Automated light-based motor mapping of multiple limb movements in mice using deep neural networks

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

doi:10.1117/12.2578860

5 March 2021 Automated light-based motor mapping of multiple limb movements in mice using deep neural networks

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

Proceedings Volume 11629, Optical Techniques in Neurosurgery, Neurophotonics, and Optogenetics; 116290O (2021) https://doi.org/10.1117/12.2578860
Event: SPIE BiOS, 2021, Online Only

Abstract

Recent developments in optogenetics allow for quick and minimally-invasive methods of studying functional brain organization in animal models. DeepLabCut (DLC), a toolbox for markerless pose estimation, offers the ability to track user-defined features in 3-dimensions with human level accuracy. We demonstrate a hybrid method utilizing DLC and optogenetic motor mapping to localize the movements of multiple modalities to the mouse cortex. We outline a pipeline to map and characterize multiple motor representations in anesthetized and awake mice. Furthermore, we identify behaviorally-relevant motor movements of multiple limbs reside in overlapping cortical representations of the respective limbs.

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Citation Download Citation

Nischal Khanal, Kevin Schulte, Trevor Voss, Jonah Padawer-Curry, Byungchan Kim, Annie R. Bice, and Adam Bauer "Automated light-based motor mapping of multiple limb movements in mice using deep neural networks", Proc. SPIE 11629, Optical Techniques in Neurosurgery, Neurophotonics, and Optogenetics, 116290O (5 March 2021); https://doi.org/10.1117/12.2578860

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KEYWORDS

Brain mapping

Neural networks

Brain

Animal model studies

Cameras

Electronics

Motion estimation

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