Poster: Parameter estimation for a reduced order spiking neuron model with relevance to in vitro embryonic rat motoneuronal data

The problem of finding parameters of an adaptive quadratic spiking neuron model in order to fit data derived from in vitro embryonic rat motoneurons is addressed. Since the model does not fit the shape of the experimental action potential, we utilize a correlation based technique to extract input-independent spike areas, and pre-distort these areas such that they conform to the model assumptions. Simulation results show that the spike train is accurately predicted.