EthoLoop: automated closed-loop neuroethology in naturalistic environments

Ali Nourizonoz , Robert Zimmermann , Chun Lum Andy Ho , Sebastien Pellat , Yannick Ormen , Clément Prévost-Solié , Gilles Reymond , Fabien Pifferi , Fabienne Aujard , Anthony Herrel (1) , Daniel Huber

1 MECADEV - Mécanismes Adaptatifs et Evolution

Accurate tracking and analysis of animal behavior is crucial for modern systems neuroscience. However, following freely mov-ing animals in naturalistic, three-dimensional (3D) or nocturnal environments remains a major challenge. Here, we present EthoLoop, a framework for studying the neuroethology of freely roaming animals. Combining real-time optical tracking and behavioral analysis with remote-controlled stimulus-reward boxes, this system allows direct interactions with animals in their habitat. EthoLoop continuously provides close-up views of the tracked individuals and thus allows high-resolution behavioral analysis using deep-learning methods. The behaviors detected on the fly can be automatically reinforced either by classi-cal conditioning or by optogenetic stimulation via wirelessly controlled portable devices. Finally, by combining 3D tracking with wireless neurophysiology we demonstrate the existence of place-cell-like activity in the hippocampus of freely moving primates. Taken together, we show that the EthoLoop framework enables interactive, well-controlled and reproducible neuroethological studies in large-field naturalistic settings.

Domaines: Sciences du Vivant [q-bio]

Ali Nourizonoz, Robert Zimmermann, Chun Lum Andy Ho, Sebastien Pellat, Yannick Ormen, et al.. EthoLoop: automated closed-loop neuroethology in naturalistic environments. Nature Methods, 2020, 17, pp.1052 - 1059. ⟨10.1038/s41592-020-0961-2⟩. ⟨hal-02990284⟩