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    Area of Science:

    • Biomedical Engineering
    • Neuroscience
    • Computational Modeling

    Background:

    • Vestibular organs are crucial for gaze and posture stabilization.
    • Vestibular diseases severely impact quality of life.
    • Developing vestibular neuroprostheses is a promising therapeutic approach.

    Purpose of the Study:

    • To create a computational model of human vestibular nerve responses.
    • To enable in-silico testing of implantable vestibular prostheses.
    • To guide the optimization of neuroprosthetic device design.

    Main Methods:

    • Reconstructed a digital vestibular system model from anatomical data.
    • Utilized finite-element methods to compute electrical potentials from monopolar stimulation.
    • Simulated extracellular stimulation of vestibular, facial, and cochlear nerves.

    Main Results:

    • Analyzed electrode configurations for selectivity during stimulation.
    • Found electrode position significantly impacts nerve selectivity, while distance has minimal effect.
    • Validated the model by comparing simulated eye movements to experimental data.

    Conclusions:

    • The computational model accurately mimics human vestibular nerve responses.
    • Electrode placement is critical for selective nerve stimulation in vestibular prostheses.
    • The model provides valuable insights for designing effective vestibular neuroprostheses.