golgi: an open-source graphical platform for image-to-recruitment modeling of peripheral nerve stimulation

Computational models of peripheral nerve stimulation-coupling finite-element bioelectric fields to biophysical axon models-are essential for designing electrodes and waveforms for neuromodulation, but established open tools are code-first, assume substantial modeling expertise, and often depend on commercial finite-element solvers. We present golgi, an open-source platform that takes a peripheral nerve from image to stimulated fiber population.

golgi integrates the full pipeline through a single graphical interface, with an equivalent scriptable Python API and command-line interface: image segmentation (or import of surfaces or masks), automated multi-region tetrahedral meshing, anisotropic finite-element solution of the extracellular field with explicit perineurium contact impedance, generation of realistic fiber populations and their three-dimensional trajectories (straight, or curved via a quasi-static streamline solver), and biophysical activation thresholds through interchangeable NEURON and a GPU-accelerated surrogate backend.

We demonstrate golgi on extruded multifascicular swine and human cervical vagus nerves and on real three-dimensional, branching human and rabbit vagus nerves reconstructed from micro-computed tomography. It reproduces the physiological fiber-diameter recruitment order, quantifies fascicular selectivity and current steering with a multi-contact cuff, and resolves anatomically defined branches. Selectively engaging a vagal cardiac branch from a proximal cuff depends on anatomy: in the rabbit, whose cardiac fibers are predominantly small and whose superior cardiac branch forms a discrete tract, current steering isolates even its small cardiac (B-type) fibers; in the human only large myelinated fibers are separable, because the high thresholds of small cardiac fibers force currents that also recruit off-target fibers.

Every study exports as an integrity-hashed, self-contained bundle whose finite-element-to-recruitment provenance is verifiable byte-for-byte-a reproducibility guarantee absent from existing tools. By combining non-specialist usability, anatomical realism, and verifiable reproducibility, golgi lowers the barrier to in-silico peripheral nerve stimulation modeling. golgi is freely available as open-source software.