PT  - JOURNAL ARTICLE
AU  - J. Xu
AU  - S. Xu
AU  - F. Wang
AU  - S. Xu
TI  - On the delay in propagation of action potentials
AID  - 10.1101/763698
DP  - 2019 Jan 01
TA  - bioRxiv
PG  - 763698
4099  - http://biorxiv.org/content/early/2019/09/09/763698.short
4100  - http://biorxiv.org/content/early/2019/09/09/763698.full
AB  - The signal delay during the propagation of action potentials is one of the key issues in understanding the mechanisms of generation and propagation of neural signals. Here we reanalyzed related experimental data to demonstrate that action potentials in the propagation process along a myelinated axon are highly overlapped in the time scale. The shift in time of two successive signals from neighboring nodes, defined as delay time τ in this work, is only tens of microseconds (16.3-87.0 μs), thus is only ~ 0.8-4.4 % of the measured average duration of an action potential, ~ 2 ms. This fact may reveal a huge gap to the commonly accepted picture for propagation of neural signal. We could apply the electromagnetic soliton-like model to well explain this phenomenon, and attribute τ to the waiting time that one signal source (i.e., ion channel cluster at one node) needs to take when it generates an electromagnetic neural pulse with increasing intensity until the intensity is higher than a certain point so as to activate neighboring signal source. This viewpoint may shed some light on a better understanding of the exact physical mechanism of neural signal communication in a variety of biosystems.Statement of Significance The delay time during the propagation of action potentials is an important term in understanding the mechanisms of generation and propagation of neural signals. In this article we analyzed published experimental data and showed that action potentials from two neighboring Ranvier nodes are highly overlapped in time, with an average shift of tens of microseconds, which occupied only ~ 0.8-4.4 % of the average duration of an action potential (2 ms). The electromagnetic soliton-model seemed the best model to explain this phenomenon.The viewpoint of this article may shed some light on a better understanding of the exact physical mechanism of neural signal communication, and be tractive to researchers in a variety of fields, such as neuroscience, brain-computer interface, etc..