Swimming in the future already: the use of AI in zebrafish neurobehavioral research and CNS drug screening.

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.