Behavioural phenotyping with small aquatic model organisms: why digital video resolution and bitrate matter.

Authors

Hy Do, Florian Kreuder, Xuhui Han, Michael Didham, Savita Kumari, Oskar Wasielewski, Jan Kaslin, Paul A Ramsland, Antoine M Dujon, Donald Wlodkowic

Published in

Behavioural pharmacology. Jul 09, 2026. Epub Jul 09, 2026.

Abstract

Behavioural analysis with small aquatic model organisms is increasingly applied across diverse areas of biosciences and biomedicine, including ecology, pharmacology, and experimental neurobiology. High-throughput behavioural phenotyping workflows frequently employ organisms such as larval zebrafish (Danio rerio) in multiwell laboratory plates, yet the considerable cost of commercial imaging platforms often limits access for smaller laboratories, early career investigators and researchers in low- and middle-income countries. Here, we describe a rapid and practical approach for constructing an inexpensive, flexible and fully customisable behavioural data acquisition system suitable for use with a broad range of aquatic model species. We also examine an important but frequently overlooked methodological issue in quantitative behavioural research: how video acquisition parameters, particularly resolution and bitrate, influence the reliability of automated animal tracking. Using Artemia franciscana nauplii, adult Daphnia carinata, and 7 days postfertilisation larval Danio rerio, we show that video resolution is a major determinant of detection reliability, particularly for very small test organisms. Artemia franciscana could not be reliably tracked in multiarena configurations at resolutions below full high definition, whereas ultra high definition (3840 × 2160 pixels) provided robust detection across all tested species. We also show that concerns regarding ultra high definition file size can be mitigated by optimising bitrate settings. Moderate compression produced major reductions in file size while preserving detection reliability at practical compression levels. Together, these findings provide a practical framework for designing affordable and custom animal tracking systems and selecting video acquisition settings that support reliable high-throughput behavioural phenotyping across diverse aquatic species.

PMID:
42430751
Bibliographic data and abstract were imported from PubMed on 11 Jul 2026.

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