Topic: activating function

Personalized computational modeling is rapidly expanding the landscape of therapeutic possibilities for neurostimulation. However, applications are limited by the computational expense of electrophysiological simulations. Here, we introduce a new method for dramatically reducing these costs while preserving the accuracy of traditional axon simulations.The “activating function” (AF) is a linear quantity derived directly from the extracellular field potential that can predict axonal spike initiation in lieu of compartment-based models [1], but with limited accuracy. Thus, we developed a “general

Neural interfaces to peripheral nerves are increasingly employed for basic research, neuroprosthetics, and bioelectronic medicine (‘electroceuticals’). We previously established a pipeline for hybrid electromagnetic-electrophysiology modeling of nerve stimulation on the o2S2PARC platform for collaborative, FAIR, and reproducible computational neurosciences. It leverages histological data to generate a detailed anatomical model of the nerve microstructure and to functionalize it with populations of fiber neuro-dynamics models (myelinated/unmyelinated, statistical distributions of fiber types an