Synaptic strength changes and neural dynamical transitions induced by a synaptic plasticity for wakefulness-sleep cycle

Abstract

Experiments found that learning during wakefulness led to a net enhancement of synaptic strength, accompanied by the neural dynamical transition from tonic to bursting firing, while the net synaptic strength decreases to a baseline level during sleep, accompanied by the transition from bursting to tonic firing. In this paper, we provided a model of synaptic plasticity, which can realize synaptic strength changes and neural dynamical transitions for wakefulness-sleep cycle by using a coupled Hindmarsh-Rose neurons. Through numerical simulation and theoretical analysis, it was further found that, the average synaptic weight of the neural network can arrive to a stable value during either prolonged wakefulness or prolonged sleep, which depends on the ratio of some specific parameters in the model. Particularly, the synaptic weights exhibit a stable log-normal distribution observed in real neural systems, when the average synaptic weight arrives to the stable value. Moreover, the fluctuation of this weight distribution is positively correlated with the fluctuation of noise in the synaptic plasticity model. The provided model of the synaptic plasticity and the results of its dynamics can provide a theoretical reference for the physiological mechanism of synaptic plasticity and neuronal firings during the wakefulness-sleep cycle, and are expected to have potential applications in the development of therapeutic interventions for sleep disorders.