Integrated light-based motor mapping with deep neural networks for tracking multiple limb movements in mice

Jonah A. Padawer-Curry; Adam Q. Bauer; Nischal Khanal

doi:10.1117/12.2610258

7 March 2022 Integrated light-based motor mapping with deep neural networks for tracking multiple limb movements in mice

Jonah A. Padawer-Curry, Adam Q. Bauer, Nischal Khanal

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Proceedings Volume PC11947, Optogenetics and Optical Manipulation 2022; PC119470A (2022) https://doi.org/10.1117/12.2610258
Event: SPIE BiOS, 2022, 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 3-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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Jonah A. Padawer-Curry, Adam Q. Bauer, and Nischal Khanal "Integrated light-based motor mapping with deep neural networks for tracking multiple limb movements in mice", Proc. SPIE PC11947, Optogenetics and Optical Manipulation 2022, PC119470A (7 March 2022); https://doi.org/10.1117/12.2610258

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KEYWORDS

Brain mapping

Neural networks

Brain

Animal model studies

Cameras

Electronics

Motion models

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