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Regular spiking in high-conductance states: The essential role of inhibition
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SYSNO ASEP 0541638 Druh ASEP J - Článek v odborném periodiku Zařazení RIV J - Článek v odborném periodiku Poddruh J Článek ve WOS Název Regular spiking in high-conductance states: The essential role of inhibition Tvůrce(i) Bárta, Tomáš (FGU-C) RID, ORCID
Košťál, Lubomír (FGU-C) RID, ORCID, SAIČíslo článku 022408 Zdroj.dok. Physical Review E. - : American Physical Society - ISSN 2470-0045
Roč. 103, č. 2 (2021)Poč.str. 13 s. Jazyk dok. eng - angličtina Země vyd. US - Spojené státy americké Klíč. slova inhibition ; synaptic noise ; neuronal models ; spike-firing adaptation ; leaky integrate-and-fire ; Hodgkin-Huxley ; neuron Vědní obor RIV EA - Morfologické obory a cytologie Obor OECD Biology (theoretical, mathematical, thermal, cryobiology, biological rhythm), Evolutionary biology CEP GA20-10251S GA ČR - Grantová agentura ČR Způsob publikování Omezený přístup Institucionální podpora FGU-C - RVO:67985823 UT WOS 000619236600004 EID SCOPUS 85101275184 DOI 10.1103/PhysRevE.103.022408 Anotace Strong inhibitory input to neurons, which occurs in balanced states of neural networks, increases synaptic current fluctuations. This has led to the assumption that inhibition contributes to the high spike-firing irregularity observed in vivo. We used single compartment neuronal models with time-correlated (due to synaptic filtering) and state-dependent (due to reversal potentials) input to demonstrate that inhibitory input acts to decrease membrane potential fluctuations, a result that cannot be achieved with simplified neural input models. To clarify the effects on spike-firing regularity, we used models with different spike-firing adaptation mechanisms, and we observed that the addition of inhibition increased firing regularity in models with dynamic firing thresholds and decreased firing regularity if spike-firing adaptation was implemented through ionic currents or not at all. This fluctuation-stabilization mechanism provides an alternative perspective on the importance of strong inhibitory inputs observed in balanced states of neural networks, and it highlights the key roles of biologically plausible inputs and specific adaptation mechanisms in neuronal modeling. Pracoviště Fyziologický ústav Kontakt Lucie Trajhanová, lucie.trajhanova@fgu.cas.cz, Tel.: 241 062 400 Rok sběru 2022 Elektronická adresa https://doi.org/10.1103/PhysRevE.103.022408
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