This chapter discusses a computational approach to brain function in which the effects of noise on the operation of attractor networks involved in short-term memory, attention, and decision making are described. It focuses on integrate-and-fire models of brain and cognitive function that incorporate the stochastic spiking-related dynamics and mean-field analyses that are consistent in terms of the parameters with these, but allow formal analysis of the networks.
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