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While mainly used for reducing seizures in epileptic patients, vagus nerve stimulation (VNS) has been implied to be capable of treating various other diseases. However, the therapeutic extent and control of neuromodulation for these conditions are still uncertain and are limited by the ability to predict neural activation responses upon targeting certain fascicles. Generally, VNS is administered through a bipolar helical cuff electrode implanted around the left vagus nerve. The electrode delivers pulses of electricity to the nerve to recruit axons. This work focuses on predicting percent activation and regions of activation based on different adjustable factors such as injected current amplitude and pulse width of stimuli and the activated region of the electrode. To achieve, a simplified finite element model was created using cylindrical geometries as nerve components with an addition of helical cuff electrodes. All of these components were encased in surrounding tissue with assumed properties similar to adipose. Electric potential distribution in the model was processed with an activating function defined along the axonal length which estimates the injected current at the nodes of Ranvier (NoR). These values were then enforced in the neuron simulation as a current clamp approximation applied at the NoR and the likelihood of an action potential was determined. Presence of action potentials were then detected to determine which axons were recruited in VNS. This preliminary work determined that electrode configurations can target specific fascicles in the nerve while amplitudes and pulse widths of stimuli contribute to the percentage of the nerve activated. This demonstrates the ability for patient-specific control over targeting fascicles. Additionally, this work presents initial steps to improving the model by using histological data to create a geometric-specific approach.
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