Počet záznamů: 1
The effect of inhibition on rate code efficiency indicators
- 1.
SYSNO ASEP 0518628 Druh ASEP J - Článek v odborném periodiku Zařazení RIV J - Článek v odborném periodiku Poddruh J Článek ve WOS Název The effect of inhibition on rate code efficiency indicators Tvůrce(i) Bárta, Tomáš (FGU-C) RID, ORCID
Košťál, Lubomír (FGU-C) RID, ORCID, SAIČíslo článku e1007545 Zdroj.dok. PLoS Computational Biology - ISSN 1553-734X
Roč. 15, č. 12 (2019)Poč.str. 21 s. Jazyk dok. eng - angličtina Země vyd. US - Spojené státy americké Klíč. slova neural models ; information theory ; neural coding Vědní obor RIV FH - Neurologie, neurochirurgie, neurovědy Obor OECD Neurosciences (including psychophysiology CEP GA17-06943S GA ČR - Grantová agentura ČR Způsob publikování Open access Institucionální podpora FGU-C - RVO:67985823 UT WOS 000507310800018 EID SCOPUS 85076448863 DOI 10.1371/journal.pcbi.1007545 Anotace In this paper we investigate the rate coding capabilities of neurons whose input signal are alterations of the base state of balanced inhibitory and excitatory synaptic currents. We consider different regimes of excitation-inhibition relationship and an established conductance-based leaky integrator model with adaptive threshold and parameter sets recreating biologically relevant spiking regimes. We find that given mean post-synaptic firing rate, counter-intuitively, increased ratio of inhibition to excitation generally leads to higher signal to noise ratio (SNR). On the other hand, the inhibitory input significantly reduces the dynamic coding range of the neuron. We quantify the joint effect of SNR and dynamic coding range by computing the metabolic efficiency—the maximal amount of information per one ATP molecule expended (in bits/ATP). Moreover, by calculating the metabolic efficiency we are able to predict the shapes of the post-synaptic firing rate histograms that may be tested on experimental data. Likewise, optimal stimulus input distributions are predicted, however, we show that the optimum can essentially be reached with a broad range of input distributions. Finally, we examine which parameters of the used neuronal model are the most important for the metabolically efficient information transfer. Pracoviště Fyziologický ústav Kontakt Lucie Trajhanová, lucie.trajhanova@fgu.cas.cz, Tel.: 241 062 400 Rok sběru 2020 Elektronická adresa https://doi.org/10.1371/journal.pcbi.1007545
Počet záznamů: 1