On physical processes controlling nerve signalling

• Published in: The European physical journal. ST, Special topics Vol. 232; no. 20-22; pp. 3561 - 3576
• Main Authors: Mareš, Jiří J., Špička, Václav, Hubík, Pavel
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.12.2023; Springer Nature B.V
• Subjects: Atomic; Channels; Classical and Continuum Physics; Condensed Matter Physics; Dissipation; Foundations of Quantum Mechanics; Many Body Systems; Materials Science; Measurement Science and Instrumentation; Membranes; Molecular; Nerves; Non-Equilibrium Quantum Physics; Optical and Plasma Physics; Physics; Physics and Astronomy; Review; Signal transmission
• ISSN: 1951-6355; 1951-6401
• DOI: 10.1140/epjs/s11734-023-01045-7

The intensive experimental and theoretical research into the nerve signalling, which lasts for more than 230 years, has provided many valuable pieces of knowledge but no definite, really satisfying solution. Such an unfavourable state is due to the extraordinary complexity of this phenomenon and enormous technical difficulties encountered by experiments. Therefore, the problem till now persists as a challenging subject of research, being opened to various approaches. In the present contribution we are thus trying to summarize the accessible experimental findings and compare them critically with existing alternative theories. Finally, we attempt to compile a minimal model of the signal transmission in nerves, intentionally based only on well turned-out physically transparent arguments. The model combines two types of diffusion processes, microscopic and macroscopic ones, which act simultaneously and ensure nerve signalling. The full-time evolution of the corresponding action potential, from its emergence, increase, decrease and recovery phase, is controlled by the two types of membrane channels: by dissipative protein-based channels of Hodgkin–Huxley type and randomly created non-dissipative fissures in membranes. This approach could be useful for the efforts aiming to the improvement of the current models.