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A reductionist paradigm for high-throughput behavioural fingerprinting in Drosophila melanogaster.


ABSTRACT: Understanding how the brain encodes behaviour is the ultimate goal of neuroscience and the ability to objectively and reproducibly describe and quantify behaviour is a necessary milestone on this path. Recent technological progresses in machine learning and computational power have boosted the development and adoption of systems leveraging on high-resolution video recording to track an animal pose and describe behaviour in all four dimensions. However, the high temporal and spatial resolution that these systems offer must come as a compromise with their throughput and accessibility. Here, we describe coccinella, an open-source reductionist framework combining high-throughput analysis of behaviour using real-time tracking on a distributed mesh of microcomputers (ethoscopes) with resource-lean statistical learning (HCTSA/Catch22). Coccinella is a reductionist system, yet outperforms state-of-the-art alternatives when exploring the pharmacobehaviour in Drosophila melanogaster.

SUBMITTER: Jones H 

PROVIDER: S-EPMC10631757 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature

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A reductionist paradigm for high-throughput behavioural fingerprinting in <i>Drosophila melanogaster</i>.

Jones Hannah H   Willis Jenny A JA   Firth Lucy C LC   Giachello Carlo N G CNG   Gilestro Giorgio F GF  

eLife 20231108


Understanding how the brain encodes behaviour is the ultimate goal of neuroscience and the ability to objectively and reproducibly describe and quantify behaviour is a necessary milestone on this path. Recent technological progresses in machine learning and computational power have boosted the development and adoption of systems leveraging on high-resolution video recording to track an animal pose and describe behaviour in all four dimensions. However, the high temporal and spatial resolution th  ...[more]

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2008-12-04 | GSE13679 | GEO