Systematic evaluation of a predator stress model of depression in mice using a hierarchical 3D-motion learning framework

• Published in: Translational psychiatry Vol. 13; no. 1; p. 178
• Main Authors: Tseng, Yu-Ting, Zhao, Binghao, Ding, Hui, Liang, Lisha, Schaefke, Bernhard, Wang, Liping
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 25.05.2023; Nature Publishing Group
• Subjects: 13/56; 631/378; 64/60; 692/699; Animals; Behavior; Behavior, Animal; Behavioral Sciences; Biological Psychology; Depression - psychology; Disease Models, Animal; Female; Humans; Male; Medicine; Medicine & Public Health; Mice; Mice, Inbred C57BL; Neurosciences; Pharmacotherapy; Phenotype; Psychiatry; Social Behavior; Stress, Psychological - genetics
• ISSN: 2158-3188; 2158-3188
• DOI: 10.1038/s41398-023-02481-8

Investigation of the neurobiology of depression in humans depends on animal models that attempt to mimic specific features of the human disorder. However, frequently-used paradigms based on social stress cannot be easily applied to female mice which has led to a large sex bias in preclinical studies of depression. Furthermore, most studies focus on one or only a few behavioral assessments, with time and practical considerations prohibiting a comprehensive evaluation. In this study, we demonstrate that predator stress effectively induced depression-like behaviors in both male and female mice. By comparing predator stress and social defeat models, we observed that the former elicited a higher level of behavioral despair and the latter elicited more robust social avoidance. Furthermore, the use of machine learning (ML)-based spontaneous behavioral classification can distinguish mice subjected to one type of stress from another, and from non-stressed mice. We show that related patterns of spontaneous behaviors correspond to depression status as measured by canonical depression-like behaviors, which illustrates that depression-like symptoms can be predicted by ML-classified behavior patterns. Overall, our study confirms that the predator stress induced phenotype in mice is a good reflection of several important aspects of depression in humans and illustrates that ML-supported analysis can simultaneously evaluate multiple behavioral alterations in different animal models of depression, providing a more unbiased and holistic approach for the study of neuropsychiatric disorders.