Design of Video Tracking Software for Analysis of Animal Movement in Water Maze Experiments

In this study, a video tracking software was designed for use in Morris water tank (MST) experiments. The software, developed using Python programming language and Bootstrap interface, enables the detection, tracking and analysis of animal movements from both recorded video files and live video streams. The software, which was originally designed and developed within the scope of this study, uses image processing techniques, which are vital in spatial memory studies, and automates processes such as experiment design, region identification and object detection, unlike the traditional method of laboratory tracking. also performs functions such as experiment control, visualization of traces and calculation of analysis parameters. Using this advanced video monitoring system, we aim to more effectively characterize the data obtained with MST and improve statistical analysis. Thus, we aim to provide practical solutions to the problems encountered in neuroscience research and increase the efficiency of experiments