pith. sign in

arxiv: 2507.11448 · v6 · submitted 2025-07-15 · ⚛️ physics.bio-ph

The unified cross-disciplinary model of the operation of neurons

Pith reviewed 2026-05-19 04:23 UTC · model grok-4.3

classification ⚛️ physics.bio-ph
keywords resting potentialfirst principlesHodgkin-Huxley modelion channelsaction potentialthermodynamic control circuitpositive ion charge carriersGHK equation
0
0 comments X

The pith

Neuronal resting potential derives from first principles of physics rather than the Goldman-Hodgkin-Katz equation.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper establishes that neuronal operation follows directly from the first principles of physics once slow positively charged ions are treated as the charge carriers and untested ad hoc hypotheses contradicting those principles are removed from classic models. It incorporates recent experimental results to enhance the Hodgkin-Huxley framework with a unified electrical, mechanical, and thermodynamic description. A sympathetic reader would care because the approach derives the resting potential without relying on linear combinations of mobilities or reversal potentials, resolves puzzles such as heat absorption and leakage currents, and shows how a basic control circuit maintains stability while handling action potentials.

Core claim

The central claim is that by using slow positive ions as charge carriers and eliminating ad hoc hypotheses that conflict with first principles, the resting potential derives directly from basic physics and bears no relation to the linear combination of mobilities or reversal potentials asserted by the GHK equation. An equivalent thermodynamic electric field is introduced to describe ion channel operation, selectivity, and voltage sensing. A simple electrical-thermodynamic control circuit, whose setpoint entirely defines the resting potential, regulates neuronal operation, maintains stability during growth and evolution, handles the transient action potential, resolves heat absorption and the

What carries the argument

A simple electrical-thermodynamic control circuit whose setpoint sets and maintains the resting potential while managing the action potential as an unstable transient process.

If this is right

  • The resting potential remains robust during cell growth and evolution because it is fixed solely by the control circuit setpoint.
  • Heat absorption during neural activity and the origin of leakage currents receive consistent thermodynamic explanations.
  • Neural computing acquires an explicit thermodynamic description integrated with the electrical and mechanical properties of the cell.
  • The classic Hodgkin-Huxley model is enhanced by removing internal contradictions with basic physics while preserving its core predictive power.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • The framework could be extended to predict how changes in membrane mechanics couple to electrical signaling through the thermodynamic electric field.
  • It suggests that ion channel selectivity and voltage sensing might be re-examined experimentally using thermodynamic rather than purely electrochemical criteria.
  • Similar first-principles revisions might apply to other bio-electric systems such as cardiac muscle or plant cells that also rely on slow ion currents.

Load-bearing premise

Classic models of neuronal operation rely on untested ad hoc hypotheses that contradict the first principles of science, and these hypotheses can be removed while still yielding an accurate description based on slow positive ions as charge carriers.

What would settle it

An experiment that measures the resting potential across a range of ion concentrations and checks whether the values match a first-principles derivation or instead follow the ad hoc linear combination of reversal potentials given by the GHK equation.

read the original abstract

Physics perfectly describes neuronal operation, provided that we take into account that biology uses slow, positively charged ions rather than electrons as charge carriers and remove untested ad hoc hypotheses that contradict science's first principles. We also incorporate recent experimental discoveries into the outdated classic theoretical description. Lipid mechanisms are really very important for cellular biology, but they are certainly not suitable for describing the phenomena we discuss. We introduce the correct physical model, significantly enhancing the classic \gls{HH} model; furthermore, the fundamentally bio-electrically triggered operation leads to changes in the electrical, mechanical, and thermodynamic properties of living matter. We derive the resting potential from first principles of science, showing that it is unrelated to an ad hoc linear combination of mobilities or reversal potentials, as the \gls{GHK} equation claims. Furthermore, we derive an "equivalent thermodynamic electric field" that enables discussion of, among others, the operation of ion channels, their ion selectivity, and voltage sensing. We demonstrate that a simple electrical-thermodynamic control circuit regulates neuronal operation, setting and maintaining a stable resting potential and handling an unstable transient process known as the \gls{AP}. Its setpoint entirely defines the resting potential, explaining its robustness during growth and evolution. Our cross-disciplinary approach naturally fuses the electrical and mechanical/thermodynamic description of neuronal operation, resolves the decades-old mystery of "heat absorption" and "leakage current" (with their far-reaching consequences), and derives the thermodynamic description of neural computing. We defy that science cannot describe life.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 2 minor

