Automatic classification of behavior in zebrafish larvae

Abstract

Zebrafish larvae navigate the environment by discrete episode of propulsion called bouts. We introduce a novel method for automatically classifying tail bouts. 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 larvas trajectory and is thus compatible with both free-swimming and functional imaging in head-fixed condition.