Neuronal jitter: can we measure the spike timing dispersion differently?
Language English Country India Media print
Document type Journal Article, Research Support, Non-U.S. Gov't
- MeSH
- Action Potentials physiology MeSH
- Entropy MeSH
- Humans MeSH
- Models, Neurological * MeSH
- Neurons physiology MeSH
- Probability MeSH
- Models, Statistical * MeSH
- Synapses physiology MeSH
- Models, Theoretical MeSH
- Animals MeSH
- Check Tag
- Humans MeSH
- Animals MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
We propose a novel measure of statistical dispersion of a positive continuous random variable: the entropy-based dispersion (ED). We discuss the properties of ED and contrast them with the widely employed standard deviation (SD) measure. We show that the properties of SD and ED are different: while SD is a second moment characteristics measuring the dispersion relative to the mean value, ED measures an effective spread of the probability distribution and is more closely related to the notion of randomness of spiking activity. We apply both SD and ED to analyze the temporal precision of neuronal spiking activity of the perfect integrate-and-fire model, which is a plausible neural model under the assumption of high input synaptic activity. We show that SD and ED may give strikingly different results for some widely used models of presynaptic activity.
References provided by Crossref.org
Variability and Randomness of the Instantaneous Firing Rate
Ergodicity and parameter estimates in auditory neural circuits
