Stability analysis of action potential generation using Markov models of voltage-gated sodium channel isoforms

Fuente: arXiv
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Main Authors: Abdullah, Youssof, Hart, Violet, Das, Moumita
Format: Preprint
Published: 2025
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author Abdullah, Youssof
Hart, Violet
Das, Moumita
author_facet Abdullah, Youssof
Hart, Violet
Das, Moumita
contents We investigate a conductance-based neuron model to explore how voltage-gated ion channel isoforms influence action-potential generation. The model combines a six-state Markov representation of NaV channels with a first-order KV3.1 model, allowing us to vary maximal sodium and potassium conductances and compare nine NaV isoforms. Using bifurcation theory and local stability analysis, we map regions of stable limit cycles and visualize excitability landscapes via heatmap-based diagrams. These analyses show that isoforms NaV1.3, NaV1.4 and NaV1.6 support broad excitable regimes, while isoforms NaV1.7 and NaV1.9 exhibit minimal oscillatory behavior. Our findings provide insights into the role of channel heterogeneity in neuronal dynamics and may help to guide the design of synthetic excitable systems by narrowing the parameter space needed for robust action-potential trains.
format Preprint
id arxiv_https___arxiv_org_abs_2512_01058
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Stability analysis of action potential generation using Markov models of voltage-gated sodium channel isoforms
Abdullah, Youssof
Hart, Violet
Das, Moumita
Neurons and Cognition
Chaotic Dynamics
We investigate a conductance-based neuron model to explore how voltage-gated ion channel isoforms influence action-potential generation. The model combines a six-state Markov representation of NaV channels with a first-order KV3.1 model, allowing us to vary maximal sodium and potassium conductances and compare nine NaV isoforms. Using bifurcation theory and local stability analysis, we map regions of stable limit cycles and visualize excitability landscapes via heatmap-based diagrams. These analyses show that isoforms NaV1.3, NaV1.4 and NaV1.6 support broad excitable regimes, while isoforms NaV1.7 and NaV1.9 exhibit minimal oscillatory behavior. Our findings provide insights into the role of channel heterogeneity in neuronal dynamics and may help to guide the design of synthetic excitable systems by narrowing the parameter space needed for robust action-potential trains.
title Stability analysis of action potential generation using Markov models of voltage-gated sodium channel isoforms
topic Neurons and Cognition
Chaotic Dynamics
url https://arxiv.org/abs/2512.01058