Light-based motor mapping of multiple limbs using deep learning reveals behaviorally relevant cortical motor representations

Nischal Khanal; Jonah Padawer-Curry; Kevin Schulte; Trevor Voss; Byungchan Kim; Annie R. Bice; Adam Q. Bauer

doi:10.1117/12.2649138

17 March 2023 Light-based motor mapping of multiple limbs using deep learning reveals behaviorally relevant cortical motor representations

Nischal Khanal, Jonah Padawer-Curry, Kevin Schulte, Trevor Voss, Byungchan Kim, Annie R. Bice, Adam Q. Bauer

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Proceedings Volume PC12366, Optogenetics and Optical Manipulation 2023; PC1236604 (2023) https://doi.org/10.1117/12.2649138
Event: SPIE BiOS, 2023, San Francisco, California, United States

Abstract

Recent developments in optogenetics allow for quick and minimally invasive methods of mapping functional brain circuits in animal models. DeepLabCut (DLC), a toolbox for markerless pose estimation, offers the ability to track features in three-dimensions. We demonstrate a hybrid method utilizing DLC and light-based, optogenetic motor mapping to concurrently localize motor representations of multiple limbs in mice. Our results suggest that behaviorally-relevant, motor movements involving multiple limbs reside in overlapping cortical representations of each limb. Applications of this technique include characterizing recovery of finer, articulated movements of affected limbs after stroke, or mapping brain network activity during naturalistic behavior.

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Nischal Khanal, Jonah Padawer-Curry, Kevin Schulte, Trevor Voss, Byungchan Kim, Annie R. Bice, and Adam Q. Bauer "Light-based motor mapping of multiple limbs using deep learning reveals behaviorally relevant cortical motor representations", Proc. SPIE PC12366, Optogenetics and Optical Manipulation 2023, PC1236604 (17 March 2023); https://doi.org/10.1117/12.2649138

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KEYWORDS

Brain mapping

Brain

Animal model studies

Cameras

Electronics

Motion models

Mouth

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