Multistable Synaptic Plasticity induces Memory Effects and Cohabitation of Chimera and Bump States in Leaky Integrate-and-Fire Networks
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2024
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| author | Provata, Astero Almirantis, Yannis Li, Wentian |
| author_facet | Provata, Astero Almirantis, Yannis Li, Wentian |
| contents | Chimera states and bump states are collective synchronization phenomena observed independently (at different parameter regions) in networks of coupled nonlinear oscillators. And while chimera states are characterized by coexistence of coherent and incoherent domains, bump states consist of active domains operating on a silent background. Multistable plasticity in the network connections originates from brain dynamics and is based on the idea that neural cells may transmit inhibitory or excitatory signals depending on various factors, such as local connectivity, influence of neighboring cells etc. During the system/network integration, the link weights adapt and, in the case of multistability, they may organize in coexisting excitatory and/or inhibitory domains. Here, we explore the influence of bistable plasticity on collective synchronization states and we numerically demonstrate that the dynamics of the linking may give rise to co-existence of bump-like and chimera-like states simultaneously in the network. In the case of bump and chimera co-existence, confinement effects are developed: the different domains stay localized and do not travel around the network. Memory effects are also reported in the sense that the final spatial arrangement of the coupling strengths reflects some of the local properties of the initial link distribution. For the quantification of the system's spatial and temporal features, the global and local entropy functions are employed as measures of the network organization, while the average firing rates account for the network evolution and dynamics. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2410_14530 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Multistable Synaptic Plasticity induces Memory Effects and Cohabitation of Chimera and Bump States in Leaky Integrate-and-Fire Networks Provata, Astero Almirantis, Yannis Li, Wentian Chaotic Dynamics Disordered Systems and Neural Networks Adaptation and Self-Organizing Systems Chimera states and bump states are collective synchronization phenomena observed independently (at different parameter regions) in networks of coupled nonlinear oscillators. And while chimera states are characterized by coexistence of coherent and incoherent domains, bump states consist of active domains operating on a silent background. Multistable plasticity in the network connections originates from brain dynamics and is based on the idea that neural cells may transmit inhibitory or excitatory signals depending on various factors, such as local connectivity, influence of neighboring cells etc. During the system/network integration, the link weights adapt and, in the case of multistability, they may organize in coexisting excitatory and/or inhibitory domains. Here, we explore the influence of bistable plasticity on collective synchronization states and we numerically demonstrate that the dynamics of the linking may give rise to co-existence of bump-like and chimera-like states simultaneously in the network. In the case of bump and chimera co-existence, confinement effects are developed: the different domains stay localized and do not travel around the network. Memory effects are also reported in the sense that the final spatial arrangement of the coupling strengths reflects some of the local properties of the initial link distribution. For the quantification of the system's spatial and temporal features, the global and local entropy functions are employed as measures of the network organization, while the average firing rates account for the network evolution and dynamics. |
| title | Multistable Synaptic Plasticity induces Memory Effects and Cohabitation of Chimera and Bump States in Leaky Integrate-and-Fire Networks |
| topic | Chaotic Dynamics Disordered Systems and Neural Networks Adaptation and Self-Organizing Systems |
| url | https://arxiv.org/abs/2410.14530 |