Multi-scale computational modeling of magnetoelectric nanoparticle-dispersed conductive nanofibers for peripheral nerve modulation

Introduction The electrical stimulation of peripheral nerves has shown the potential to restore impaired functions across a wide range of clinical scenarios. In most cases, though, the lack of selectivity of existing stimulation interfaces limits their applicability and can in some cases produce severe adverse effects. In addition, traditional stimulation requires physical connectors to a pulse generator that can add further biological and mechanical stress already linked to interfacing with physiological structures. This study focuses on the use of magnetoelectric nanoparticles (MENPs) embedded within conductive polymeric nanofibers as new wireless, highly selective, and minimally invasive interfaces for modulating peripheral nerves activity. Methods A step-by-step detailed characterization of the physical variables involved in this interaction, spanning from the nanometric single MENPs to micrometric multi-nanofibers structure with dispersed MENPs (poly-ME devices) and ending with the millimetric peripheral nerve, was proposed. MENPs concentration and distribution, device geometry, orientation, and size were systematically varied, and their effects on nerve fiber recruitment were quantified across myelinated and unmyelinated fiber types at different distances from the stimulating source. Results and discussion Our results evidenced how higher MENPs concentrations, higher stimulating source size and lower distance enhance the modulation capability of the poly-ME devices, with differences in stimulation capability between myelinated and unmyelinated nerve fibers. The solution of embedding MENPs in conductive polymer nanofibers enables higher MENPs loading than direct tissue injection, improves positional stability, and preserves biocompatibility, thereby offering a potential alternative for the engineering of MENPs as neuromodulation interfaces.