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Key kinematic features in early training predict performance of adult female mice in a single pellet reaching and grasping task

View ORCID ProfileMichael Mykins, View ORCID ProfileEric Espinoza-Wade, View ORCID ProfileXu An, View ORCID ProfileBilly You Bun Lau, View ORCID ProfileKeerthi Krishnan
doi: https://doi.org/10.1101/2021.05.07.442851
Michael Mykins
1Department of Biochemistry & Cellular and Molecular Biology, University of Tennessee, Knoxville, TN 37996
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Eric Espinoza-Wade
2Department of Mechanical Engineering, California Polytechnic State University, San Luis Obispo, CA 93407
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Xu An
3Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724
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Billy You Bun Lau
1Department of Biochemistry & Cellular and Molecular Biology, University of Tennessee, Knoxville, TN 37996
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Keerthi Krishnan
1Department of Biochemistry & Cellular and Molecular Biology, University of Tennessee, Knoxville, TN 37996
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  • For correspondence: krishnan@utk.edu
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Abstract

Detailed analyses of overly trained animal models have been long employed to decipher foundational features of skilled motor tasks and their underlying neurobiology. However, initial trial-and-error features that ultimately give rise to skilled, stereotypic movements, and the underlying neurobiological basis of flexibility in learning, to stereotypic movement in adult animals are still unclear. Knowledge obtained from addressing these questions is crucial to improve quality of life in patients affected by movement disorders.

We sought to determine if known kinematic parameters of skilled movement in humans could predict learning of motor efficiency in mice during the single pellet reaching and grasping assay. Mice were food restricted to increase motivation to reach for a high reward food pellet. Their attempts to retrieve the pellet were recorded for 10 minutes a day for continuous 4 days. Individual successful and failed reaches for each mouse were manually tracked using Tracker Motion Analysis Software to extract time series data and kinematic features. We found the number of peaks and time to maximum velocity were strong predictors of individual variation in failure and success, respectively. Overall, our approach validates the use of select kinematic features to describe fine motor skill acquisition in mice and establishes peaks and time to maximum velocity as predictive measure of natural variation in motion efficiency in mice. This manually curated dataset, and kinematic parameters would be useful in comparing with pose estimation generated from deep learning approaches.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted May 09, 2021.
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Key kinematic features in early training predict performance of adult female mice in a single pellet reaching and grasping task
Michael Mykins, Eric Espinoza-Wade, Xu An, Billy You Bun Lau, Keerthi Krishnan
bioRxiv 2021.05.07.442851; doi: https://doi.org/10.1101/2021.05.07.442851
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Key kinematic features in early training predict performance of adult female mice in a single pellet reaching and grasping task
Michael Mykins, Eric Espinoza-Wade, Xu An, Billy You Bun Lau, Keerthi Krishnan
bioRxiv 2021.05.07.442851; doi: https://doi.org/10.1101/2021.05.07.442851

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