ArticleJournal of computational neuroscience2015
Interspike interval correlation in a stochastic exponential integrate-and-fire model with subthreshold and spike-triggered adaptation.
Article in Journal of computational neuroscience, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Mean-return-time phase of a stochastic oscillator provides an approximate renewal description for the associated point process.Biological cybernetics · 2022Review
- Interspike interval correlations in neuron models with adaptation and correlated noise.PLoS computational biology · 2021Article
- Multi-scale detection of rate changes in spike trains with weak dependencies.Journal of computational neuroscience · 2017Article
- Modulation of neuronal dynamic range using two different adaptation mechanisms.Neural regeneration research · 2017Article
- A Diffusion Approximation and Numerical Methods for Adaptive Neuron Models with Stochastic Inputs.Frontiers in computational neuroscience · 2016Article
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3 authors.
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Abstract
We study the spike statistics of an adaptive exponential integrate-and-fire neuron stimulated by white Gaussian current noise. We derive analytical approximations for the coefficient of variation and the serial correlation coefficient of the interspike interval assuming that the neuron operates in the mean-driven tonic firing regime and that the stochastic input is weak. Our result for the serial correlation coefficient has the form of a geometric sequence and is confirmed by the comparison to numerical simulations. The theory predicts various patterns of interval correlations (positive or negative at lag one, monotonically decreasing or oscillating) depending on the strength of the spike-triggered and subthreshold components of the adaptation current. In particular, for pure subthreshold adaptation we find strong positive ISI correlations that are usually ascribed to positive correlations in the input current. Our results i) provide an alternative explanation for interspike-interval correlations observed in vivo, ii) may be useful in fitting point neuron models to experimental data, and iii) may be instrumental in exploring the role of adaptation currents for signal detection and signal transmission in single neurons.
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