An efficient new assay for measuring zebrafish anxiety: Tall tanks that better characterize between-individual differences

Hamza Anwer*, Dominic Mason, Susanne Zajitschek, Daniel W.A. Noble, Daniel Hesselson, Margaret J. Morris, Malgorzata Lagisz, Shinichi Nakagawa

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    9 Citations (Scopus)

    Abstract

    Background: Zebrafish (Danio rerio) are increasingly being used to model anxiety. A common behavioral assay employed for assessing anxiety-like behaviors in zebrafish is the “novel tank test”. We hypothesized that using deeper tanks in this test would result in greater between-individual variation in behavioral responses and a more ‘repeatable’ assay. New methods: After mapping the literature and identifying common behavioral parameters used in analysis, we performed novel tank anxiety tests in both custom-designed ‘tall’ tanks with increased depth and ‘short’ trapezoidal tanks. We compared the repeatability of the behavioral parameters between tall and short tanks and also investigated sex differences. Results: Overall, regardless of tank depth, almost all behavioral parameters associated with anxiety in zebrafish were significantly repeatable (R = 0.24 to 0.60). Importantly, our tall tanks better captured between-individual differences, resulting in higher repeatability estimates (average repeatability tall tanks: R = 0.46; average repeatability short tanks: R = 0.36) and clearer sex differences. Conclusions: Our assay using tall tanks has advantages over tests based on short tanks which underestimate repeatability. We argue that use of deeper tanks will improve the reliability of behavioral data across studies using novel tank tests for zebrafish. Our results also call for increased attention in designing the most appropriate assay in biomedical and behavioral sciences as current methods may lack the sensitivity to detect subtle, yet important, information, such as between-individual variation, an important component in assessing the reliability of behavioral data.

    Original languageEnglish
    Article number109138
    JournalJournal of Neuroscience Methods
    Volume356
    DOIs
    Publication statusPublished - 15 May 2021

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