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ZENODO
Dataset . 2024
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2024
License: CC BY
Data sources: Datacite
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Complex excitability and ``flipping" of granule cells: an experimental and computational study

Authors: Danielewicz, Joanna;

Complex excitability and ``flipping" of granule cells: an experimental and computational study

Abstract

Electrophysiology dataset for Complex excitability and ``flipping" of granule cells: an experimental and computational study. In response to prolonged depolarizing current steps, different classes of neurons display specific firing characteristics (i.e., excitability class), such as a regular train of action potentials with more or less adaptation, delayed responses, or bursting. In general, one or more specific ionic transmembrane currents underlie the different firing patterns. Here, we sought to investigate the influence of artificial sodium-like (Na channels) and slow potassium-like (KM channels) voltage-gated channels conductances on firing patterns and transition to depolarization block (DB) in Dentate Gyrus granule cells with dynamic clamp - a computer-controlled real-time closed-loop electrophysiological technique, which allows to couple mathematical models simulated in a computer with biological cells. Our findings indicate that the mimicked extra Na/KM channels significantly affect the firing rate of low frequency cells, but not in high-frequency cells. Moreover, we have observed that 44 percent of recorded cells exhibited what we have called a ``flipping'' behavior. This means that these cells were able to overcome the DB and generate trains of action potentials at higher current injection steps. We have developed a mathematical model of ``flipping" cells to explain this phenomenon. Based on our computational model, we conclude that the appearance of ``flipping" is linked to the number of states for the sodium channel of the model.

Keywords

excitability, dentate gyrus, dynamic clamp electrophysiology, depolarization block, granule cells

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average