Automatic classification of behavior in zebrafish larvae

Zebrafish larvae navigate the environment by discrete episode of propulsion called bouts. We introduce a novel method for automatically classifying zebrafish tail movements. We used a supervised soft-clustering algorithm to categorize tail bouts into 5 categories of movements: Scoot, Asymmetrical Scoot, Routine Turn, C Bend and Burst. Tail bouts were correctly classified with 82% chance while errors in the classification occurred mostly between similar categories. Although previous studies have performed categorization of behavior in free-swimming conditions, our method does not rely on the analysis of the trajectories and can be applied in both head-fixed and free-swimming conditions.