A Novel Method for Automated Tracking and Quantification of Adult Zebrafish Behaviour During Anxiety

Background: Behavioural neuroscience relies on software driven methods for behavioural assessment, but the field lacks cost-effective, robust, open source software for behavioural analysis.

New Method: Here we propose a novel method which we called as ZebraTrack. It includes cost-effective imaging setup for distraction-free behavioural acquisition, automated tracking using open-source ImageJ software and workflow for extraction of behavioural endpoints. Our ImageJ algorithm is capable of providing control to users at key steps while maintaining automation in tracking without the need for the installation of external plugins.

Results: We have validated this method by testing novelty induced anxiety behaviour in adult zebrafish. Our results, in agreement with established findings, showed that during state-anxiety, zebrafish showed reduced distance travelled, increased thigmotaxis and freezing events. Furthermore, we proposed a method to represent both spatial and temporal distribution of choice-based behaviour which is currently not possible to represent using simple videograms.

Comparison With Existing Method(s): ZebraTrack method is simple and economical, yet robust enough to give results comparable with those obtained from costly proprietary software like Ethovision XT.

Conclusion: We have developed and validated a novel cost-effective method for behavioural analysis of adult zebrafish using open-source ImageJ software.