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Frequency cluster formation and slow oscillations in neural populations with plasticity


Autoři: Vera Röhr aff001;  Rico Berner aff002;  Ewandson L. Lameu aff004;  Oleksandr V. Popovych aff006;  Serhiy Yanchuk aff003
Působiště autorů: Neurotechnology Group, Technische Universität Berlin, Berlin, Germany aff001;  Institut für Theoretische Physik, Technische Universität Berlin, Berlin, Germany aff002;  Institut für Mathematik, Technische Universität Berlin, Berlin, Germany aff003;  National Institute for Space Research (INPE), São José dos Campos, São Paulo, Brazil aff004;  Institut für Physik, Humboldt-Universität zu Berlin, Berlin, Germany aff005;  Institute of Neuroscience and Medicine - Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany aff006;  Institute for Systems Neuroscience - Medical Faculty, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany aff007
Vyšlo v časopise: PLoS ONE 14(11)
Kategorie: Research Article
doi: https://doi.org/10.1371/journal.pone.0225094

Souhrn

We report the phenomenon of frequency clustering in a network of Hodgkin-Huxley neurons with spike timing-dependent plasticity. The clustering leads to a splitting of a neural population into a few groups synchronized at different frequencies. In this regime, the amplitude of the mean field undergoes low-frequency modulations, which may contribute to the mechanism of the emergence of slow oscillations of neural activity observed in spectral power of local field potentials or electroencephalographic signals at high frequencies. In addition to numerical simulations of such multi-clusters, we investigate the mechanisms of the observed phenomena using the simplest case of two clusters. In particular, we propose a phenomenological model which describes the dynamics of two clusters taking into account the adaptation of coupling weights. We also determine the set of plasticity functions (update rules), which lead to multi-clustering.

Klíčová slova:

Action potentials – Functional magnetic resonance imaging – Neural networks – Neurons – Population dynamics – Synapses – Synaptic plasticity – Neuronal plasticity


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