A model for Fast Analog Computation Based on Unreliable Synapses

W. Maass and T. Natschlaeger


We investigate through theoretical analysis and computer simulations the consequences of unreliable synapses for fast analog computations in networks of spiking neurons, with analog variables encoded by the current firing activities of pools of spiking neurons. Our results suggest that the known unreliability of synaptic transmission may be viewed as a useful tool for analog computing, rather than as a ``bug'' in neuronal hardware. We also investigate computations on time series and Hebbian learning in this context of space-rate coding.

Reference: W. Maass and T. Natschlaeger. A model for fast analog computation based on unreliable synapses. Neural Computation, 12(7):1679-1704, 2000.