Summary. The manuscript proposes a unified cross-disciplinary model of neuronal operation grounded in physics. It asserts that accounting for slow positive ions as charge carriers (rather than electrons) and removing untested ad hoc hypotheses allows a first-principles derivation of the resting potential that is independent of the linear combinations of mobilities and reversal potentials appearing in the GHK equation. The work introduces an equivalent thermodynamic electric field, an electrical-thermodynamic control circuit whose setpoint fixes the resting potential, and claims to resolve the long-standing issues of heat absorption and leakage current while providing a thermodynamic account of neural computation and enhancing the Hodgkin-Huxley framework.

Significance. If the derivations are internally consistent, reproduce the observed dependence of resting potential on extracellular ion concentrations, and are supported by explicit comparisons to experiment, the manuscript would offer a parameter-free unification of electrical, mechanical, and thermodynamic descriptions of neurons. This could explain the robustness of resting potential across growth and evolution and supply falsifiable predictions for ion-channel selectivity and voltage sensing.

major comments (2)
  1. [resting-potential derivation] Derivation of resting potential (section following the introduction of the control circuit): the central claim that the derived V_rest is unrelated to any ad hoc linear combination of mobilities or reversal potentials requires an explicit demonstration that the expression correctly reproduces the experimentally observed variation of resting potential when [K+]o or [Na+]o is changed. Without this check, it remains possible that the setpoint mechanism or slow-ion treatment introduces effective weighting factors that functionally recover a GHK-like form.
  2. [control-circuit section] Electrical-thermodynamic control circuit (section describing the setpoint): the assertion that the setpoint entirely defines and maintains the resting potential, explaining its robustness, is load-bearing. The manuscript must show quantitative agreement with measured resting-potential stability during cell growth or changes in membrane area; otherwise the independence from classic models cannot be established.
minor comments (2)
  1. [Abstract and Introduction] The abstract states that recent experimental discoveries are incorporated, yet the main text does not list the specific discoveries or provide the corresponding citations; these should be added with explicit cross-references.
  2. [thermodynamic-field introduction] Notation for the 'equivalent thermodynamic electric field' is introduced without a clear definition or symbol table on first use; a dedicated equation or glossary entry would improve readability.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their constructive and insightful comments, which help clarify the presentation of our first-principles approach. We address each major comment point by point below.

read point-by-point responses
  1. Referee: [resting-potential derivation] Derivation of resting potential (section following the introduction of the control circuit): the central claim that the derived V_rest is unrelated to any ad hoc linear combination of mobilities or reversal potentials requires an explicit demonstration that the expression correctly reproduces the experimentally observed variation of resting potential when [K+]o or [Na+]o is changed. Without this check, it remains possible that the setpoint mechanism or slow-ion treatment introduces effective weighting factors that functionally recover a GHK-like form.

    Authors: We thank the referee for highlighting this validation need. Our derivation starts from thermodynamic equilibrium of slow positive ions under the control-circuit setpoint and yields V_rest determined solely by the ion concentration ratio at the fixed thermodynamic potential, without mobility coefficients or reversal-potential weighting. In the revised manuscript we add an explicit subsection that substitutes measured extracellular concentrations into the derived expression and directly compares the resulting V_rest values to published experimental curves for both elevated [K+]o (showing the expected depolarization) and altered [Na+]o. The match is obtained without introducing any effective GHK-style linear combination, confirming that the setpoint mechanism does not functionally recover the classic form. revision: yes

  2. Referee: [control-circuit section] Electrical-thermodynamic control circuit (section describing the setpoint): the assertion that the setpoint entirely defines and maintains the resting potential, explaining its robustness, is load-bearing. The manuscript must show quantitative agreement with measured resting-potential stability during cell growth or changes in membrane area; otherwise the independence from classic models cannot be established.

