Effects of spike-time-dependent plasticity on chimera-like states in the bistable excitatory–inhibitory cortical neuronal network

Synaptic plasticity and transmission delays are crucial for information processing in the nervous system. In this study, we investigate the emergence of chimera-like states using a bistable Hodgkin–Huxley adaptive neuronal network incorporating axonal transmission delays and spike-time-dependent plasticity (STDP). While previous research has predominantly focused on static topologies, the core novelty of our work lies in revealing how the dynamic co-evolution of network structure and synchronization actively reshapes macroscopic phase transition boundaries. In All-Excitatory networks, excitatory STDP promotes the self-organization of local clusters. These clusters generate substantial excitatory postsynaptic currents (EPSCs) that trigger the Synchronization-induced spike termination (SIST) mechanism, significantly expanding the parameter range for chimera-like states. In All-Inhibitory networks, inhibitory STDP drives structural sparsification by pruning redundant connections. This optimized topology leverages transmission delays to enforce precise global phase locking, efficiently creating temporal windows for neuronal silencing. In Excitatory–Inhibitory mixed networks, a synergistic interaction emerges where inhibitory neurons act as a “SIST catalyst.” By establishing a rigid temporal order, inhibition lowers the structural barrier for state transitions, allowing excitation to deliver sufficient perturbations to induce silence. Parameter space analysis demonstrates that STDP enhances pattern formation efficiency under weak coupling while limiting robustness under strong external drives. This study elucidates how plasticity dynamically reshapes the effective topology, providing a new theoretical perspective for understanding cortical multistable transitions.