AquaMaze: A Computer Vision-Based Framework for Automated Behavioral Analysis of Zebrafish in Controlled Environments.

Abstract

Zebrafish (Danio rerio) have become a prominent model organism in behavioral neuroscience and pharmacological studies due to their genetic homology with humans and transparent physiology. Despite their increasing use, many laboratories still rely on manual or semi-automated tracking systems to assess behavior. There are programs commercially available, which are expensive and may not be possible to purchase for those researchers with a limited budget. Here, we introduce AquaMaze, a standalone, open-source desktop application built with PyQt5 and OpenCV, designed for real-time and post-hoc video-based behavioral tracking of zebrafish. AquaMaze computes locomotion metrics, including swim distance, speed, quadrant occupancy, and rest/activity patterns, from user-defined video inputs. The software provides intuitive visualization with heatmaps and exports detailed CSV reports, offering a scalable solution for high-throughput behavioral assays. We demonstrate the capabilities of AquaMaze using standard zebrafish locomotor activity paradigms such as the novel tank test, swim behavior test, novel object recognition, and Y-maze paradigms. In all of these tests, it is shown that AquaMaze gives reliable and consistent results. Hereby we provide a fast and cheap tool for the zebrafish behavioral experiments.