Examining locomotion has improved our basic understanding of motor control and aided in treating motor impairment. Mice are a premier model of human disease and increasingly the model system of choice for basic neuroscience. High frame rates (higher than 150 Hz) are needed to quantify the kinematics of running mice, due to their high stride frequency (up to 10 Hz). Thus manual tracking, especially for multiple markers, becomes time-consuming and impossible for large sample sizes. Therefore, an automated method is necessary. Several methods have been used to automatically or semi-automatically track mice, including commercially available systems (Digigait [1, 2], Motorater, Noldus Catwalk [3, 4]). These systems can be typically prohibitively expensive, and may only provide information about paws during the stand phase. In research and industry approaches to tracking mice have frequently relied on shaving fur and then drawing markers on the skin for subsequent tracking raw video [5], or on the attachment of retroreflective markers, and the use of optical motion capture systems. These methods have the drawback of requiring anesthesia and multiple handlings applications of markers, and the problem of animal removing the attached markers. Here, we develop methods to track and label the body and paws directly from high speed color video, without shaving fur or attaching markers. We analyse data from the C57BL/6 mouse, because it is the most widely used strain in basic research and biomedicine.
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