Efficient simulations of stretch growth axon based on improved HH model

ABSTRACT

Objective

According to recent studies, synaptic connections by axons formed can resist stronger mechanical stresses. A large number of nerve tissues with regular growth can be achieved quickly by appropriately managing the pulling pace and force. However, currently there are few studies on the physiological characteristics of stretching growth axons. Until now, there is no mature technology for determining whether the axons can normally transmit neural signals following continuous mechanical stimulation. In this paper, an improved HH model was proposed to investigate the effect of mechanical stimuli on stretched axons and synapses.

Methods

First, we add the link between membrane capacitance and diameter to the standard HH model and the fundamental concept of capacitance. Then, unmyelinated stretch growth axons with different lengths were simulated in this model.

Results

After mechanical pulling stimulation, the improved model successfully replicated the generation and propagation of action potentials in several different axon segments. This increase in length accompanying an increase in diameter due to stretch growth. When the stretching growth axon was stimulated again by traction, the membrane capacitance rapidly increased from the constant value and the inward current was large enough to depolarize the membrane and produce an action potential. After stretching, nerve fibers could still receive signals sent by other neuron cells and complete the signal transmission.

Discussion

This proposed research can help to optimize stretching axon culture conditions, avoid mechanical force damage to nerve tissue, and achieve a more effective nerve tissue culture process.

KEYWORDS:

• Axon stretch growth
• HH model
• mechanical stimulation
• action potential
• signal transmission

Acknowledgments

The authors acknowledge the financial support from the National Natural Science Foundation of China (Grant Nos. 52005169 & Grant Nos.81902299).

Disclosure statement

No potential conflict of interest was reported by the authors.

Data availability statement

The authors confirm that the data supporting the findings of this study are available within the article.Source code generated and used for this study is available on request from the corresponding author.

Authors’ contribution

Xiao Li: Investigation, Methodology, Writing – original draft, Writing – review and editing, Project administration, Funding acquisition. Xianxin Dong: Investigation, Methodology, Formal analysis, Visualization, Writing – review and editing. Xikai Tu: Investigation, Writing – review and editing. Hailong Huang: Investigation, Methodology, Writing – review and editing, Project administration, Funding acquisition.

Additional information

Funding

The work was supported by the National Natural Science Foundation of China [52005169 & 81902299].