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Power spectral analysis of voltage-gated channels in neurons
by
Magnani, Christophe
, Moore, Lee E.
in
admittance
/ Channel gating
/ Channel opening
/ Cognitive science
/ Fourier transforms
/ Hodgkin–Huxley
/ Markov
/ Markov chains
/ Membranes
/ Neural networks
/ neuronal noise
/ Neuroscience
/ Potassium
/ quadratic sinusoidal analysis
/ Simulation
/ Sodium
/ Voltage
/ voltage-gated ion channels
2025
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Power spectral analysis of voltage-gated channels in neurons
by
Magnani, Christophe
, Moore, Lee E.
in
admittance
/ Channel gating
/ Channel opening
/ Cognitive science
/ Fourier transforms
/ Hodgkin–Huxley
/ Markov
/ Markov chains
/ Membranes
/ Neural networks
/ neuronal noise
/ Neuroscience
/ Potassium
/ quadratic sinusoidal analysis
/ Simulation
/ Sodium
/ Voltage
/ voltage-gated ion channels
2025
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While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
Power spectral analysis of voltage-gated channels in neurons
by
Magnani, Christophe
, Moore, Lee E.
in
admittance
/ Channel gating
/ Channel opening
/ Cognitive science
/ Fourier transforms
/ Hodgkin–Huxley
/ Markov
/ Markov chains
/ Membranes
/ Neural networks
/ neuronal noise
/ Neuroscience
/ Potassium
/ quadratic sinusoidal analysis
/ Simulation
/ Sodium
/ Voltage
/ voltage-gated ion channels
2025
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Power spectral analysis of voltage-gated channels in neurons
Journal Article
Power spectral analysis of voltage-gated channels in neurons
2025
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Overview
This article develops a fundamental insight into the behavior of neuronal membranes, focusing on their responses to stimuli measured with power spectra in the frequency domain. It explores the use of linear and nonlinear (quadratic sinusoidal analysis) approaches to characterize neuronal function. It further delves into the random theory of internal noise of biological neurons and the use of stochastic Markov models to investigate these fluctuations. The text also discusses the origin of conductance noise and compares different power spectra for interpreting this noise. Importantly, it introduces a novel sequential chemical state model, named p 2 , which is more general than the Hodgkin–Huxley formulation, so that the probability for an ion channel to be open does not imply exponentiation. In particular, it is demonstrated that the p 2 (without exponentiation) and n 4 (with exponentiation) models can produce similar neuronal responses. A striking relationship is also shown between fluctuation and quadratic power spectra, suggesting that voltage-dependent random mechanisms can have a significant impact on deterministic nonlinear responses, themselves known to have a crucial role in the generation of action potentials in biological neural networks.
Publisher
Frontiers Research Foundation,Frontiers Media,Frontiers Media S.A
Subject
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