Voltage-Gated Ion Channels and the Variability in Information Transfer

Rahul Kumar Rathour, Hanoch Kaphzan

Research output: Contribution to journalArticlepeer-review

Abstract

The prerequisites for neurons to function within a circuit and be able to contain and transfer information efficiently and reliably are that they need to be homeostatically stable and fire within a reasonable range, characteristics that are governed, among others, by voltage-gated ion channels (VGICs). Nonetheless, neurons entail large variability in the expression levels of VGICs and their corresponding intrinsic properties, but the role of this variability in information transfer is not fully known. In this study, we aimed to investigate how this variability of VGICs affects information transfer. For this, we used a previously derived population of neuronal model neurons, each with the variable expression of five types of VGICs, fast Na+, delayed rectifier K+, A-type K+, T-type Ca++, and HCN channels. These analyses showed that the model neurons displayed variability in mutual information transfer, measured as the capability of neurons to successfully encode incoming synaptic information in output firing frequencies. Likewise, variability in the expression of VGICs caused variability in EPSPs and IPSPs amplitudes, reflected in the variability of output firing frequencies. Finally, using the virtual knockout methodology, we show that among the ion channels tested, the A-type K+ channel is the major regulator of information processing and transfer.

Original languageEnglish
Article number906313
JournalFrontiers in Cellular Neuroscience
Volume16
DOIs
StatePublished - 22 Jul 2022

Bibliographical note

Funding Information:
This work was supported by the Israel Science Foundation, Grant Number 248/20 (HK).

Publisher Copyright:
Copyright © 2022 Rathour and Kaphzan.

Keywords

  • active dendrites
  • global sensitivity analysis
  • information transfer
  • variability
  • voltage-gated ion channels

ASJC Scopus subject areas

  • Cellular and Molecular Neuroscience

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