Long-term monitoring of huddling behavior in mice using online image processing.

ABSTRACT: Many animal species, including mice, form societies of numerous individuals for survival. Understanding the interactions between individual animals is crucial for elucidating group behavior. One such behavior in mice is huddling, yet its analysis has been limited. In this study, we propose a cost-effective method for monitoring long-term huddling behavior in mice using online image processing with OpenCV. This method treats a single mouse or a group of mice as a cluster of pixels (a 'blob') in video images, extracting and saving only essential information such as areas, coordinates, and orientations. This approach reduces data storage needs to 1/200000th of what would be required if the video were recorded in its compressed form, thereby enabling long-term behavioral analysis. To validate

SUBMITTER: Nomoto K 

PROVIDER: S-EPMC10932781 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature