Objective and comprehensive re-evaluation of anxiety-like behaviors in mice using the Behavior Atlas

Liu, Nan; Han, Yaning; Ding, Hui; Huang, Kang; Wei, Pengfei; Wang, Liping

doi:10.1016/j.bbrc.2021.03.125

Cited by 11 publications

(18 citation statements)

References 26 publications

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“…And our analysis of self-grooming still relies on manual analysis. One resolution in the future is to use a 3D animal motion-capture system and machine learning analysis framework to explore this type of spontaneous behavior ( Huang et al, 2021 ), which can provide more intact information for understanding self-grooming and anxiety ( Liu et al, 2021 ). It also can save the experimenter a lot of time and energy.…”

Section: Discussionmentioning

confidence: 99%

Dissection of the relationship between anxiety and stereotyped self-grooming using the Shank3B mutant autistic model, acute stress model and chronic pain model

Liu

Huang

et al. 2021

Neurobiology of Stress

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Section: Discussionmentioning

confidence: 99%

Dissection of the relationship between anxiety and stereotyped self-grooming using the Shank3B mutant autistic model, acute stress model and chronic pain model

Liu

Huang

et al. 2021

Neurobiology of Stress

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“…4e left). The dimensionally reduced distance component by uniform manifold approximation and projection (UMAP) is beneficial to improve the separation of behavior atlas verified by our previous studies 11–14,32 . But with the increase of data scale, the computational consumption of UMAP would be unacceptable because of limited memory space, which is the second question.…”

Section: Resultsmentioning

confidence: 74%

“…1a). This approach captures the animals covering more view angles and helps to overcome the challenge of frequent occlusion [11][12][13][14] . The camera array is used to capture images of a checkerboard for camera calibration, followed by videos of two free-moving animals for the social behavior test (Video capture phase 1, Fig.…”

Section: Resultsmentioning

confidence: 99%

“…Here we have presented SBeA, a framework for 3D pose tracking and behavior mapping of multiple free-social animals. SBeA builds upon the BeA framework, extending it to enable multi-animal pose estimation and social behavior clustering [11][12][13][14] . The method reduces the labor required for annotation by up to fifty percent compared to traditional approaches for pose estimation.…”

Section: Discussionmentioning

confidence: 99%

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Social Behavior Atlas: A computational framework for tracking and mapping 3D close interactions of free-moving animals

Han

Chen

Wang

et al. 2023

Preprint

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The study of social behaviors in animals is essential for understanding their survival and reproductive strategies. However, accurately tracking and analyzing the social interactions of free-moving animals has remained a challenge. Existing multi-animal pose estimation techniques suffer from drawbacks such as the need for extensive manual annotation and difficulty in discriminating between similar-looking animals in close social interactions. In this paper, we present the Social Behavior Atlas (SBeA), a novel computational framework that solves these challenges by employing a deep learning-based video instance segmentation model, 3D pose reconstruction, and unsupervised dynamic behavioral clustering. SBeA framework also involves a multi-camera setup to prevent occlusion, and a novel approach to identify individual animals in close social interactions. We demonstrate the effectiveness of SBeA in tracking and mapping the 3D close interactions of free-moving animals using the example of genetic mutant mice, birds, and dogs. Our results show that SBeA is capable of identifying subtle social interaction abnormalities, and the models and frameworks developed can be applied to a wide range of animal species. SBeA is a powerful tool for researchers in the fields of neuroscience and ecology to study animal social behaviors with a high degree of accuracy and reliability.

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“…We propose a bidirectional transfer learning identity recognition strategy, achieving zeroshot annotation of multi-animal identity recognition with an accuracy rate exceeding 90% [15][16][17] . We extend Behavior Atlas, an unsupervised dynamic behavior decomposition framework, from a single animal to multiple animals, which achieves unsupervised fine-grained social behavior module clustering with a purity exceeding 80% 10,18,19 . In the study of free social behavior between autism model animals and normal animals, the application of SBeA enables automatically identifying of animals with social abnormalities and explores the precise characteristics of these abnormal social behaviors.…”

Section: Introductionmentioning

confidence: 99%

Social Behavior Atlas: A few-shot learning framework for multi-animal 3D social pose estimation, identification, and behavior embedding

Wei

Han

Chen

et al. 2023

Preprint

Self Cite

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The fact that multi-animal behavior quantification is still technically challenging nowadays greatly limits the accuracy and granularity of social behavior analysis. Data labeling of deep-learning-based approaches can be incredibly laborious, especially when multiple animals closely interact with each other, under which circumstances animal identity switching and body occlusions are likely to happen. To overcome the challenge, we designed a novel framework - Social Behavior Atlas (SBeA) and it shows promising results. SBeA utilizes a much smaller number of labeled frames for multi-animal 3D pose estimation, achieves label-free identification recognition, and successfully applies unsupervised dynamic learning for social behavior classification. Our results also demonstrate that SBeA is capable of achieving high performance across various species using existing customized datasets. Therefore, we can build a multi-animal behavior atlas. To start with, we construct a social behavior atlas for autism spectrum disorder (ASD) knockout mice, and SBeA reveals several behavioral biomarkers which were neglected before. These findings highlight the immense potential of SBeA for quantifying subtle social behaviors and provide a new paradigm in the fields of neuroscience and ecology.

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Objective and comprehensive re-evaluation of anxiety-like behaviors in mice using the Behavior Atlas

Cited by 11 publications

References 26 publications

Dissection of the relationship between anxiety and stereotyped self-grooming using the Shank3B mutant autistic model, acute stress model and chronic pain model

Dissection of the relationship between anxiety and stereotyped self-grooming using the Shank3B mutant autistic model, acute stress model and chronic pain model

Social Behavior Atlas: A computational framework for tracking and mapping 3D close interactions of free-moving animals

Social Behavior Atlas: A few-shot learning framework for multi-animal 3D social pose estimation, identification, and behavior embedding

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