Synchronicity transitions determine connection fluctuations in a model of coupled oscillators with plasticity

Sleep and rest are crucial for knowledge reorganization and creativity. During these periods, synapses between neurons are plastically altered and neuronal activities are collectively synchronized, accompanied by large differences in excitation-inhibition (EI) balance. These processes are assumed to be dissimilar from the learning process during task engagement. The detailed mechanism of how synchronized neuronal activities modify neural circuits via plasticity has yet to be fully understood. The Kuramoto model is utilized to study the collective synchronization of oscillators, including neurons. We previously proposed the EI-Kuramoto model, in which the EI balance was implemented in the Kuramoto model. The model alters its synchronicity based on the EI balance of the interaction strength. In this study, we developed this EI-Kuramoto model by implementing plasticity, leading to the plastic EI-Kuramoto (pEI-Kuramoto) model. Models with high inhibition displayed desynchronized dynamics and consistent connection strengths. Models with low inhibition exhibited bistable dynamics between synchronized and desynchronized states and fluctuation of interaction strengths in middle strength connections, while the strongest connections remained stable. These results, stabilizing a few strong connections and fluctuating the other connections in low inhibition conditions, could facilitate knowledge abstraction and reorganization. Our findings shed light on how varying inhibitory effects influence network stability and coupling, offering deeper insights into synaptic networks and knowledge reshaping.