Distribution of interspike intervals estimated from multiple spike trains observed in a short time window
Language English Country United States Media print-electronic
Document type Journal Article, Research Support, Non-U.S. Gov't
- MeSH
- Models, Biological * MeSH
- Time Factors MeSH
- Neurons cytology MeSH
- Poisson Distribution MeSH
- Stochastic Processes MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
Several nonparametric estimators of the probability distribution of interspike intervals are introduced. The methods are suitable for simultaneous spike trains observed in a time window of length comparable with the mean interspike interval. This reflects the situation in which a high number of input spike trains converge to a single cortical neuron that has to react in a relatively short time. The simulation study is performed to compare the estimators. For that purpose, several types of stationary point processes are considered as the models of neuronal activity. The methods permit one to estimate the distribution of interspike intervals even if practically none of them are observed. The Kaplan-Meier estimator seems to be the most flexible and reliable among all studied methods, but no direct conclusions as to how real neurons work can be deduced from it.
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