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bioRxiv · 10.1101/810960

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

Karpenko, S.·Wolf, S.·Lafaye, J.·Le Goc, G.·Panier, T.·Bormuth, V.·Candelier, R.·Debregeas, G.
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Abstract

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 predict the stationary distribution of the fishs 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 similarly capture the statistics of both spontaneous and contrast-driven navigation.

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Karpenko, S., Wolf, S., Lafaye, J., Le Goc, G., Panier, T., Bormuth, V., Candelier, R., Debregeas, G.. 2019-10-21. From behavior to circuit modeling of light-seeking navigation in zebrafish larvae. https://doi.org/10.1101/810960

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