Neuromodulation of a peripheral nerve using fully polymeric cuff electrodes: understanding predictability of...

Area of Science:

• Biomedical Engineering
• Neuroscience
• Materials Science

Background:

• Peripheral nerve stimulation (PNS) has therapeutic potential but lacks spatial selectivity in mixed nerves.
• Current nerve interfaces often use metallic electrodes, which can cause imaging artifacts.

Purpose of the Study:

• To evaluate a fully polymeric, multipolar nerve cuff for selective fascicular activation.
• To assess the predictability of this selectivity using imaging-informed computational models.

Main Methods:

• Developed a flexible, fully polymeric nerve cuff from conductive elastomer.
• Evaluated ex vivo on rat sciatic nerves, recording compound nerve action potentials from individual fascicles.
• Used microCT imaging and ASCENT modeling pipeline for simulations.

Main Results:

• Demonstrated high fascicular selectivity (selectivity index > 0.65) in ex vivo experiments.
• Imaging-informed simulations partially reproduced selectivity but showed discrepancies.
• Simulations were sensitive to neuroanatomical variability, exceeding experimental sensitivity.

Conclusions:

• Fully polymeric conductive elastomer cuffs are effective alternatives to metallic interfaces for selective PNS.
• Combining microCT imaging and computational modeling refines predictive frameworks for PNS.
• Improved tissue and electrode modeling is crucial for advancing spatially selective PNS technologies.