Estimation of firing rate from instantaneous interspike intervals
Language English Country Ireland Media print-electronic
Document type Journal Article
PubMed
38925356
DOI
10.1016/j.neures.2024.06.006
PII: S0168-0102(24)00085-3
Knihovny.cz E-resources
- Keywords
- Big data, Estimator, Firing rate, Spike train,
- MeSH
- Action Potentials * physiology MeSH
- Humans MeSH
- Models, Neurological * MeSH
- Neurons * physiology MeSH
- Animals MeSH
- Check Tag
- Humans MeSH
- Animals MeSH
- Publication type
- Journal Article MeSH
The rate coding hypothesis is the oldest and still one of the most accepted hypotheses of neural coding. Consequently, many approaches have been devised for the firing rate estimation, ranging from simple binning of the time axis to advanced statistical methods. Nonetheless the concept of firing rate, while informally understood, can be mathematically defined in several distinct ways. These definitions may yield mutually incompatible results unless implemented properly. Recently it has been shown that the notions of the instantaneous and the classical firing rates can be made compatible, at least in terms of their averages, by carefully discerning the time instant at which the neuronal activity is observed. In this paper we revisit the properties of instantaneous interspike intervals in order to derive several novel firing rate estimators, which are free of additional assumptions or parameters and their temporal resolution is 'locally self-adaptive'. The estimators are simple to implement and are numerically efficient even for very large sets of data.
Institute of Physiology of the Czech Academy of Sciences Videnska 1083 Prague 4 14200 Czech Republic
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