    Authors: We agree that quantitative demonstration of robustness is essential. The setpoint is fixed by the thermodynamic balance between the equivalent electric field and the slow-ion chemical potentials; because this balance is independent of total membrane capacitance or area, V_rest remains constant when membrane area increases during growth. The revised manuscript now includes a short quantitative section that inserts literature values for membrane-area expansion in developing neurons and shows that the predicted V_rest variation stays within the experimentally reported range (typically <2 mV), again without invoking the parameter adjustments required by classic conductance-based models. revision: yes

Circularity Check

0 steps flagged

Derivation of resting potential presented as independent first-principles result with no evident reduction to inputs

full rationale

The paper explicitly claims to derive the resting potential from first principles of science, showing it is unrelated to any ad hoc linear combination of mobilities or reversal potentials as in the GHK equation. It introduces an electrical-thermodynamic control circuit whose setpoint defines the resting potential, and states that this resolves issues with classic models by removing untested ad hoc hypotheses while incorporating recent experimental discoveries. No equations, self-citations, or fitted parameters are quoted in the provided text that reduce the claimed result to a renaming, fit, or self-referential definition by construction. The central premise remains independent of the target GHK form and is presented as self-contained against external benchmarks, making this the normal honest finding of no significant circularity.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

The central claim rests primarily on the domain assumption that biological charge carriers are slow positive ions and that certain ad hoc hypotheses may be discarded; no explicit free parameters or invented entities are identified in the abstract.

axioms (1)
  • domain assumption Biology uses slow, positively charged ions rather than electrons as charge carriers.
    Explicitly stated in the abstract as the physical basis that must be taken into account.

pith-pipeline@v0.9.0 · 5800 in / 1282 out tokens · 63220 ms · 2026-05-19T04:23:23.729098+00:00 · methodology

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Lean theorems connected to this paper

Citations machine-checked in the Pith Canon. Every link opens the source theorem in the public Lean library.

What do these tags mean?
matches
The paper's claim is directly supported by a theorem in the formal canon.
supports
The theorem supports part of the paper's argument, but the paper may add assumptions or extra steps.
extends
The paper goes beyond the formal theorem; the theorem is a base layer rather than the whole result.
uses
The paper appears to rely on the theorem as machinery.
contradicts
The paper's claim conflicts with a theorem or certificate in the canon.
unclear
Pith found a possible connection, but the passage is too broad, indirect, or ambiguous to say the theorem truly supports the claim.

Reference graph

Works this paper leans on

34 extracted references · 34 canonical work pages

  1. [1]

    The McGraw-Hill Medical, New York Chicago etc

    Kandel, E.R., Schwartz, J.H., Jessell, T.M., Siegelbaum, S.A., Hudspeth, A.J.: Principles of Neural Science, 5th edn. The McGraw-Hill Medical, New York Chicago etc. (2013)

  2. [2]

    6 (2024)

    Tamagawa, H., Sasaki, M., Lin, W., Delalande, B.: Is the membrane permeabil- ity the primary property for the membrane potential generation? Mod Concept Material Sci. 6 (2024)

  3. [3]

    The Physio- logical Society, Seattle, WA 98195, USA (2022)

    Brown, A.M.: A Companion Guide to the Hodgkin-Huxley Papers. The Physio- logical Society, Seattle, WA 98195, USA (2022)

  4. [4]

    Feher, J.: The Origin of the Resting Membrane Potential, Second edition edn., pp. 255–264. Academic Press, Boston (2017). https://doi.org/10.1016/B978-0-12-800883-6.00023-9 . https://www.sciencedirect.com/science/article/pii/B9780128008836000239

  5. [5]

    Progress in Biophysics and Molecular Biology 162, 2–25 (2021) https://doi.org/10.1016/ j.pbiomolbio.2020.10.001

    Schneider, M.F.: Living systems approached from physical principles. Progress in Biophysics and Molecular Biology 162, 2–25 (2021) https://doi.org/10.1016/ j.pbiomolbio.2020.10.001 . On the Physics of Excitable Media. Waves in Soft and Living Matter, their Transmission at the Synapse and their Cooperation in the Brain

  6. [6]

    Applied Physical Sciences 45, 11826–11831 (2017) https://doi.org/10

    Podobnik, B., Jusup, M., Tiganj, Z., Wangi, W.-X., Buld, J.M., Stanley, H.E.: Biological conservation law as an emerging functionality in dynamical neuronal networks. Applied Physical Sciences 45, 11826–11831 (2017) https://doi.org/10. 35 1073/pnas.1705704114

  7. [7]

    Physics A: Statistical Mechanics and its Applications 1, (2025) https://doi.org/10.2139/ssrn.5217729

    V´ egh, J.: The non-ordinary laws of physics describing life. Physics A: Statistical Mechanics and its Applications 1, (2025) https://doi.org/10.2139/ssrn.5217729

  8. [8]

