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揭示幼鱼斑马鱼导航行为变异性的多尺度结构

Uncovering multiscale structure in the variability of larval zebrafish navigation.

机构信息

Sorbonne University, Paris Brain Institute (Institut du Cerveau), Inserm U1127, CNRS UMR 7225, Paris 75013, France.

Laboratoire de Physique de l'Ecole normale supérieure, École Normale Supérieure, Université Paris Sciences & Lettres, CNRS, Sorbonne Université, Université de Paris, Paris F-75005, France.

出版信息

Proc Natl Acad Sci U S A. 2024 Nov 19;121(47):e2410254121. doi: 10.1073/pnas.2410254121. Epub 2024 Nov 15.

Abstract

Animals chain movements into long-lived motor strategies, exhibiting variability across scales that reflects the interplay between internal states and environmental cues. To reveal structure in such variability, we build Markov models of movement sequences that bridge across timescales and enable a quantitative comparison of behavioral phenotypes among individuals. Applied to larval zebrafish responding to diverse sensory cues, we uncover a hierarchy of long-lived motor strategies, dominated by changes in orientation distinguishing cruising versus wandering strategies. Environmental cues induce preferences along these modes at the population level: while fish cruise in the light, they wander in response to aversive stimuli, or in search for appetitive prey. As our method encodes the behavioral dynamics of each individual fish in the transitions among coarse-grained motor strategies, we use it to uncover a hierarchical structure in the phenotypic variability that reflects exploration-exploitation trade-offs. Across a wide range of sensory cues, a major source of variation among fish is driven by prior and/or immediate exposure to prey that induces exploitation phenotypes. A large degree of variability that is not explained by environmental cues unravels hidden states that override the sensory context to induce contrasting exploration-exploitation phenotypes. Altogether, by extracting the timescales of motor strategies deployed during navigation, our approach exposes structure among individuals and reveals internal states tuned by prior experience.

摘要

动物将运动链成长期的运动策略,表现出跨尺度的可变性,反映了内部状态和环境线索之间的相互作用。为了揭示这种可变性中的结构,我们构建了运动序列的马尔可夫模型,这些模型跨越了时间尺度,能够对个体之间的行为表型进行定量比较。将其应用于对不同感觉线索做出反应的幼虫斑马鱼,我们揭示了一种长期的运动策略层次结构,主要由区分巡游和漫游策略的方向变化决定。环境线索在群体水平上沿着这些模式诱导偏好:虽然鱼在光中巡游,但它们会在遇到厌恶刺激或寻找有吸引力的猎物时漫游。由于我们的方法在粗粒度运动策略之间的转换中对每个个体鱼的行为动态进行编码,因此我们可以利用它来揭示反映探索-开发权衡的表型可变性的层次结构。在广泛的感觉线索范围内,鱼类之间的一个主要变异来源是由先前和/或即时暴露于猎物引起的,这会导致开发表型。大量无法用环境线索解释的可变性揭示了隐藏状态,这些隐藏状态会忽略感官环境,从而导致不同的探索-开发表型。总之,通过提取导航过程中部署的运动策略的时间尺度,我们的方法揭示了个体之间的结构,并揭示了由先前经验调整的内部状态。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b690/11588111/6540b66cbf18/pnas.2410254121fig01.jpg

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