ASCENT

Basic ASCENT Usage

  • Getting Started
  • Running ASCENT
  • JSON Configuration Files
  • Publishing with ASCENT
    • Template for Reporting Methods in a Publication
    • Tool for Creating Dataset with ASCENT Data (SPARC’s Format)

Advanced ASCENT Usage

  • Creating Mock Morphology
  • Part Primitives and Custom Cuffs
  • Modeling Neural Recording
  • Convergence Analysis Example
  • Troubleshooting Guide

ASCENT Hierarchies

  • Code Hierarchy
  • Data Hierarchy

Reference

  • Publications Utilizing ASCENT
  • References
  • ASCENT Validation
  • Changelog

External Links

  • ASCENT Publication
  • ASCENT on GitHub
  • The Grill Lab
  • NIH SPARC
ASCENT
  • Publishing with ASCENT
  • View page source

Publishing with ASCENT

  • Template for Reporting Methods in a Publication
  • Tool for Creating Dataset with ASCENT Data (SPARC’s Format)
Previous Next

© Copyright 2021-2025, Duke University.

Musselman ED, Cariello JE, Grill WM, Pelot NA. ASCENT (Automated Simulations to Characterize Electrical Nerve Thresholds): A Pipeline for Sample-Specific Computational Modeling of Electrical Stimulation of Peripheral Nerves. PLoS Comput Biol [Internet]. 2021; Available from: https://doi.org/10.1371/journal.pcbi.1009285

Peña E, Pelot NA, Grill WM. Computational models of compound nerve action potentials: Efficient filter-based methods to quantify effects of tissue conductivities, conduction distance, and nerve fiber parameters. PLoS Comput Biol 20(3): e1011833. 2024; Available from: https://doi.org/10.1371/journal.pcbi.1011833

ASCENT software available from: https://github.com/wmglab-duke/ascent