Journal article
Zebrafish behavioral phenotyping: Current assays, automated platforms, and the emerging need for AI in neuroscience, drug discovery and toxicology
Neuroscience and Biobehavioral Reviews, Vol.187, pp.1-19
2026
PMID: 42176767
Abstract
Over the past two decades, zebrafish have become an increasingly prominent model organism for basic research, drug discovery, and toxicology. Its advantages combine low cost, high throughput amenability, high gene homology to humans, genetic flexibility and widespread use in academia. This animal model combines the ease of use of smaller animals (such as C. elegans and D. melanogaster) with the complexity of its vertebrate/mammalian counterparts, adding access to comprehensive phenotypic and behavioral studies without compromising high throughput and low cost.
Similar to rodent models, a growing number of assays have recently been developed for zebrafish. This repertoire is rapidly growing and recent advancements in high-throughput techniques, computer-driven simulations, and automated tracking technologies/devices are starting to open new doors of research while simplifying the analysis of previously difficult-to-detect phenotypes. In parallel, the integration of artificial intelligence (AI) holds great promise for more effectively detecting and characterizing even the most subtle behavioral changes. Despite this rapid progress, the field would benefit from greater standardization of nomenclature, assays, and data formats.
Here, we reviewed the literature associated with comprehensive zebrafish behavioral assays, with a particular focus on their applications in drug discovery and toxicology. We compiled the automated devices developed or adapted for these assays. We further discussed the advantages and limitations of these technologies and outlined potential future directions and needs in the field.
Details
- Title
- Zebrafish behavioral phenotyping: Current assays, automated platforms, and the emerging need for AI in neuroscience, drug discovery and toxicology
- Authors
- Quynh T N Nguyen - Griffith UniversityJean Giacomotto (Corresponding Author) - University of the Sunshine Coast
- Publication details
- Neuroscience and Biobehavioral Reviews, Vol.187, pp.1-19
- Publisher
- Elsevier Ltd
- Date published
- 2026
- DOI
- 10.1016/j.neubiorev.2026.106774
- ISSN
- 1873-7528
- PMID
- 42176767
- Copyright note
- © 2026 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ ).
- Grant note
- FightMND Impact Grant to JG.
- Organisation Unit
- Thompson Institute
- Language
- English
- Record Identifier
- 991239200002621
- Output Type
- Journal article
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