Review: Methods of firing rate estimation
Language English Country Ireland Media print-electronic
Document type Journal Article, Review
PubMed
31163197
DOI
10.1016/j.biosystems.2019.103980
PII: S0303-2647(19)30149-2
Knihovny.cz E-resources
- Keywords
- Bayesian rule, Firing rate, Kernel smoothing, Spike train, Time histogram,
- MeSH
- Action Potentials * MeSH
- Algorithms MeSH
- Bayes Theorem MeSH
- Data Interpretation, Statistical MeSH
- Humans MeSH
- Models, Neurological MeSH
- Neurons physiology MeSH
- Probability MeSH
- Stochastic Processes MeSH
- Animals MeSH
- Check Tag
- Humans MeSH
- Animals MeSH
- Publication type
- Journal Article MeSH
- Review MeSH
Neuronal firing rate is traditionally defined as the number of spikes per time window. The concept is essential for the rate coding hypothesis, which is still the most commonly investigated scenario in neuronal activity analysis. The estimation of dynamically changing firing rate from neural data can be challenging due to the variability of spike times, even under identical external conditions; hence a wide range of statistical measures have been employed to solve this particular problem. In this paper, we review established firing rate estimation methods, briefly summarize the technical aspects of each approach and discuss their practical applications.
Institute of Physiology of the Czech Academy of Sciences Videnska 1083 14220 Prague 4 Czech Republic
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