Understanding how genes, drugs and neural circuits influence behavior requires the ability to effectively organize information about similarities and differences within complex behavioral datasets. Motion Sequencing (MoSeq) is an ethologically inspired behavioral analysis method that identifies modular components of three-dimensional mouse body language called ‘syllables’. Here, we show that MoSeq effectively parses behavioral differences and captures similarities elicited by a panel of neuroactive and psychoactive drugs administered to a cohort of nearly 700 mice. MoSeq identifies syllables that are characteristic of individual drugs, a finding we leverage to reveal specific on- and off-target effects of both established and candidate therapeutics in a mouse model of autism spectrum disorder. These results demonstrate that MoSeq can meaningfully organize large-scale behavioral data, illustrate the power of a fundamentally modular description of behavior and suggest that behavioral syllables represent a new class of druggable target.

了解基因、药物和神经回路如何影响行为，需要能够有效地组织复杂行为数据集中的异同信息。运动测序 (MoSeq) 是一种受动物行为学启发的行为分析方法，可识别称为“音节”的三维鼠标肢体语言的模块化组件。在这里，我们展示了 MoSeq 有效地解析了行为差异并捕获了由一组向近 700 只小鼠给药的神经活性和精神活性药物引起的相似性。MoSeq 可识别具有单个药物特征的音节，我们利用这一发现来揭示已建立和候选疗法在自闭症谱系障碍小鼠模型中的特定靶向和脱靶效应。