Variability and Randomness of the Instantaneous Firing Rate

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985823%3A_____%2F21%3A00543840" target="_blank" >RIV/67985823:_____/21:00543840 - isvavai.cz</a>
Alternative codes found
RIV/00216208:11130/21:10428833
Result on the web
<a href="https://doi.org/10.3389/fncom.2021.620410" target="_blank" >https://doi.org/10.3389/fncom.2021.620410</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3389/fncom.2021.620410" target="_blank" >10.3389/fncom.2021.620410</a>

Result language
angličtina
Original language name
Variability and Randomness of the Instantaneous Firing Rate
Original language description
The apparent stochastic nature of neuronal activity significantly affects the reliability of neuronal coding. To quantify the encountered fluctuations, both in neural data and simulations, the notions of variability and randomness of inter-spike intervals have been proposed and studied. In this article we focus on the concept of the instantaneous firing rate, which is also based on the spike timing. We use several classical statistical models of neuronal activity and we study the corresponding probability distributions of the instantaneous firing rate. To characterize the firing rate variability and randomness under different spiking regimes, we use different indices of statistical dispersion. We find that the relationship between the variability of interspike intervals and the instantaneous firing rate is not straightforward in general. Counter-intuitively, an increase in the randomness (based on entropy) of spike times may either decrease or increase the randomness of instantaneous firing rate, in dependence on the neuronal firing model. Finally, we apply our methods to experimental data, establishing that instantaneous rate analysis can indeed provide additional information about the spiking activity.
Czech name
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Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
10103 - Statistics and probability

Project
<a href="/en/project/GA20-10251S" target="_blank" >GA20-10251S: Optimality of neuronal communication: an information-theoretic perspective</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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