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ASCENT (Automated Simulations to Characterize Electrical Nerve Thresholds): A pipeline for sample-specific computational modeling of electrical stimulation of peripheral nerves

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ASCENT: Automated Simulations to Characterize Electrical Nerve Thresholds

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User support: [email protected]

Funding: NIH SPARC OT2 OD025340, NIH SPARC 75N98022C00018

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ASCENT is an open source platform for simulating peripheral nerve stimulation. For more information, see the ASCENT documentation: https://wmglab-duke-ascent.readthedocs.io/en/latest/

Cite the ASCENT paper, PyFibers paper, and the DOI for the release of the repository used for your work. We encourage you to clone the most recent commit of the repository.

  • Cite the ASCENT paper:

    Musselman, E. D., Cariello, J. E., Grill, W. M., & Pelot, N. A. (2021). ASCENT (Automated Simulations to Characterize Electrical Nerve Thresholds): A pipeline for sample-specific computational modeling of electrical stimulation of peripheral nerves. PLOS Computational Biology, 17(9), e1009285. https://doi.org/10.1371/journal.pcbi.1009285

  • Cite the PyFibers paper:

    PyFibers paper citation will be available soon: See https://wmglab-duke.github.io/pyfibers/ for most recent updates

  • If you use the neural recording feature or SMALL_MRG_INTERPOLATION model, also cite the nerve recording modeling paper:

    Peña, E., Pelot, N.A., Grill, W.M., 2024. 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, e1011833. https://doi.org/10.1371/journal.pcbi.1011833

  • Cite the code (replace DOI and VERSION with the DOI and version number of code used. Latest release: DOI click to see all releases)

    Musselman, E. D., Cariello, J. E., Grill, W. M., & Pelot, N. A. (2025). wmglab-duke/ascent: ASCENT v1.5.0 (v1.5.0) [Computer software]. Zenodo. https://doi.org/10.5281/ZENODO.TBD.


The copyrights of this software are owned by Duke University. As such, two licenses for this software are offered:

  1. An open-source license under the GPLv2 license for non-commercial use (See LICENSE).

  2. A custom license with Duke University, for commercial use or for use without the GPLv2 license restrictions.

As a recipient of this software, you may choose which license to receive the code under. Outside contributions to the Duke-owned code base cannot be accepted unless the contributor transfers the copyright to those changes over to Duke University.

To enter a custom license agreement without the GPLv2 license restrictions, please contact the Digital Innovations department at Duke Office for Translation & Commercialization (https://olv.duke.edu/software/) at [email protected] with reference to "OTC File No. 7483" in your email.

Please note that this software is distributed AS IS, WITHOUT ANY WARRANTY; and without the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.

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ASCENT (Automated Simulations to Characterize Electrical Nerve Thresholds): A pipeline for sample-specific computational modeling of electrical stimulation of peripheral nerves

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