Basic NeuroscienceValidation of video motion-detection scoring of forced swim test in mice

•We use a video motion-detection method in MATLAB to quantify the forced swim test.•Data obtained by computer scoring correlate well with visual scoring.•Group differences detected by computer and visual scoring are almost the same.•Hybrid F1 mice are more active than parental strains in the test.

BackgroundThe forced swim test (FST) is used to predict the effectiveness of novel antidepressant treatments. In this test, a mouse or rat is placed in a beaker of water for several minutes, and the amount of time spent passively floating is measured; antidepressants reduce the amount of such immobility. Though the FST is commonly used, manually scoring the test is time-consuming and involves considerable subjectivity.New methodWe developed a simple MATLAB-based motion-detection method to quantify mice's activity in videos of FST. FST trials are video-recorded from a side view. Each pixel of the video is compared between subsequent video frames; if the pixel's color difference surpasses a threshold, a motion count is recorded.ResultsHuman-scored immobility time correlates well with total motion detected by the computer (r = −0.80) and immobility time determined by the computer (r = 0.83). Our computer method successfully detects group differences in activity between genotypes and different days of testing. Furthermore, we observe heterosis for this behavior, in which (C57BL/6J × A/J) F1 hybrid mice are more active in the FST than the parental strains.Comparison with existing methodsThis computer-scoring method is much faster and more objective than human scoring. Other automatic scoring methods exist, but they require the purchase of expensive hardware and/or software.ConclusionThis computer-scoring method is an effective, fast, and low-cost method of quantifying the FST. It is validated by replicating statistical differences observed in traditional visual scoring. We also demonstrate a case of heterosis in the FST.