Taiki Yabumoto1, Fumiaki Yoshida2, Hideaki Miyauchi3, Kousuke Baba4, Hiroshi Tsuda1, Kensuke Ikenaka1, Hideki Hayakawa1, Nozomu Koyabu5, Hiroki Hamanaka6, Stella M Papa7, Masayuki Hirata8, Hideki Mochizuki9. 1. Department of Neurology, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan. 2. Department of Neurological Diagnosis and Restoration, Graduat School of Medicine, Osaka University, Suita, Osaka, Japan; Department of Neurosurgery, Osaka University Medical School, Suita, Osaka, Japan; Department of Anatomy & Physiology, Faculty of Medicine, Saga University, Saga, Japan; Japan Science and Technology Agency, PRESTO, Japan. 3. COCOSNET Ltd., Fukuoka, Japan. 4. Department of Neurology, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan; Department of Advanced Hybrid Medicine, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan. 5. The Institute of Large Laboratory Animal Sciences, Center of Medical Innovation and Translational Research, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan. 6. Department of Neurological Diagnosis and Restoration, Graduat School of Medicine, Osaka University, Suita, Osaka, Japan. 7. Yerkes National Primate Research Center, Emory University, Atlanta, GA, USA; Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA. 8. Department of Neurological Diagnosis and Restoration, Graduat School of Medicine, Osaka University, Suita, Osaka, Japan; Department of Neurosurgery, Osaka University Medical School, Suita, Osaka, Japan; Center for Information and Neural Networks, National Institute of Information and Communications Technology and Osaka University, Osaka, Japan. Electronic address: mhirata@cne.mei.osaka-u.ac.jp. 9. Department of Neurology, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan. Electronic address: hmochizuki@neurol.med.osaka-u.ac.jp.
Abstract
BACKGROUND: Callithrix jacchus, generally known as the common marmoset, has recently garnered interest as an experimental primate model for better understanding the basis of human social behavior, architecture and function. Modelling human neurological and psychological diseases in marmosets can enhance the knowledge obtained from rodent research for future pre-clinical studies. Hence, comprehensive and quantitative assessments of marmoset behaviors are crucial. However, systems for monitoring and analyzing marmoset behaviors have yet to be established. NEW METHOD: In this paper, we present a novel multimodal system, MarmoDetector, for the automated 3D analysis of marmoset behavior under freely moving conditions. MarmoDetector allows the quantitative assessment of marmoset behaviors using computerised tracking analysis techniques that are based on a Kinect system equipped with video recordings, infrared images and depth analysis. RESULTS: Using MarmoDetector, we assessed behavioral circadian rhythms continuously over several days in home cages. In addition, MarmoDetector detected acute, transient complex behaviors of alcohol injected marmosets. COMPARISON TO EXISTING METHOD: Compared to 2D recording, MarmoDetector detects activities more precisely and is very sensitive as we could detect behavioral defects specifically induced by alcohol administration. CONCLUSION: MarmoDetector facilitates the rapid and accurate analysis of marmoset behavior and will enhance research on the neural basis of brain disorders.
BACKGROUND:Callithrix jacchus, generally known as the common marmoset, has recently garnered interest as an experimental primate model for better understanding the basis of human social behavior, architecture and function. Modelling human neurological and psychological diseases in marmosets can enhance the knowledge obtained from rodent research for future pre-clinical studies. Hence, comprehensive and quantitative assessments of marmoset behaviors are crucial. However, systems for monitoring and analyzing marmoset behaviors have yet to be established. NEW METHOD: In this paper, we present a novel multimodal system, MarmoDetector, for the automated 3D analysis of marmoset behavior under freely moving conditions. MarmoDetector allows the quantitative assessment of marmoset behaviors using computerised tracking analysis techniques that are based on a Kinect system equipped with video recordings, infrared images and depth analysis. RESULTS: Using MarmoDetector, we assessed behavioral circadian rhythms continuously over several days in home cages. In addition, MarmoDetector detected acute, transient complex behaviors of alcohol injected marmosets. COMPARISON TO EXISTING METHOD: Compared to 2D recording, MarmoDetector detects activities more precisely and is very sensitive as we could detect behavioral defects specifically induced by alcohol administration. CONCLUSION: MarmoDetector facilitates the rapid and accurate analysis of marmoset behavior and will enhance research on the neural basis of brain disorders.
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