Understanding the complex array of genes, proteins and cells involved in learning and memory is a major challenge for neuroscientists. Using the genetically powerful model system, Drosophila melanogaster, and its well-studied courtship behavior, investigators have begun to delineate essential elements of associative and nonassociative behavioral plasticity. Advances in transgenic tools and developments in behavioral assays have increased the power of studying courtship learning in the fruit fly.
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SARTAB, a scalable system for automated real-time behavior detection based on animal tracking and Region Of Interest analysis: validation on fish courtship behavior.
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Methods from Machine Learning (ML) and Computer Vision (CV) have proven powerful tools for quickly and accurately analyzing behavioral recordings. The computational complexity of these techniques, however, often precludes applications that require real-time analysis: for example, experiments where a stimulus must be applied in response to a particular behavior or samples must be collected soon after the behavior occurs. Here, we describe SARTAB (Scalable Automated Real-Time Analysis of Behavior), a system that achieves automated real-time behavior detection by continuously monitoring animal positions relative to behaviorally relevant Regions Of Interest (ROIs).
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