Simulating Short-Term Synaptic Plasticity on SpiNNaker Neuromorphic Hardware

Abstract

Neuromorphic chips are well-suited for the exploration of neuronal dynamics in (near) real-time. In order to port existing research onto these chips, relevant models of neuronal and synaptic dynamics first need to be supported by their respective development environments and validated against existing simulator backends. At the time of writing, support for short-term synaptic plasticity on neuromorphic hardware is scarce. This technical paper proposes an implementation of dynamic synapses for the SpiNNaker development environment based on the popular synaptic plasticity model by Tsodyks and Markram (TM). This extension is undertaken in the context of existing research on neuromodulation and the study of deep brain stimulation (DBS) effects on singular-neuron responses. The implementation of the TM synapse is first detailed and then, simulated for various response types. Its role in studies of DBS effect on postsynaptic responses is also reviewed. Finally, given the real-time capabilities offered by the hardware, we provide some insights to lay the groundwork for future explorations of closed-loop DBS on neuromorphic chips.