Videograms: A method for repeatable unbiased quantitative behavioral analysis without scoring or tracking

Abstract

We present a method that complements both scoring by observers and automated tracking methods for quantifying behaviors. Based on standard motion enhancement, our algorithm converts a behavioral video recording into a single image ('videogram') that maps the spatial distribution of activity in the video sequence. This videogram can be used as a visual summary of activity and also as a direct, repeatable, and unbiased measure of animal activity. We describe the algorithm, and then use videograms to show acquisition of odorant-dependent place-conditioning in zebrafish trained in groups. We also demonstrate its potential for determining depth preferences and swimming speeds. This method generates activity measurements suitable for continuous variable statistics, and can be considered as an analysis alternative to behavioral tracking (over which it can have several advantages) for experiments not requiring exact trajectories. © 2011 Springer Science+Business Media, LLC.