RT Journal Article
SR Electronic
T1 Automatic classification of behavior in zebrafish larvae
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 052324
DO 10.1101/052324
A1 Adrien Jouary
A1 German Sumbre
YR 2016
UL http://biorxiv.org/content/early/2016/05/10/052324.abstract
AB 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 larva’s trajectory and is thus compatible with both free-swimming and functional imaging in head-fixed condition.