Simulating Facilitation in a Spiking Neural Network

Abstract: Many insects are able to detect, isolate and track small targets that move quickly against a dynamic background. This ability is enabled by a group of neurons called small target motion detectors (STMD). These neurons, among other properties, have a type of short term memory called response facilitation. This type of facilitation is a phenomenon in which continued visual stimuli lead to an enhanced response, whereas single signals lead to little or no transmission of the signal. In previous studies on dragonflies, studies have shown that the facilitation waves have an intrinsic ability to travel throughout the neural networks even after the stimulus has stopped, which has not been simulated yet. The goal of this project was to examine which neuron and synapse models are currently available, then use those models to construct simulations of neural networks that could potentially support travelling facilitation waves in the ways that mimic the results of the in vivo studies. After a series of simulations the results show that even though NEST simulator currently has a number of synapse and neuron models that support facilitation, none of them could currently support a model with a travelling facilitation wave. The NEURON simulations were promising but overall proved to be inconclusive and required further experimentation.