ASCENT

Basic ASCENT Usage

  • Getting Started
  • Running ASCENT
  • JSON Configuration Files
  • Publishing with ASCENT

Advanced ASCENT Usage

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

ASCENT Hierarchies

  • Code Hierarchy
    • Python Classes
    • Java Classes
    • NEURON Files
  • Data Hierarchy

Reference

  • Publications Utilizing ASCENT
  • References
  • ASCENT Validation
  • Changelog

External Links

  • ASCENT Publication
  • ASCENT on GitHub
  • The Grill Lab
  • NIH SPARC
ASCENT
  • Code Hierarchy
  • View page source

Code Hierarchy

  • Python Classes
    • Python classes for representing nerve morphology (Sample)
    • Simulation
    • Fiberset
    • Python utility classes
  • Java Classes
    • ModelWrapper Class
    • Making geometries in COMSOL (Part class)
    • Java utility classes
  • NEURON Files
    • NEURON simulations
    • Simulation hierarchy & run_controls.py
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© 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