Automatically annotated motion tracking identifies a distinct social behavioral profile following chronic social defeat stress

Joeri Bordes, Lucas Miranda, Maya Reinhardt, Sowmya Narayan, Jakob Hartmann, Emily L. Newman, Lea Maria Brix, Lotte Doeselaar, Clara Engelhardt, Larissa Dillmann, Shiladitya Mitra, Kerry J. Ressler, Benno Pütz, Felix Agakov, Bertram Müller-Myhsok () and Mathias V. Schmidt ()
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Joeri Bordes: Max Planck Institute of Psychiatry
Lucas Miranda: Max Planck Institute of Psychiatry
Maya Reinhardt: Max Planck Institute of Psychiatry
Sowmya Narayan: Max Planck Institute of Psychiatry
Jakob Hartmann: Harvard Medical School, McLean Hospital
Emily L. Newman: Harvard Medical School, McLean Hospital
Lea Maria Brix: Max Planck Institute of Psychiatry
Lotte Doeselaar: Max Planck Institute of Psychiatry
Clara Engelhardt: Max Planck Institute of Psychiatry
Larissa Dillmann: Max Planck Institute of Psychiatry
Shiladitya Mitra: Max Planck Institute of Psychiatry
Kerry J. Ressler: Harvard Medical School, McLean Hospital
Benno Pütz: Max Planck Institute of Psychiatry
Felix Agakov: Pharmatics Limited
Bertram Müller-Myhsok: Max Planck Institute of Psychiatry
Mathias V. Schmidt: Max Planck Institute of Psychiatry

Nature Communications, 2023, vol. 14, issue 1, 1-19

Abstract: Abstract Severe stress exposure increases the risk of stress-related disorders such as major depressive disorder (MDD). An essential characteristic of MDD is the impairment of social functioning and lack of social motivation. Chronic social defeat stress is an established animal model for MDD research, which induces a cascade of physiological and behavioral changes. Current markerless pose estimation tools allow for more complex and naturalistic behavioral tests. Here, we introduce the open-source tool DeepOF to investigate the individual and social behavioral profile in mice by providing supervised and unsupervised pipelines using DeepLabCut-annotated pose estimation data. Applying this tool to chronic social defeat in male mice, the DeepOF supervised and unsupervised pipelines detect a distinct stress-induced social behavioral pattern, which was particularly observed at the beginning of a novel social encounter and fades with time due to habituation. In addition, while the classical social avoidance task does identify the stress-induced social behavioral differences, both DeepOF behavioral pipelines provide a clearer and more detailed profile. Moreover, DeepOF aims to facilitate reproducibility and unification of behavioral classification by providing an open-source tool, which can advance the study of rodent individual and social behavior, thereby enabling biological insights and, for example, subsequent drug development for psychiatric disorders.

Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-40040-3

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DOI: 10.1038/s41467-023-40040-3

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