In the traditional Hodgkin-Huxley model, the nerve signal transmission is carried out through action potential along the neuronal axon. Action potential is generated by the diffusion of K⁺/Na⁺ ions in sodium-potassium pump nanochannels, while most of the other sodium-potassium pumps are stationary. This ionic fluid is an entropy-driven disordered fluid, and the ion diffusion process needs to consume large energy. The conduction of action potential behaves a domino-like propagation with a relatively slow speed (~1 m/s). Thus, traditional Hodgkin-Huxley model is not applicable to explain the rapid nerve signal transmission. 

Recently, an article published in Nano Research, entitled “Quantum-confined ion superfluid in nerve signal transmission”, has proposed a nerve signal transmission process based on quantum-confined ion superfluid (QISF). QISF is considered as an enthalpy-driven confined ordered fluid. The ultrafast Na⁺ and K⁺ ions transportation through all sodium-potassium pump nanochannels simultaneously in the membrane is without energy loss, and leads to QISF wave along the neuronal axon, which acts as an information medium in the ultrafast nerve signal transmission. The QISF and action potential processes are not coherent, and the action potential has nothing to do with the nerve signal transmission. It is also found that the de Broglie wavelength of K⁺ and Na⁺ is one order of magnitude smaller than the diameter of ions. In principle, the de Broglie wavelength of ions should be much larger than the diameter of ions, which indicates the de Broglie wavelength formula is not applicable to describe the quantum effects of ions in biological channels. The QISF process will not only provide a new view point for a reasonable explanation of ultrafast signal transmission in the nerves and brain, but also challenge the theory of matter wave for ions, molecules and particles. 

Link：https://doi.org/10.1007/s12274-019-2281-3 

E-mail: xqzhang@mail.ipc.ac.cn  

Action potential and QISF wave in nerve signal transmission (Image by Xiqi Zhang)