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• W2236752435 abstract "The calculation of the steady-state probability density for multidimensional stochastic systems that do not obey detailed balance is a difficult problem. Here we present the analytical derivation of the stationary joint and various marginal probability densities for a stochastic neuron model with adaptation current. Our approach assumes weak noise but is valid for arbitrary adaptation strength and time scale. The theory predicts several effects of adaptation on the statistics of the membrane potential of a tonically firing neuron: (i) a membrane potential distribution with a convex shape, (ii) a strongly increased probability of hyperpolarized membrane potentials induced by strong and fast adaptation, and (iii) a maximized variability associated with the adaptation current at a finite adaptation time scale." @default.
• W2236752435 created "2016-06-24" @default.
• W2236752435 creator A5005593731 @default.
• W2236752435 creator A5030771251 @default.
• W2236752435 date "2015-12-07" @default.
• W2236752435 modified "2023-10-01" @default.
• W2236752435 title "Analytical approach to an integrate-and-fire model with spike-triggered adaptation" @default.
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• W2236752435 doi "https://doi.org/10.1103/physreve.92.062703" @default.
• W2236752435 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/26764723" @default.
• W2236752435 hasPublicationYear "2015" @default.
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