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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.

Publication ,  Journal Article
Musselman, ED; Cariello, JE; Grill, WM; Pelot, NA
Published in: PLoS computational biology
September 2021

Electrical stimulation and block of peripheral nerves hold great promise for treatment of a range of disease and disorders, but promising results from preclinical studies often fail to translate to successful clinical therapies. Differences in neural anatomy across species require different electrodes and stimulation parameters to achieve equivalent nerve responses, and accounting for the consequences of these factors is difficult. We describe the implementation, validation, and application of a standardized, modular, and scalable computational modeling pipeline for biophysical simulations of electrical activation and block of nerve fibers within peripheral nerves. The ASCENT (Automated Simulations to Characterize Electrical Nerve Thresholds) pipeline provides a suite of built-in capabilities for user control over the entire workflow, including libraries for parts to assemble electrodes, electrical properties of biological materials, previously published fiber models, and common stimulation waveforms. We validated the accuracy of ASCENT calculations, verified usability in beta release, and provide several compelling examples of ASCENT-implemented models. ASCENT will enable the reproducibility of simulation data, and it will be used as a component of integrated simulations with other models (e.g., organ system models), to interpret experimental results, and to design experimental and clinical interventions for the advancement of peripheral nerve stimulation therapies.

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Published In

PLoS computational biology

DOI

EISSN

1553-7358

ISSN

1553-734X

Publication Date

September 2021

Volume

17

Issue

9

Start / End Page

e1009285

Related Subject Headings

  • Reproducibility of Results
  • Peripheral Nerves
  • Electrodes
  • Electric Stimulation
  • Computational Biology
  • Bioinformatics
  • Automation
  • 08 Information and Computing Sciences
  • 06 Biological Sciences
  • 01 Mathematical Sciences
 

Citation

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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
Musselman, Eric D., Jake E. Cariello, Warren M. Grill, and Nicole A. Pelot. “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, no. 9 (September 2021): e1009285. https://doi.org/10.1371/journal.pcbi.1009285.
Musselman, Eric D., et al. “ASCENT (Automated Simulations to Characterize Electrical Nerve Thresholds): A pipeline for sample-specific computational modeling of electrical stimulation of peripheral nerves.PLoS Computational Biology, vol. 17, no. 9, Sept. 2021, p. e1009285. Epmc, doi:10.1371/journal.pcbi.1009285.

Published In

PLoS computational biology

DOI

EISSN

1553-7358

ISSN

1553-734X

Publication Date

September 2021

Volume

17

Issue

9

Start / End Page

e1009285

Related Subject Headings

  • Reproducibility of Results
  • Peripheral Nerves
  • Electrodes
  • Electric Stimulation
  • Computational Biology
  • Bioinformatics
  • Automation
  • 08 Information and Computing Sciences
  • 06 Biological Sciences
  • 01 Mathematical Sciences