2026-05-24T16:34:11Zhttps://www.radar-service.eu/oai/OAIHandler

10.48606/x6xjjyddnzkkzd9c2026-05-09T03:00:57Z

10.48606/x6xjjyddnzkkzd9c Capelle, Maxim Q. Maxim Q. Capelle 0009-0009-3473-0240 University of Konstanz Bahl, Armin Armin Bahl 0000-0001-7591-5860 University of Konstanz University of Konstanz 2025 2026 Biology zebrafish phototaxis sensorimotor decision-making virtual environment ontogeny Modeling Behavioral tracking and modeling data Open Access Creative Commons Attribution 4.0 International Bahl, Armin 0000-0001-7591-5860 Slangewal, Katja 0000-0003-0074-2656 University of Konstanz Eleftheriadis, Panagiotis E. 0000-0001-7425-3076 University of Konstanz Animals undergo major behavioral adjustments during ontogeny, but how the underlying cognitive algorithms change during this process remains elusive. Here, we describe that zebrafish shift from light-seeking to dark-seeking, as they grow from larval to juvenile stage, within the first few weeks of their life. We apply a combination of complementary phototaxis assays in virtual reality and modeling to dissect the computational basis of this transition. We identify three parallel pathways, one analyzing ambient whole-field luminance levels, one spatially comparing light levels across the eyes, and one computing eye-specific temporal derivatives. Larvae mostly use the latter two spatio-temporal computations for navigation, while juveniles largely employ the first one. We build a library of agent-based models to predict animal behavior across stimulation conditions and in more complex environments. Model-based extraction of latent cognitive variables points towards potential neural correlates of the observed behavioral inversion and illustrates a novel way to explore the processes of vertebrate ontogeny. We suggest that zebrafish phototaxis is regulated via parallel processing streams, which could be a universal implementation to change strategies depending on developmental stage, context, or internal state, making behavior flexible and goal-oriented. Tracking setup and computational modeling Custom-written Python scripts en 10.1101/2025.06.13.659371 10.48606/m9v18p3c6cb7k77q 10.48606/sb32fkvwj5avwhbr GERMANY Deutsche Forschungsgemeinschaft https://ror.org/018mejw64 BA 5923/1-1 European Commission https://ror.org/00k4n6c32 101075541 CollectiveDecisions Deutsche Forschungsgemeinschaft https://ror.org/018mejw64 EXC 2117 – 422037984 Zukunftskolleg, Universität Konstanz https://doi.org/10.13039/501100024848 Max Planck Society https://ror.org/01hhn8329 IMPRS-QBEE Boehringer Ingelheim Fonds https://ror.org/00dkye506 National Institute of Health https://ror.org/05h1kgg64 U19NS104653 application/x-tar