Literature DB >> 33972613

Multistability in a star network of Kuramoto-type oscillators with synaptic plasticity.

Irmantas Ratas1, Kestutis Pyragas2, Peter A Tass3.   

Abstract

We analyze multistability in a star-type network of phase oscillators with coupling weights governed by phase-difference-dependent plasticity. It is shown that a network with N leaves can evolve into [Formula: see text] various asymptotic states, characterized by different values of the coupling strength between the hub and the leaves. Starting from the simple case of two coupled oscillators, we develop an analytical approach based on two small parameters [Formula: see text] and [Formula: see text], where [Formula: see text] is the ratio of the time scales of the phase variables and synaptic weights, and [Formula: see text] defines the sharpness of the plasticity boundary function. The limit [Formula: see text] corresponds to a hard boundary. The analytical results obtained on the model of two oscillators are generalized for multi-leaf star networks. Multistability with [Formula: see text] various asymptotic states is numerically demonstrated for one-, two-, three- and nine-leaf star-type networks.

Entities:  

Year:  2021        PMID: 33972613     DOI: 10.1038/s41598-021-89198-0

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


  20 in total

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5.  Co-evolution of phases and connection strengths in a network of phase oscillators.

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6.  Emergence of slow collective oscillations in neural networks with spike-timing dependent plasticity.

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7.  Noise-enhanced coupling between two oscillators with long-term plasticity.

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8.  Formation of feedforward networks and frequency synchrony by spike-timing-dependent plasticity.

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Journal:  J Comput Neurosci       Date:  2007-03-28       Impact factor: 1.453

9.  Delay-Induced Multistability and Loop Formation in Neuronal Networks with Spike-Timing-Dependent Plasticity.

Authors:  Mojtaba Madadi Asl; Alireza Valizadeh; Peter A Tass
Journal:  Sci Rep       Date:  2018-08-13       Impact factor: 4.379

10.  The importance of the whole: Topological data analysis for the network neuroscientist.

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Journal:  Netw Neurosci       Date:  2019-07-01
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