Silhouette-Length-Scaled Gait Parameters for Motor Functional Analysis in Mice and Rats

Timotius I, Moceri S, Plank AC, Habermeyer J, Canneva F, Winkler J, Klucken J, Casadei N, Riess O, Eskofier B, von Hörsten S (2019)

Publication Language: English

Publication Type: Journal article, Original article

Publication year: 2019

Journal

eNeuro Society for Neuroscience

Book Volume: 6

Article Number: ENEURO.0100-19.2019

Journal Issue: 6

URI: https://www.eneuro.org/content/6/6/ENEURO.0100-19.2019

DOI: 10.1523/ENEURO.0100-19.2019

Open Access Link: https://www.eneuro.org/content/6/6/ENEURO.0100-19.2019

Abstract

Gait analysis of transgenic mice and rats modeling human diseases often suffers from the condition that those models exhibit genotype-driven differences in body size, weight, and length. Thus, we hypothesized that scaling by the silhouette length improves the reliability of gait analysis allowing normalization for individual body size differences. Here, we computed video-derived silhouette length and area parameters from a standard markerless gait analysis system using image-processing techniques. By using length- and area-derived data along with body weight and age, we systematically scaled individual gait parameters. We compared these different scaling approaches and report here that normalization for silhouette length improves the validity and reliability of gait analysis in general. The application of this silhouette length scaling to transgenic Huntington disease mice and Parkinson´s disease rats identifies the remaining differences reflecting more reliable, body length-independent motor functional differences. Overall, this emphasizes the need for silhouette-length-based intra-assay scaling as an improved standard approach in rodent gait analysis.

Authors with CRIS profile

Ivanna Timotius Lehrstuhl für Informatik 14 (Machine Learning and Data Analytics) Sandra Moceri Professur für Experimentelle Biomedizin Anne-Christine Plank Professur für Experimentelle Biomedizin Johanna Habermeyer Professur für Experimentelle Biomedizin Jürgen Winkler Professur für Molekulare Neurologie Jochen Klucken Department of Molecular Neurology Björn Eskofier Lehrstuhl für Informatik 14 (Machine Learning and Data Analytics) Stephan von Hörsten Professur für Experimentelle Biomedizin

Additional Organisation(s)

Machine Learning and Data Analytics Lab

Involved external institutions

Eberhard Karls Universität Tübingen DE Germany (DE)

How to cite

APA:

Timotius, I., Moceri, S., Plank, A.-C., Habermeyer, J., Canneva, F., Winkler, J.,... von Hörsten, S. (2019). Silhouette-Length-Scaled Gait Parameters for Motor Functional Analysis in Mice and Rats. eNeuro, 6(6). https://doi.org/10.1523/ENEURO.0100-19.2019

MLA:

Timotius, Ivanna, et al. "Silhouette-Length-Scaled Gait Parameters for Motor Functional Analysis in Mice and Rats." eNeuro 6.6 (2019).

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