    Nat Rev Neurosci 11, 552–562 (2010) https://doi.org/10.1038/nrn2852

    Rasband, M.: The axon initial segment and the maintenance of neuronal polarity. Nat Rev Neurosci 11, 552–562 (2010) https://doi.org/10.1038/nrn2852

  9. [9]

    Nature Neuroscience 11, 178–186 (2008) https://doi.org/ 10.1038/nn2040

    Kole, M.H.P., Ilschner, S.U., Kampa, B.M., Williams, S.R., Ruben, P.C., Stuart, G.J.: Action potential generation requires a high sodium channel density in the axon initial segment. Nature Neuroscience 11, 178–186 (2008) https://doi.org/ 10.1038/nn2040

  10. [10]

    Neuron 73(2), 235–247 (2012) https://doi.org/10.1016/j.neuron.2012.01.007

    Kole, M.P., Stuart, G.: Signal processing in the axon initial segment. Neuron 73(2), 235–247 (2012) https://doi.org/10.1016/j.neuron.2012.01.007

  11. [11]

    Journal of Neuro- science 38(9), 2135–2145 (2018) https://doi.org/10.1523/JNEUROSCI.1922-17

    Leterrier, C.: The axon initial segment: An updated viewpoint. Journal of Neuro- science 38(9), 2135–2145 (2018) https://doi.org/10.1523/JNEUROSCI.1922-17. 2018

  12. [12]

    Annals of the New York Academy of Sciences 1420 (2018) https://doi

    Huang, C.Y.-M., Rasband, M.N.: Axon initial segments: structure, function, and disease. Annals of the New York Academy of Sciences 1420 (2018) https://doi. org/10.1111/nyas.13718

  13. [13]

    Proceedings of the National Academy of Sciences 118(18), 2008173118 (2021) https://doi.org/10.1073/pnas.2008173118

    Levy, W.B., Calvert, V.G.: Communication consumes 35 times more energy than computation in the human cortex, but both costs are needed to predict synapse number. Proceedings of the National Academy of Sciences 118(18), 2008173118 (2021) https://doi.org/10.1073/pnas.2008173118

  14. [14]

    https: //jvegh.github.io/DANCES/ (Accessed on July 8, 2025) (2025)

    V´ egh, J.: Dynamic Abstract Neural Computing with Electronic Simulation. https: //jvegh.github.io/DANCES/ (Accessed on July 8, 2025) (2025)

  15. [15]

    Bulletin of Mathemat- ical Biology 52(1), 5–23 (1990)

    Rinzel, J.: Discussion: Electrical excitability of cells, theory and experiment: Review of the hodgkin-huxley foundation and an update. Bulletin of Mathemat- ical Biology 52(1), 5–23 (1990)

  16. [16]

    Membranes 4(2), 257–274 (2014) https://doi.org/10.3390/membranes4020257

    Tamagawa, H., Morita, S.: Membrane potential generated by ion adsorption. Membranes 4(2), 257–274 (2014) https://doi.org/10.3390/membranes4020257

  17. [17]

    Journal of Membrane Science 549, 616–630 (2018) https://doi.org/ 10.1016/j.memsci.2017.11.073

    Ryzhkov, I.I., Lebedev, D.V., Solodovnichenko, V.S., Minakov, A.V., Simunin, M.M.: On the origin of membrane potential in membranes with polarizable nanopores. Journal of Membrane Science 549, 616–630 (2018) https://doi.org/ 10.1016/j.memsci.2017.11.073

  18. [18]

    2021.10.004

    Hirohisa Tamagawa and Titus Mulembo and Vera Maura Fernandes de Lima and Wolfgang Hanke: Analyses of HH and GHK equations with another perspective: Can ion adsorption also govern trans-membrane potential? Progress in Biophysics 36 and Molecular Biology 167, 3–11 (2021) https://doi.org/10.1016/j.pbiomolbio. 2021.10.004

  19. [19]

    Acta Biotheoretica 71(15) (2023) https: //doi.org/10.1007/s10441-023-09467-5

    Tamagawa, H., Nakahata, T., Sugimori, R., Delalande, B., T, M.: The Membrane Potential Has a Primary Key Equation. Acta Biotheoretica 71(15) (2023) https: //doi.org/10.1007/s10441-023-09467-5

  20. [20]

    Schr¨ odinger, E.: IS LIFE BASED ON THE LAWS OF PHYSICS?, pp. 76–85. Cambridge University Press, Canto (1992).https://archive.org/details/WhatIsLife- EdwardSchrodinger/

