Delayed Random Walk Models of Neural Information Processing
نویسنده
چکیده
We present and compare two delayed random walk models of neural information processing. A delayed random walk is a random walk in which the transition probability depends on the position of the walker at a time in the past. The rst model is of human neuro-muscular control for postural sway. The other model is for a stochastic single neuron which has a delayed self{exciting feedback. We study each model using computer simulation to examine its time{ dependent and asymptotic stochastic behaviors. The similarities and di erences between the two models are discussed as well as how they relate to empirical data.
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تاریخ انتشار 2007