Deep learning tools for the measurement of animal behavior in neuroscience. (February 2020)

• Record Type: Journal Article
• Authors: Mathis, Mackenzie Weygandt; Mathis, Alexander
• Is Part Of: Current opinion in neurobiology. Volume 60(2020)
• Page Start: 1
• Page End: 11
• Publication Date: 2020-02
• Subjects: Neurobiology -- Periodicals; 573.8
• DOI: 10.1016/j.conb.2019.10.008
• Languages: English
• ISSNs: 0959-4388

Abstract

Highlights: Deep neural networks are shattering performance benchmarks in computer vision for various tasks. Using modern deep learning approaches (DNNs) in the lab is a fruitful approach for robust, fast, and efficient measurement of animal behavior. New DNN-based tools allow for customized tracking approaches, which opens new avenues for more flexible and ethologically relevant real-world neuroscience. Abstract : Recent advances in computer vision have made accurate, fast and robust measurement of animal behavior a reality. In the past years powerful tools specifically designed to aid the measurement of behavior have come to fruition. Here we discuss how capturing the postures of animals — pose estimation - has been rapidly advancing with new deep learning methods. While challenges still remain, we envision that the fast-paced development of new deep learning tools will rapidly change the landscape of realizable real-world neuroscience.