Simulating bidirectional peripheral neural interfaces in EIDORS.

Area of Science:

• Neuroscience
• Biomedical Engineering
• Computational Biology

Background:

• Bioelectronic neural interfaces require simultaneous sensing and stimulation within nerves for adaptive therapy.
• Current peripheral neural interfaces offer limited specificity in electrical recordings of nerve activity.
• Understanding current spread in complex neural environments is crucial for signal integration.

Purpose of the Study:

• To develop and validate a computational model for simulating extracellular stimulation and recording in peripheral nerves.
• To enhance the specificity of neural recordings for improved therapeutic interventions.
• To investigate the application of the model in the context of pelvic nerve stimulation for voiding disorders.

Main Methods:

• Utilized the open-source EIDORS package for computational modeling.
• Developed biophysical models for myelinated and unmyelinated axons.
• Simulated spontaneous and electrically-evoked nerve activity recordings.
• Modeled the complex, heterogeneous, and anisotropic extracellular space of the pelvic nerve.

Main Results:

• Stimulus thresholds were found to be highly dependent on nerve fiber type and electrode-fiber distance.
• The model accurately simulated extracellular recordings in complex neural geometries.
• Demonstrated the capability to differentiate contributions of various neural populations to recordings.

Conclusions:

• The EIDORS package provides an accurate platform for simulating extracellular recordings in complex neural tissues.
• This modeling approach can improve the specificity and efficacy of bioelectronic neural interfaces.
• The developed model shows promise for optimizing therapeutic electrical stimulation in the pelvic nerve and other neural targets.