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Understanding such multiscale dynamics is essential for revealing the mechanisms and organizing principles that generate behavior and shape motor control. However, conventional analyses largely rely on static or statistical descriptors, which fail to capture the intrinsic dynamical rules governing behavioral evolution over time. Larval zebrafish, whose body posture can be quantified as spatial coordinates, provide an ideal vertebrate model for studying behavioral dynamics. Here, we develop a dynamical reconstruction framework that combines delay embedding with an echo state network to recover the latent state space of zebrafish behavior from high-dimensional postural time series. The framework preserves temporal dependencies and maps postural variations onto latent factors whose combinations define distinct behavioral states\u2014turning, routine swimming, and slow swimming\u2014matching feature-based clustering. These states evolve as continuous trajectories on a low-dimensional attractor, with transitions marked by nonlinear tipping points that reflect reorganization of underlying factors. Leveraging this reconstructed state space, the framework also enables short-term behavioral prediction. Overall, our framework provides a unified quantitative tool for revealing the latent dynamical principles of zebrafish behavior, with potential extensions to neural and bio-inspired control.<\/jats:p>","DOI":"10.1063\/5.0354035","type":"journal-article","created":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T12:52:20Z","timestamp":1790686340000},"update-policy":"https:\/\/doi.org\/10.1063\/aip-crossmark-policy-page","source":"Crossref","is-referenced-by-count":0,"title":["Latent factors capturing evolution of behavior in larval zebrafish"],"prefix":"10.1063","volume":"36","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-6223-2301","authenticated-orcid":false,"given":"Changhong","family":"Han","sequence":"first","affiliation":[{"name":"Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University 1 , Shanghai 200433,","place":["China"]},{"name":"Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Ministry of Education 2 , Shanghai 200433,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-5951-2326","authenticated-orcid":false,"given":"Yuchen","family":"Gong","sequence":"additional","affiliation":[{"name":"Institute of Neuroscience, State Key Laboratory of Brain Cognition and Brain-Inspired Intelligence Technology, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences 3 , Shanghai 200031,","place":["China"]},{"name":"School of Future Technology, University of Chinese Academy of Sciences 4 , Beijing 100049,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-4539-154X","authenticated-orcid":false,"given":"Le","family":"Sun","sequence":"additional","affiliation":[{"name":"Institute of Neuroscience, State Key Laboratory of Brain Cognition and Brain-Inspired Intelligence Technology, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences 3 , Shanghai 200031,","place":["China"]},{"name":"School of Future Technology, University of Chinese Academy of Sciences 4 , Beijing 100049,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9413-9991","authenticated-orcid":false,"given":"Jiulin","family":"Du","sequence":"additional","affiliation":[{"name":"Institute of Neuroscience, State Key Laboratory of Brain Cognition and Brain-Inspired Intelligence Technology, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences 3 , Shanghai 200031,","place":["China"]},{"name":"School of Future Technology, University of Chinese Academy of Sciences 4 , Beijing 100049,","place":["China"]},{"name":"School of Life Science and Technology, Shanghai Tech University 5 , Shanghai 200031,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3225-8431","authenticated-orcid":false,"given":"Peng","family":"Ji","sequence":"additional","affiliation":[{"name":"Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University 1 , Shanghai 200433,","place":["China"]},{"name":"Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Ministry of Education 2 , Shanghai 200433,","place":["China"]},{"name":"MOE Frontiers Center for Brain Science, Fudan University 6 , Shanghai 200433,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"317","published-online":{"date-parts":[[2026,9,29]]},"reference":[{"issue":"3","key":"2026092908434409200_c1","doi-asserted-by":"publisher","first-page":"562","DOI":"10.1016\/j.neuron.2019.10.037","article-title":"Nested neuronal dynamics orchestrate a behavioral hierarchy across timescales","volume":"105","year":"2020","journal-title":"Neuron"},{"issue":"19","key":"2026092908434409200_c2","doi-asserted-by":"publisher","first-page":"4134","DOI":"10.1016\/j.cell.2023.07.035","article-title":"Brain-wide representations of behavior spanning multiple timescales and states in C. elegans","volume":"186","year":"2023","journal-title":"Cell"},{"issue":"7664","key":"2026092908434409200_c3","doi-asserted-by":"publisher","first-page":"445","DOI":"10.1038\/nature23014","article-title":"A novel mechanism for mechanosensory-based rheotaxis in larval zebrafish","volume":"547","year":"2017","journal-title":"Nature"},{"issue":"1","key":"2026092908434409200_c4","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1016\/j.neuron.2016.12.003","article-title":"Perceptual decision making in rodents, monkeys, and humans","volume":"93","year":"2017","journal-title":"Neuron"},{"issue":"50","key":"2026092908434409200_c5","doi-asserted-by":"publisher","first-page":"e2102157118","DOI":"10.1073\/pnas.2102157118","article-title":"The geometry of decision-making in individuals and collectives","volume":"118","year":"2021","journal-title":"Proc. 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