An open-source AI tool available to study movement across behaviors and species
Understanding the brain, in part, means understanding how behavior is created. To reverse-engineer how neural circuits drive behavior requires accurate and vigorous tracking of behavior, yet the increasingly complex tasks animals perform in the laboratory have made that challenging. Now, a team of researchers from the Rowland Institute at Harvard, Harvard University, and the University of Tübingen is turning to artificial intelligence technology to solve the problem. The software they developed, dubbed DeepLabCut, harnesses new learning techniques to track features from the digits of mice, to egg-laying behavior in Drosophila, and beyond. The work is described in an Aug. 20 paper published in Nature Neuroscience. The software is the brainchild of Mackenzie Mathis, a Rowland Fellow at the Rowland Institute at Harvard; Alexander Mathis, a postdoctoral fellow working in the lab of Venkatesh N. Murthy, professor of molecular and cellular biology and chair of the Department of Molecular and Cellular Biology; and Matthias Bethge,...