From behavior to circuit modeling of light-seeking navigation in zebrafish larvae

eLife

Guillaume Le Goc¹  Sebastien Wolf²  Julie Lafaye³  Georges Debrégeas⁴  Raphaël Candelier⁴  Volker Bormuth⁴  Sophia Karpenko⁴  Thomas Panier⁴ 

[1] Institut de Biologie de l’Ecole Normale Supérieure, CNRS, INSERM, UMR 8197 & PSL Research, Paris, France;Université Paris Sciences et Lettres, Paris, France;Laboratoire de Physique de l’Ecole Normale Supérieure, CNRS UMR 8023 & PSL Research, Paris, France;Sorbonne Université, CNRS, Institut de Biologie Paris-Seine (IBPS), Laboratoire Jean Perrin (LJP), Paris, France;

关键词: animal behavior;    decision-making;    neural circuit models;    phototaxis;   

DOI  :  10.7554/eLife.52882

来源: DOAJ

【 摘 要 】

Bridging brain-scale circuit dynamics and organism-scale behavior is a central challenge in neuroscience. It requires the concurrent development of minimal behavioral and neural circuit models that can quantitatively capture basic sensorimotor operations. Here, we focus on light-seeking navigation in zebrafish larvae. Using a virtual reality assay, we first characterize how motor and visual stimulation sequences govern the selection of discrete swim-bout events that subserve the fish navigation in the presence of a distant light source. These mechanisms are combined into a comprehensive Markov-chain model of navigation that quantitatively predicts the stationary distribution of the fish’s body orientation under any given illumination profile. We then map this behavioral description onto a neuronal model of the ARTR, a small neural circuit involved in the orientation-selection of swim bouts. We demonstrate that this visually-biased decision-making circuit can capture the statistics of both spontaneous and contrast-driven navigation.

【 授权许可】

Unknown