  21. [21]

    Oxford University Press, New York, Oxford (1999)

    Koch, C.: Biophysics of Computation. Oxford University Press, New York, Oxford (1999)

  22. [22]

    Biophysical Journal 124 (2025) https://doi.org/10.1016/j.bpj.2024.11.557

    Baumgart, A., Clarke, J.R., Cranfield, G.C., Zerlotti, R., Buoninsegni, F.T.: Membrane binding of hydrophobic ions: Dipole potential revisited. Biophysical Journal 124 (2025) https://doi.org/10.1016/j.bpj.2024.11.557

  23. [23]

    Biophysical Journal 47, 673–678 (1985)

    Oshima, Hiroyuki and Ohki, Shinpei: Donnan potential and surface potential of a charged membrane. Biophysical Journal 47, 673–678 (1985)

  24. [24]

    Current Opinion in Electrochemistry39, 101258 (2023) https://doi.org/10.1016/j.coelec.2023.101258

    Doblhoff-Dier, K., Koper, M.T.M.: Electric double layer of pt(111): Known unknowns and unknown knowns. Current Opinion in Electrochemistry39, 101258 (2023) https://doi.org/10.1016/j.coelec.2023.101258

  25. [25]

    Mas- sachusetts Institute of Technology, Cambridge, Massachusetts and London, England (1995)

    Johnston, D., Wu, S.M.-S.: Foundations of Cellular Neurophysiology. Mas- sachusetts Institute of Technology, Cambridge, Massachusetts and London, England (1995)

  26. [26]

    New York: Garland Science, New York (2002)

    Alberts, B., Johnson, A., Lewis, J., al.: Molecular Biology of the Cell. New York: Garland Science, New York (2002). https://www.ncbi.nlm.nih.gov/books/ NBK26910/

  27. [27]

    and Freeman, Benny D

    Gokturk, Pinar Aydogan and Sujanani, Rahul and Qian, Jin and Wang, Ye and Katz, Lynn E. and Freeman, Benny D. and Crumlin, Ethan J: The Donnan potential revealed. Nature Communications 13 (2022) https://doi.org/10.1038/ s41467-022-33592-3

  28. [28]

    Hodgkin, A.L., Huxley, A.F.: A quantitative description of membrane current and its application to conduction and excitation in nerve. J. Physiol. 117, 500–544 (1952)

  29. [29]

    Nature Reviews Neuroscience 19, 566–578 (2018) https://doi.org/ 10.1038/s41583-018-0038-8

    Bassett, D.S., Zurn, P., Gold, J.I.: On the nature and use of models in network neuroscience. Nature Reviews Neuroscience 19, 566–578 (2018) https://doi.org/ 10.1038/s41583-018-0038-8

  30. [30]

    37 Applied Sciences 1 (2025) https://doi.org/https://www.mdpi.com/2076-3417/ 15/11/5805/pdf

    V´ egh, J.: On implementing technomorph biology for inefficient computing. 37 Applied Sciences 1 (2025) https://doi.org/https://www.mdpi.com/2076-3417/ 15/11/5805/pdf

  31. [31]

    Algorithms 1 (2025) https://doi.org/10.20944/preprints202506.1290.v1

    V´ egh, J.: Algorithm for describing neuronal electric operation. Algorithms 1 (2025) https://doi.org/10.20944/preprints202506.1290.v1

  32. [32]

    Liverpool University Press, Liverpool, UK, 1964 (1964)

    Hodgkin, A.L.: The Conduction of the Nervous Impulse. Liverpool University Press, Liverpool, UK, 1964 (1964)

  33. [33]

    Abbott, B.C., Hill, A.V., Howarth, J.V.: The positive and negative heat produc- tion associated with a nerve impulse. Proc. R. Soc. London. B. 148, 149–187 (1958)

  34. [34]

    In: Byrne, J.H., Heidelberger, R., Waxham, M.N

    McCormick, D.A.: Chapter 12 - membrane potential and action potential. In: Byrne, J.H., Heidelberger, R., Waxham, M.N. (eds.) From Molecules to Networks (Third Edition), Third edition edn., pp. 351–376. Academic Press, Boston (2014). https://doi.org/10.1016/B978-0-12-397179-1.00012-9 . https://www.sciencedirect.com/science/article/pii/B9780123971791000129 38