Motor Learning

Motor Learning
Motor learning in a multisensory environment

We aim to monitor brain wide network plasticity while zebrafish adapt to changing conditions in a multisensory virtual environment during motor learning. We will identify the operant neural circuits and quantify adaptive network changes.

Motor learning involves one of the most fundamental feature of the brain: neuronal plasticity, the capacity of neuronal networks to modify their functional architecture. Our goal is to analyze neuronal plasticity at brain-wide scale. With a new multisensory virtual-reality platform, we want to monitor neuronal activity throughout the brain, while fish adapt their gaze stabilization and postural control to simulated changes of body parameters or the environment. We will identify the neuronal circuits involved and quantify network changes using methods from statistical physics.

Publications

  • Publication 1: Migault G, van der Plas TL, Trentesaux H, Panier T, Candelier R, Proville R, et al: Whole-Brain Calcium Imaging during Physiological Vestibular Stimulation in Larval Zebrafish. Current Biology 28:3723–3735.e6, 2018.

  • Publication 2: Wolf S, Dubreuil AM, Bertoni T, Böhm UL, Bormuth V, Candelier R, et al: Sensorimotor computation underlying phototaxis in zebrafish. Nature Communication 8:651, 2017.

  • Publication 3: Bormuth V, Barral J, Joanny J-F, Jülicher F, Martin P: Transduction channels' gating can control friction on vibrating hair-cell bundles in the ear. PNAS 111:7185–7190, 2014.