Evaluating the Effect of Fibre Parameters on Neural Simulations Computed Using ASCENT

Area of Science:

• Computational neuroscience
• Biomedical engineering
• Neural engineering

Background:

• Computational models are vital for neural stimulation technique development, enabling in silico testing.
• Simulation parameter fidelity is critical for predictive accuracy in real-world applications.
• ASCENT is a pipeline combining COMSOL and NEURON for nerve and cuff simulations.

Purpose of the Study:

• To investigate the ASCENT simulation pipeline for neural stimulation.
• To identify key simulation parameters affecting fascicle-level selectivity.
• To provide recommendations for optimizing ASCENT neural simulations.

Main Methods:

• Focused on three simulation parameters: modelled fibre count, fascicle fibre ratio, and random number seed values.
• Evaluated the effect of these parameters on fascicle-level selectivity for a stimulation pulse.
• Utilized the ASCENT pipeline for simulating specific nerve and cuff configurations.

Main Results:

• Modelled fibre count significantly impacts calculated fascicle selectivity.
• Fibre diameter seed values also have a significant effect on fascicle selectivity.
• Fibre location seed and fascicle fibre ratio showed negligible effects on selectivity.

Conclusions:

• Fibre count and diameter seed are critical parameters for accurate fascicle selectivity simulations using ASCENT.
• ASCENT is a useful platform for selective stimulation method research, with specific parameter optimization needed.
• Recommendations are provided for researchers using ASCENT to improve the optimization of neural simulations.