Capturing continuous, long timescale behavioral changes in Drosophila melanogaster postural data.

ABSTRACT: Animal behavior spans many timescales, from short, seconds-scale actions to daily rhythms over many hours to life-long changes during aging. To access longer timescales of behavior, we continuously recorded individual Drosophila melanogaster at 100 frames per second for up to 7 days at a time in featureless arenas on sucrose-agarose media. We use the deep learning framework SLEAP to produce a full-body postural dataset for 47 individuals resulting in nearly 2 billion pose instances. We identify stereotyped behaviors such as grooming, proboscis extension, and locomotion and use the resulting ethograms to explore how the flies' behavior varies across time of day and days in the experiment. We find distinct daily patterns in all stereotyped behaviors, adding specific information about trends

SUBMITTER: McKenzie-Smith GC 

PROVIDER: S-EPMC11813078 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature