Validated computational models predict vagus nerve stimulation thresholds in preclinical animals and humans

Area of Science:

• Neuroscience
• Computational Biology
• Biomedical Engineering

Background:

• Accurate modeling of peripheral nerve stimulation is crucial for understanding therapeutic effects and optimizing device design.
• Existing models often lack the precision to capture species-specific and individual variations in nerve responses.
• Automated simulation software offers a promising approach to address these limitations.

Purpose of the Study:

• To demonstrate the application of an open-source software for automated simulations to accurately characterize electrical nerve thresholds.
• To validate the software's ability to model nerve responses to electrical stimulation across different species and fiber types.
• To investigate the impact of individual nerve morphology on neural and physiological responses to vagus nerve stimulation (VNS).

Main Methods:

• Simulated vagus nerve stimulation (VNS) in humans, pigs, and rats using an open-source automated simulation software.
• Incorporated species-specific histology, device design features, published material properties, and realistic fiber models into the simulations.
• Validated model predictions against experimental data for activation thresholds and physiological responses.

Main Results:

• The models accurately predicted activation thresholds across species and myelinated fiber types, despite variations in nerve size and cuff geometry.
• Human VNS models accurately predicted thresholds for laryngeal motor fibers and captured inter-individual variability.
• Models for pig VNS consistently matched in vivo thresholds across various nerve types and physiological responses.
• Identified limitations in C fiber and small-diameter B fiber models, highlighting the need for improved models of unmyelinated nerve fibers.

Conclusions:

• Automated simulations significantly advance the standards for modeling peripheral nerve stimulation across diverse populations and species.
• Individual differences in nerve morphology demonstrably contribute to variability in neural and physiological responses to VNS.
• These refined models can accurately predict therapeutic mechanisms and potential side effects of VNS.