Adult Zebrafish Neuroscience Behavioral Models (Dissertation Research)
The use of adult zebrafish (Danio rerio) in neurobehavioral research is rapidly expanding. The present large-scale study applied the newest video-tracking and data-mining technologies to further examine zebrafish anxiety-like phenotypes. Here, we generated temporal and spatial three-dimensional (3D) reconstructions of zebrafish locomotion, globally assessed behavioral profiles evoked by several anxiogenic and anxiolytic manipulations, mapped individual endpoints to 3D reconstructions, and performed cluster analysis to reconfirm behavioral correlates of high- and low-anxiety states. The application of 3D swim path reconstructions consolidates behavioral data (while increasing data density) and provides a novel way to examine and represent zebrafish behavior. It also enables rapid optimization of video tracking settings to improve quantification of automated parameters, and suggests that spatiotemporal organization of zebrafish swimming activity can be affected by various experimental manipulations in a manner predicted by their anxiolytic or anxiogenic nature. Our approach markedly enhances the power of zebrafish behavioral analyses, providing innovative framework for high-throughput 3D phenotyping of adult zebrafish behavior.
Zebrafish (Danio rerio) are offering novel perspectives to investigate the nervous system as a genetically and molecularly tractable in-vivo model of complex vertebrate behavior. The balance of low cost, experimental agility and phenotypic complexity, unique to zebrafish, empowers researchers to study biochemical regulators of development, behavior and disease pathogenesis in ways previously unapproachable. Larval zebrafish assays have demonstrated the value of integrating behavioral tests with high-throughput quantification techniques by successfully identifying psychotropic compounds and predicting neurological targets based on large-scale analysis of variation in behavioral responses. Pre-clinical drug discovery and behavioral genetics stands to benefit greatly from high-throughput screening assays using adult zebrafish. However, a characterization and quantification technique of adult zebrafish behavioral phenotypes requires standardization before such assays can be realized. This dissertation provides characterization of adult zebrafish behavior following ethological and pharmacological experimental treatments in affective and social domains. Behavior is quantified manually, as well as using automated video-tracking software, and correlated with a physiological biomarker (i.e. whole-body cortisol) to verify phenotypic states. In addition, a novel method of neurophenotyping using three-dimensional swim trajectory reconstructions is presented to enable rapid identification of treatment specific movement patterns. Collectively, this research provides a foundation for future studies pursing high-throughput behavioral phenotyping in adult zebrafish, and their application to modeling complex human disorders.
Developed novel research methodologies to explore the relationship between drugs, the brain and behavior.
Movement Pattern Analysis is a machine learning approach to characterize and classify particular types of spatiotemporal motion.
A worldwide expert on the use of adult zebrafish in neurobehavioral and psychopharmacological research.