The unified cross-disciplinary model of the operation of neurons

TL;DR

This paper proposes a unified cross-disciplinary model of neuronal operation that treats the membrane as a finite-width condenser interfacing two electrolyte segments. It derives resting potential from first principles using an equivalent thermodynamic electric field $E_{thermal}$ and a coupled Nernst–Planck/thermodynamic framework, arguing that traditional HH/GHK formalisms misinterpret ion-based currents and heat dynamics. The action potential is recast as a damped serial RC oscillator driven by slow ion currents, with energy and entropy described via a Carnot-like cycle and reversible elastic storage rather than pure Ohmic dissipation. By portraying neurons as multi-physics control systems (akin to PID controllers) with distinct resting and transient states, the work claims to resolve long-standing puzzles about heat absorption and leakage currents, offer a coherent account of ion selectivity and pumps, and provide a foundation for a true cross-disciplinary understanding of neural computing and energy use.

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 We also incorporate recent experimental discoveries into the outdated classic theoretical description.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.

Figures (16)

• Figure 1: The thermodynamic "electric field" depends on the membrane's thickness, see Eq.(\ref{['eq:NernstPlanckThermal2']}). The electric gradient depends on the charged layer's concentration and thickness; see Eq.(\ref{['eq:ElectricGradient']}). The dots mark measured data shown in Table \ref{['Tab:SummaryTable']}.
• Figure 2: http://hyperphysics.phy-astr.gsu.edu/hbase/ can be found by superposing the point charge fields of infinitesimal charge elements. This field can be facilitated by summing the fields of charged rings. “From Hyperphysics by Rod Nave, Georgia State University". © hyperphysics.phy-astr.gsu.edu/hbase/
• Figure 3: The oppositely charged parallel surfaces of the membrane are treated like conducting plates (infinite planes, neglecting fringing), then one can use Gauss's law to calculate the electric field between the plates. Presuming the plates are at equilibrium with zero electric fields inside the conductors, the result from a charged conducting surface can be used. “from Hyperphysics by Rod Nave, Georgia State University". © http://hyperphysics.phy-astr.gsu.edu/hbase/
• Figure 4: The neuronal membrane's electric field in the function of the distance from the membrane's surface. The thickness of the 'atomic layers' proximal to the membrane's surfaces are also shown. The electric field is linear inside the uniformly charged atomic ion layer on the surface and is described by Eq.(\ref{['eq:ElectricFieldOutside']}) in the electrolyte. For visibility, a layer thickness $0.5\ nm$ is assumed. For illustration, a simple capped ion channel in the membrane's wall is also displayed.
• Figure 5: The measured current, instead of conductance, (Fig. 2 from HodgkinHuxley:1952), demonstrating that two different physical effects result the rising and falling edge of the measured current.