Impact of Spike-Time Dependent Plasticity on Neuro-Spike Communication

Neuro-spike communication is a promising communication technique in future nano-scale applications. For example, it can be used as the communication means between biocompatible nanomachines, which sheds light on new solutions to achieve new medical diagnosis and treatment for neurological diseases. The information transmission in the neuro-spike communication channel is regulated by the ability of neurons to change synaptic strength over time, i.e., synaptic plasticity. In this paper, we consider one kind of typical synaptic plasticity, i.e., spike-time dependent plasticity (STDP), where the synaptic weights can be enhanced or decreased depending on temporal correlations between presynaptic spike arrival and postsynaptic firing. The STDP is integrated in the modeling of neuro-spike communication channel, and the mutual information of the system is derived theoretically. The mutual information is also evaluated through simulations under the synaptic noise and different vesicle release probabilities. Through simulations, it is observed that STDP can increase the single-input single-output (SISO) communication rates between synapses.