Metastable dynamics in heterogeneous neural fields

Abstract : We present numerical simulations of metastable states in heterogeneous neural fields that are connected along heteroclinic orbits. Such trajectories are possible representations of transient neural activity as observed, for example, in the electroencephalogram. Based on previous theoretical findings on learning algorithms for neural fields, we directly construct synaptic weight kernels from Lotka-Volterra neural population dynamics without supervised training approaches. We deliver a MATLAB neural field toolbox validated by two examples of one- and two-dimensional neural fields. We demonstrate trial-to-trial variability and distributed representations in our simulations which might therefore be regarded as a proof-of-concept for more advanced neural field models of metastable dynamics in neurophysiological data.
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Article dans une revue
Frontiers in Systems Neuroscience, Frontiers, 2015, 9, pp.97. 〈10.3389/fnsys.2015.00097〉
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https://hal.inria.fr/hal-01178903
Contributeur : Axel Hutt <>
Soumis le : mardi 21 juillet 2015 - 11:36:44
Dernière modification le : mercredi 28 septembre 2016 - 11:01:08

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Cordula Schwappach, Axel Hutt, Peter Beim Graben. Metastable dynamics in heterogeneous neural fields. Frontiers in Systems Neuroscience, Frontiers, 2015, 9, pp.97. 〈10.3389/fnsys.2015.00097〉. 〈hal-01178903〉

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