Quantification of natural behaviors

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Choosing a track system

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Quantify dynamics of behavior

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• Pereira, T. D., Shaevitz, J. W. & Murthy, M. Quantifying behavior to understand the brain. Nat Neurosci 23, 1537–1549 (2020). 量化行为：From tracking【点→椭圆→姿态估计】 to dynamics【有监督：决策树/随机森林→无监督：聚类→动力学模型→层级模型】

McCullough, M. H. & Goodhill, G. J. Unsupervised quantification of naturalistic animal behaviors for gaining insight into the brain. Current Opinion in Neurobiology 70, 89–100 (2021).

• Ye, J. et al. Hierarchical behavioral analysis framework as a platform for standardized quantitative identification of behaviors. Cell Reports 44, (2025).

Tracking

Centroid[点] 位置→ Elipse[椭圆] 朝向 →Multi-animal[身份识别] 社会或复杂环境的多个体追踪 → pose estimation single-animal[body-part landmarks]; multi-animal[spatiotemporal affinity]; 3D[深度相机，多相机拍摄]

Single-animal

DeepLabcut：Mathis et al, Nature Neuroscience 2018

Multi-animal

主要的问题是identity assignment ：如何跨时间帧地识别个体身份，解决遮挡/重叠/在过去帧消失/未检测到等问题

【reviews for in-depth analyses of classical multi-animal tracking methodology】

Anderson, D. J. & Perona, P. Toward a science of computational ethology. Neuron 84, 18–31 (2014).

Robie, A. A., Seagraves, K. M., Egnor, S. E. R. & Branson, K. Machine vision methods for analyzing social interactions. J. Exp. Biol. 220, 25–34 (2017). Sridhar, V. H., Roche, D. G. & Gingins, S. Tracktor: image‐based automated tracking of animal movement and behaviour. Methods Ecol. Evol. 10, 815–820 (2019).

SLEAP

Pereira et al, Nature Methods 2022