Neuronal electricality founded in murburn-thermodynamic principles: 2. Comparisons, evidenced explanations, and predictions
A radical paper claims neuronal electrical activity is driven by murburn redox dynamics, not ion channels.
In a provocative new paper on arXiv, researchers Kelath Murali Manoj and Nagamani Sukumar challenge the long-standing Hodgkin-Huxley model of neuronal electrical activity. They argue that action potentials arise not from ionic currents flowing through membrane channels, but from murburn (muddled electron transfer) thermodynamic processes — a redox-driven, chemistry-based mechanism. The paper, the second in a series, provides comparisons with existing models, quantitative predictions, and evidence from diverse experimental conditions.
The murburn framework treats neurons as reaction-transport systems where electron transfer kinetics and oxygen availability determine excitability. It predicts specific effects from changes in redox balance, solvent properties, and external fields — offering testable alternatives to ion channel theory. The model also generalizes to other excitable systems like cardiac tissue and photoreceptors, positioning excitability as a fundamental physicochemical phenomenon. While the work focuses on mid-scale dynamics, the authors call for future integration with quantum-level electron transfer and macroscopic signals like EEG. If validated, this could rewrite textbooks on neurophysiology.
- Proposes that neuronal firing is driven by murburn (redox) dynamics, not transmembrane ion flux.
- Links electrophysiological outputs (conduction velocity, threshold) to variables like oxygen availability and redox kinetics.
- Extends the framework to cardiac tissue, photoreceptors, and artificial redox-active materials.
- Offers direct experimental predictions to challenge the Hodgkin-Huxley model.
- Suggests excitability is a general reaction-transport phenomenon, not just a biological membrane property.
Why It Matters
Could overturn the foundation of neurobiology, impacting everything from brain-computer interfaces to neurological drug design.