Neural Comput - The mean time to express synaptic plasticity in integrate-and-express, stochastic models of synaptic plasticity induction.

Tópicos

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Resumo

Stochastic models of synaptic plasticity propose that single synapses perform a directed random walk of fixed step sizes in synaptic strength, thereby embracing the view that the mechanisms of synaptic plasticity constitute a stochastic dynamical system. However, fluctuations in synaptic strength present a formidable challenge to such an approach. We have previously proposed that single synapses must interpose an integration and filtering mechanism between the induction of synaptic plasticity and the expression of synaptic plasticity in order to control fluctuations. We analyze a class of three such mechanisms in the presence of possibly non-Markovian plasticity induction processes, deriving expressions for the mean expression time in these models. One of these filtering mechanisms constitutes a discrete low-pass filter that could be implemented on a small collection of molecules at single synapses, such as CaMKII, and we analyze this discrete filter in some detail. After considering Markov induction processes, we examine our own stochastic model of spike-timing-dependent plasticity, for which the probability density functions of the induction of plasticity steps have previously been derived. We determine the dependence of the mean time to express a plasticity step on pre- and postsynaptic firing rates in this model, and we also consider, numerically, the long-term stability against fluctuations of patterns of neuronal connectivity that typically emerge during neuronal development.

Resumo Limpo

stochast model synapt plastic propos singl synaps perform direct random walk fix step size synapt strength therebi embrac view mechan synapt plastic constitut stochast dynam system howev fluctuat synapt strength present formid challeng approach previous propos singl synaps must interpos integr filter mechan induct synapt plastic express synapt plastic order control fluctuat analyz class three mechan presenc possibl nonmarkovian plastic induct process deriv express mean express time model one filter mechan constitut discret lowpass filter implement small collect molecul singl synaps camkii analyz discret filter detail consid markov induct process examin stochast model spiketimingdepend plastic probabl densiti function induct plastic step previous deriv determin depend mean time express plastic step pre postsynapt fire rate model also consid numer longterm stabil fluctuat pattern neuron connect typic emerg neuron develop

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