| First Author | Del Rosario Hernández T | Year | 2023 |
| Journal | Sci Rep | Volume | 13 |
| Issue | 1 | Pages | 8113 |
| PubMed ID | 37208415 | Mgi Jnum | J:349233 |
| Mgi Id | MGI:7485312 | Doi | 10.1038/s41598-023-35322-1 |
| Citation | Del Rosario Hernandez T, et al. (2023) An 8-cage imaging system for automated analyses of mouse behavior. Sci Rep 13(1):8113 |
| abstractText | The analysis of mouse behavior is used in biomedical research to study brain function in health and disease. Well-established rapid assays allow for high-throughput analyses of behavior but have several drawbacks, including measurements of daytime behaviors in nocturnal animals, effects of animal handling, and the lack of an acclimation period in the testing apparatus. We developed a novel 8-cage imaging system, with animated visual stimuli, for automated analyses of mouse behavior in 22-h overnight recordings. Software for image analysis was developed in two open-source programs, ImageJ and DeepLabCut. The imaging system was tested using 4-5 month-old female wild-type mice and 3xTg-AD mice, a widely-used model to study Alzheimer's disease (AD). The overnight recordings provided measurements of multiple behaviors including acclimation to the novel cage environment, day and nighttime activity, stretch-attend postures, location in various cage areas, and habituation to animated visual stimuli. The behavioral profiles were different in wild-type and 3xTg-AD mice. AD-model mice displayed reduced acclimation to the novel cage environment, were hyperactive during the first hour of darkness, and spent less time at home in comparison to wild-type mice. We propose that the imaging system may be used to study various neurological and neurodegenerative disorders, including Alzheimer's disease. |
