Diffusion approximation of neuronal models revisited

DOI10.3934/mbe.2014.11.11zbMath1279.60103OpenAlexW2326558784WikidataQ47755883 ScholiaQ47755883MaRDI QIDQ395700

Jakub Cupera

Publication date: 30 January 2014

Published in: Mathematical Biosciences and Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.3934/mbe.2014.11.11

zbMATH Keywords

diffusion approximationStein's modelintegrate-and-fire modelreversal potentials

Mathematics Subject Classification ID

Neural biology (92C20) Diffusion processes (60J60) Applications of Brownian motions and diffusion theory (population genetics, absorption problems, etc.) (60J70)

Related Items (3)

Stein's neuronal model with pooled renewal input ⋮ The Jacobi diffusion process as a neuronal model ⋮ Shot noise, weak convergence and diffusion approximations

Cites Work

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• The Ornstein-Uhlenbeck process as a model for neuronal activity. I. Mean and variance of the firing time
• The response of cortical neurons to in vivo-like input current: Theory and experiment
• Diffusion approximation of the neuronal model with synaptic reversal potentials
• The Fokker-Planck equation. Methods of solution and applications.
• On the comparison of Feller and Ornstein-Uhlenbeck models for neural activity
• Estimation of the input parameters in the Feller neuronal model
• An Extended Analytic Expression for the Membrane Potential Distribution of Conductance-Based Synaptic Noise

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