Synchronization Dynamics and Chimera States in a Two-Layer Erdős-Rényi Neural Network with STDP

This study investigates the synchronization dynamics of neuronal populations in a bilayer Erdős-Rényi (ER) network model with adaptive synaptic plasticity, focusing on the emergence and modulation of Chimera states. By integrating the FitzHugh-Nagumo neuron model with spike-timing-dependent plasticity (STDP) mechanisms, we systematically analyze how inter-layer delays and STDP rules influence the coexistence of synchronous and asynchronous subpopulations. Our key findings reveal three critical contributions: (1) adaptive STDP generates diverse Chimera configurations through dynamic synaptic weight modulation; (2) minute variations in inter-layer delay τ drive bistable transitions in network coherence; and (3) anti-Hebbian STDP enables full state transitions among synchronous, asynchronous, and non-synchronous regimes, whereas Hebbian rules stabilize synchrony. Well-established metrics enable comprehensive characterization of chimera state dynamics in adaptive neural networks, providing detailed quantitative insights into how temporal delays and synaptic plasticity govern collective neural behavior through systematic parameter exploration. While building upon established frameworks, our systematic analysis reveals specific parameter dependencies that enhance understanding of synchronization control mechanisms in layered neural systems.