Power spectral analysis of voltage-gated channels in neurons
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. I...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2025-01-01
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| Series: | Frontiers in Neuroinformatics |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fninf.2024.1472499/full |
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| author | Christophe Magnani Lee E. Moore |
| author_facet | Christophe Magnani Lee E. Moore |
| author_sort | Christophe Magnani |
| collection | DOAJ |
| description | 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 p2, 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 p2 (without exponentiation) and n4 (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. |
| format | Article |
| id | doaj-art-ebf01259c1d440aaa067a7372b4be89d |
| institution | Kabale University |
| issn | 1662-5196 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Neuroinformatics |
| spelling | doaj-art-ebf01259c1d440aaa067a7372b4be89d2025-01-15T06:10:50ZengFrontiers Media S.A.Frontiers in Neuroinformatics1662-51962025-01-011810.3389/fninf.2024.14724991472499Power spectral analysis of voltage-gated channels in neuronsChristophe MagnaniLee E. MooreThis 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 p2, 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 p2 (without exponentiation) and n4 (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.https://www.frontiersin.org/articles/10.3389/fninf.2024.1472499/fullHodgkin–HuxleyMarkovvoltage-gated ion channelsneuronal noiseadmittancequadratic sinusoidal analysis |
| spellingShingle | Christophe Magnani Lee E. Moore Power spectral analysis of voltage-gated channels in neurons Frontiers in Neuroinformatics Hodgkin–Huxley Markov voltage-gated ion channels neuronal noise admittance quadratic sinusoidal analysis |
| title | Power spectral analysis of voltage-gated channels in neurons |
| title_full | Power spectral analysis of voltage-gated channels in neurons |
| title_fullStr | Power spectral analysis of voltage-gated channels in neurons |
| title_full_unstemmed | Power spectral analysis of voltage-gated channels in neurons |
| title_short | Power spectral analysis of voltage-gated channels in neurons |
| title_sort | power spectral analysis of voltage gated channels in neurons |
| topic | Hodgkin–Huxley Markov voltage-gated ion channels neuronal noise admittance quadratic sinusoidal analysis |
| url | https://www.frontiersin.org/articles/10.3389/fninf.2024.1472499/full |
| work_keys_str_mv | AT christophemagnani powerspectralanalysisofvoltagegatedchannelsinneurons AT leeemoore powerspectralanalysisofvoltagegatedchannelsinneurons |