Coccinella is an innovative open-source framework developed for high-throughput behavioral analysis. Leveraging the power of distributed microcomputers, it facilitates real-time tracking of small animals, such as Drosophila melanogaster. Complementing this tracking capability, coccinella employs advanced statistical learning techniques to decipher and categorize observed behaviors. Unlike many high-resolution systems that often require significant resources and may compromise on throughput, coccinella strikes a balance, offering both precision and efficiency. Built upon the foundation of ethoscopes, this platform extracts minimalist yet crucial information from behavioral paradigms. Notably, in comparative studies, coccinella has demonstrated superior performance in recognizing pharmacobehavioral patterns, achieving this at a fraction of the cost of other state-of-the-art systems. This framework promises to complement current ethomics tools by providing a cost-effective, efficient, and precise tool for behavioral research. Coccinella analysis can be done in ethoscopy, a Python framework for analysis of ethoscope data.

Coccinella paper on eLife
Ethoscopy / Ethoscope-lab preprint on bioRxiv
Ethoscopy on GitHub
Ethoscopy on PyPi
Ethoscope-lab Docker container on DockerHub
Jupyter Notebook tutorials for Ethoscopy on GitHub
Ethoscopy and Ethoscope-lab documentation on bookstack
Raw data and all notebooks reproducing the paper’s figures on Zenodo

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