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Computational Software – ASCENT Sets Era of Nerve Stimulation

by Karishma Abhishek on Aug 30 2021 11:33 PM

Computational Software – ASCENT Sets Era of Nerve Stimulation
Electrical stimulation of nerves can be studied easily by even non-experts through an open-source computational platform ‘ASCENT’ as developed by the biomedical engineers at Duke University.
The study is as “ASCENT (Automated Simulations to Characterize Electrical Nerve Thresholds): A pipeline for sample-specific computational modeling of electrical stimulation of peripheral nerves” in the journal PLOS Computational Biology.

The software automates 3D electrical nerve stimulation modeling that may also allow scientists to predict the response of specific nerves to different patterns of stimulation. This may in turn help create accurate models of new therapies for a variety of diseases.

ASCENT and Electrical Nerve Stimulation

The nerve stimulation devices are similar to a pacemaker for the heart. They are implanted in the body by programming them to send targeted pulses of electricity into nerves. These electrical pulses change the signals to further regulate the organ functions in diseases.

“Despite promising preclinical data, translating nerve stimulation to the clinic is challenging because there is a lot of variability in neural anatomy between animals and humans and even person to person. These variabilities require choosing different electrodes or stimulation parameters to achieve a targeted response, which can be a bit of a guessing game,” says Nicole Pelot, a research director in the biomedical engineering lab of Warren Grill at Duke University.

The study team thereby claims that ASCENT is more accessible, reproducible, and efficient that allows one to break the complex system into its customizable sub-components.

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“A tool that is this specialized is usually inaccessible to more novice users. We hope ASCENT will help push the science forward as more researchers are able to design and interpret therapeutic interventions using computational models,” says Eric Musselman, a Ph.D. student in the Grill lab.

Source-Medindia


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