Multistable Synaptic Plasticity induces Memory Effects and Cohabitation of Chimera and Bump States in Leaky Integrate-and-Fire Networks

TL;DR

This paper investigates how multistable synaptic plasticity in neural networks leads to the simultaneous emergence of chimera and bump states, revealing memory effects and localized domain confinement through numerical simulations.

Contribution

It demonstrates that bistable plasticity can induce coexisting chimera and bump states in neural networks, highlighting the role of adaptive link weights in complex synchronization phenomena.

Findings

Coexistence of bump and chimera states observed in simulations.

Memory effects reflected in the spatial arrangement of coupling strengths.

Localization of domains prevents their travel around the network.

Abstract

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.