ArticleScientific reports2021
Multistability in a star network of Kuramoto-type oscillators with synaptic plasticity.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Synaptic reorganization of synchronized neuronal networks with synaptic weight and structural plasticity.PLoS computational biology · 2024Article
- Neuronal activity induces symmetry breaking in neurodegenerative disease spreading.Journal of mathematical biology · 2024Article
- A Phase Model of the Bio-Inspired NbOx Local Active Memristor under Weak Coupling Conditions.Micromachines · 2024Article
- Delay-dependent transitions of phase synchronization and coupling symmetry between neurons shaped by spike-timing-dependent plasticity.Cognitive neurodynamics · 2023Article
- Interplay of different synchronization modes and synaptic plasticity in a system of class I neurons.Scientific reports · 2022Article
- Synaptic reshaping of plastic neuronal networks by periodic multichannel stimulation with single-pulse and burst stimuli.PLoS computational biology · 2022Article
- Efficient suppression of parkinsonian beta oscillations in a closed-loop model of deep brain stimulation with amplitude modulation.Frontiers in human neuroscience · 2022Article
Corrections and comments
- Erratum issued
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
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