Characterizing the Firing Properties of an Adaptive Analog VLSI Neuron
We describe the response properties of a compact, low power, analog circuit that implements a model of a leaky–Integrate & Fire (I&F) neuron, with spike-frequency adaptation, refractory period and voltage threshold modulation properties. We investigate the statistics of the circuit’s output response by modulating its operating parameters, like refractory period and adaptation level and by changing the statistics of the input current. The results show a clear match with theoretical prediction and neurophysiological data in a given range of the parameter space. This analysis defines the chip’s parameter working range and predicts its behavior in case of integration into large massively parallel very–large–scale–integration (VLSI) networks.