Empirical Bayesian localization of event-related time-frequency neural activity dynamics.

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作者： Chang,Cai ^[1] ; