TY - JOUR
T1 - Swimming in the future already
T2 - the use of AI in zebrafish neurobehavioral research and CNS drug screening
AU - Eroshkin, Aleksander A.
AU - Jia, Yuxiang
AU - Fu, Zhike
AU - Pang, Yixuan
AU - Xiao, Yubo
AU - He, Shulei
AU - Wang, Gan
AU - Khatsko, Sergey L.
AU - Zhdanov, Aleksandr V.
AU - Perfilova, Valentina N.
AU - Yang, Longen
AU - Cui, Jiahao
AU - Stewart, Adam Michael
AU - Quintanilha, Thalia M.
AU - de Abreu, Murilo S.
AU - Kalueff, Allan V.
N1 - Publisher Copyright:
© 2026 International Brain Research Organization (IBRO)
PY - 2026/9/11
Y1 - 2026/9/11
N2 - Artificial intelligence (AI) is rapidly revolutionizing biomedical research. Empowered by enhanced object recognition and modern machine learning protocols, AI tools detect subtle patterns in human and animal behavior, efficiently quantifying and classifying them using supervised and unsupervised learning approaches. Complementing rodent studies, the zebrafish (Danio rerio) represents a crucial model organism in neuroscience research with well-characterized quantifiable behaviors, high-throughput potential and high genetic, neurochemical, and neuroanatomical homology to humans. The integration of AI strategies into zebrafish neuroscience research enhances behavioral endpoint monitoring, efficient processing and interpretation of data, establishing high-throughput screens and finding critical connections among behavioral and molecular endpoints. Here, we discuss the current status of the application of AI methods in zebrafish neurobehavioral research, as well as its limitations, future research directions, and remaining open questions in the field, with a particular focus on the use of AI in behavioral analyses and neuroactive drug discovery.
AB - Artificial intelligence (AI) is rapidly revolutionizing biomedical research. Empowered by enhanced object recognition and modern machine learning protocols, AI tools detect subtle patterns in human and animal behavior, efficiently quantifying and classifying them using supervised and unsupervised learning approaches. Complementing rodent studies, the zebrafish (Danio rerio) represents a crucial model organism in neuroscience research with well-characterized quantifiable behaviors, high-throughput potential and high genetic, neurochemical, and neuroanatomical homology to humans. The integration of AI strategies into zebrafish neuroscience research enhances behavioral endpoint monitoring, efficient processing and interpretation of data, establishing high-throughput screens and finding critical connections among behavioral and molecular endpoints. Here, we discuss the current status of the application of AI methods in zebrafish neurobehavioral research, as well as its limitations, future research directions, and remaining open questions in the field, with a particular focus on the use of AI in behavioral analyses and neuroactive drug discovery.
KW - Artificial intelligence
KW - Behavior
KW - Behavioral models
KW - Machine learning
KW - Zebrafish
UR - https://www.scopus.com/pages/publications/105044915778
U2 - 10.1016/j.neuroscience.2026.07.014
DO - 10.1016/j.neuroscience.2026.07.014
M3 - Review article
C2 - 42425263
AN - SCOPUS:105044915778
SN - 0306-4522
VL - 611
SP - 354
EP - 366
JO - Neuroscience
JF - Neuroscience
ER -