First-passage-time problem for simulated stochastic diffusion processes
Language English Country United States Media print
Document type Journal Article, Research Support, Non-U.S. Gov't
PubMed
8026178
DOI
10.1016/0010-4825(94)90068-x
PII: 0010-4825(94)90068-X
Knihovny.cz E-resources
- MeSH
- Algorithms MeSH
- Models, Biological * MeSH
- Humans MeSH
- Membrane Potentials physiology MeSH
- Models, Neurological MeSH
- Neurons physiology MeSH
- Computer Simulation * MeSH
- Refractory Period, Electrophysiological physiology MeSH
- Models, Statistical MeSH
- Stochastic Processes * MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
Solving the first-passage-time problem for one-dimensional stochastic diffusion processes is a task with many applications in biomedical research. It has been noted (Musila and Lánský, Int. J. Biomed. Comput. 31, 233-245, 1992) that the first-passage time is overestimated if computed as the time when the simulated trajectory of the process crosses the threshold. It is studied in this paper how the error depends on the simulation step and on the parameters of the process. We propose an adaptive algorithm to make the simulation faster. The presented examples are related to neuronal modelling, but application in other fields is straightforward.
References provided by Crossref.org
The parameters of the stochastic leaky integrate-and-fire neuronal model
On the comparison of Feller and Ornstein-Uhlenbeck models for neural activity
