transition to phase density population, and use Malkin theorem to calculate the phase deviations of a weakly coupled population model.
English

Mathematical Modelling of Natural Phenomena
2010-03
international
EDP science
Mathematics and neurosciences
5
2
5-25

Single neuron model – Population density approach – Synchronization
programme CNRS neuroinformatique
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