article · 02/01/2020
From behavior to circuit modeling of light-seeking navigation in zebrafish larvae
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Résumé
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.
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Karpenko, S., Wolf, S., Lafaye, J., Le Goc, G., Panier, T., Bormuth, V., Candelier, R., & Debrégeas, G. (2020). From behavior to circuit modeling of light-seeking navigation in zebrafish larvae. eLife, 9(e52882). https://doi.org/10.7554/eLife.52882@article{Karpenko2020_307,
author = {Karpenko, Sophia and Wolf, Sebastien and Lafaye, Julie and Le Goc, Guillaume and Panier, Thomas and Bormuth, Volker and Candelier, Raphaël and Debrégeas, Georges},
year = {2020},
month = {1},
title = {From behavior to circuit modeling of light-seeking navigation in zebrafish larvae},
journal = {eLife},
volume = {9},
number = {e52882},
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 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.},
url = {https://elifesciences.org/articles/52882},
doi = {10.7554/eLife.52882},
}TY - JOUR
AU - Karpenko, Sophia
AU - Wolf, Sebastien
AU - Lafaye, Julie
AU - Le Goc, Guillaume
AU - Panier, Thomas
AU - Bormuth, Volker
AU - Candelier, Raphaël
AU - Debrégeas, Georges
PY - 2020
DA - 2020/01/02
TI - From behavior to circuit modeling of light-seeking navigation in zebrafish larvae
JO - eLife
VL - 9
IS - e52882
AB - 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.
DO - 10.7554/eLife.52882
UR - https://elifesciences.org/articles/52882
ER -