Neuronal electricality founded in murburn-thermodynamic principles: 1. Background and basic theoretical formulation

TL;DR

This paper introduces a novel thermodynamic and redox-based framework for understanding neuronal electrical activity, challenging ion-centric models and linking metabolism directly to electrophysiological behavior.

Contribution

It develops a unified reaction-transport-relaxation model based on redox principles, providing new mechanistic insights into neuronal signaling and excitability.

Findings

Derives a single equation capturing resting potential, excitability, and signal propagation.

Explains threshold behavior and spike waveforms through nonlinear redox kinetics.

Provides a chemically grounded alternative to ion-based neuronal models.

Abstract

Trans-membrane gradients and fluxes of cations (H+, Na+, K+, etc.) were deemed to be the rationale of electrical activities of aerobic cells/organelles, as per classical perceptions. Murburn concept (an umbrella of theorization based in stochastic redox processes) has afforded novel models for various metabolic, bioenergetic and electrophysiological outcomes. Herein, the foundational mechanistic formalisms for the electrical activities of neurons that lead signal relay along the axonal length are provided. Electron Holding potential (EHP), a dimensionless field/state variable (related logarithmically to electron chemical potential) is used to explain neuronal activity. By combining local redox relaxation dynamics with spatial transport driven by thermodynamic gradients, we derive a unified reaction-transport-relaxation equation that captures resting potential, excitability, waveform generation, and signal propagation within a single framework. Nonlinear local redox kinetics naturally give rise to threshold behavior, all-or-none responses, and stable spike waveforms. The framework accommodates known physiological variability and provides a direct bridge between metabolic/redox state and electrophysiological behavior. This work establishes a chemically grounded, non-circular alternative to ion-centric models and offers testable predictions for neuronal dynamics across biological systems. In the second part of this work, we compare the new theory with existing systems, provide further evidence, simulations and describe elaborate agendas for falsification and validation.