Sign in
BioengineeringSoftwareX
Peer-reviewed journal article

golgi: open-source software for automated nerve model generation and recruitment simulation

David LungiD, Yuting JiaiD, Andrea MoroiD, Matteo FachinoiD, Max HaberbuschiD

Abstract

golgi is an open-source platform that takes a peripheral nerve from image to stimulated fiber population through a single graphical interface, with an equivalent scriptable Python API and command-line interface for batch and high-performance use. It integrates promptable image segmentation, automated multi-region tetrahedral meshing, anisotropic finite-element solution of the extracellular field with an explicit perineurium contact impedance, generation of realistic fiber populations and their three-dimensional trajectories, and biophysical activation thresholds through interchangeable backends-- NEURON (via PyFibers) and a GPU-accelerated surrogate (AxonML). Every study exports as an integrity-hashed bundle whose image-to-recruitment provenance is verifiable byte-for-byte. golgi lowers the barrier to in-silico peripheral nerve stimulation modeling for experimentalists and clinicians, using a fully open finite-element stack with no commercial dependencies.

02 /Specification & Classification

Click any tag to browse matching papers

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISLung '26Lung '26Couppey '24Felsheim '25Baden '18Geminiani '18
90% semantic matchBioengineering
David Lung, Yuting Jia, Roland Blumer+7 more·Journal of Neural Engineering·Oct 27, 2026