Zebrafish is becoming an important animal model in pre-clinical studies for its genetic similarity to humans and ease of use in the laboratory. In recent years, animal experimentation has faced several ethical issues, calling for alternative methods that capitalize on dynamical systems theory. Here, we propose a computational modeling framework to simulate zebrafish swimming in three dimensions (3D) in the form of a coupled system of stochastic differential equations. The model is capable of reproducing the burst-and-coast swimming style of zebrafish, speed modulation, and avoidance of tank boundaries. Model parameters are calibrated on an experimental dataset of zebrafish swimming in 3D and validated by comparing established behavioral measures obtained from both synthetic and experimental data. We show that the model is capable of accurately predicting fish locomotion in terms of the swimming speed and number of entries in different sections of the tank. The proposed model lays the foundations for in-silico experiments of zebrafish neurobehavioral research.

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