Switching Time Statistics for Driven Neuron Models: Analytic Expressions versus Numerics
- Analytical expressions are put forward to investigate the forced spiking activity of abstract neuron models such as the driven leaky integrate-and-fire (LIF) model. The method is valid in a wide parameter regime beyond the restraining limits of weak driving (linear response) and/or weak noise. The novel approximation is based on a discrete state Markovian modeling of the full dynamics with time-dependent rates. The scheme yields very good agreement with numerical Langevin and Fokker-Planck simulations of the full non-stationary dynamics for both, the first-passage time statistics and the interspike interval (residence time) distributions.
Author: | Michael SchindlerGND, Peter TalknerGND, Peter HänggiORCiDGND |
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URN: | urn:nbn:de:bvb:384-opus4-2897 |
Frontdoor URL | https://opus.bibliothek.uni-augsburg.de/opus4/355 |
Type: | Preprint |
Language: | English |
Publishing Institution: | Universität Augsburg |
Release Date: | 2006/09/05 |
Tag: | neurophysiology; brain models; Markov processes; bioelectric phenomena |
GND-Keyword: | Markov-Prozess; Bioelektronik; Neurophysiologie |
Source: | Firing Time Statistics for Driven Neuron Models: Analytic Expressions versus Numerics; erschienen in: Phys. Rev. Lett. 93, 048102 (2004); DOI: 10.1103/PhysRevLett.93.048102; URL: http://link.aps.org/abstract/PRL/v93/e048102 |
Institutes: | Mathematisch-Naturwissenschaftlich-Technische Fakultät |
Mathematisch-Naturwissenschaftlich-Technische Fakultät / Institut für Physik | |
Mathematisch-Naturwissenschaftlich-Technische Fakultät / Institut für Physik / Lehrstuhl für Theoretische Physik I | |
Dewey Decimal Classification: | 5 Naturwissenschaften und Mathematik / 53 Physik / 530 Physik |