Publication
Neuroprostheses based on electrical stimulation are becoming a therapeutic reality, dramatically improving the life of disabled people. They are based on neural interfaces that are designed to create an intimate contact with neural cells. These devices speak the language of electron currents, while the human nervous system uses ionic currents to communicate. A deep understanding of the complex interplay between these currents, during the electrical stimulation, is essential for the development of optimized neuroprostheses. Neural electrodes can have different geometries, placement within the nervous system, and the stimulation protocols (paradigms of use). This high-dimensional problem is not tractable by an empiric, brute-force approach and should be tackled by exact computational models, making use of our accumulated knowledge. In pursuit of this goal, a hybrid finite element method-NEURON modeling-is used for a solution of electrical field generated by stimulation, within the different neural structures having anisotropic conductivity, and a corresponding neural response computation. In this work, an important correction of perineurium electrical conductivity is computed. Models of median and sciatic nerves, innervating the hand and foot areas, relevant to the development of bionic hands and legs with sensory feedback, are implemented. The obtained results have the potential to optimize the design of neural interfaces, in terms of shape and number of stimulating contacts. Guidelines for the neurosurgical planning are proposed, by indicating the optimal number of implants for a specific nerve to obtain the best efficacy with the lowest invasiveness. The interpretation is proposed for one of the basic problems of neural interfaces, consisting in the change of the stimulation threshold due to fibrotic reaction of tissue. We show that it is possible to use human microstimulation as an experimental setup for testing of afferent stimulation paradigms, which can be translated to further chronic implants. In the future, models will have a key role in the decision of the most appropriate design of customized neuroprostheses, their optimal modality of use, understanding the effects that occur during their use, and minimizing animal and human experimentation.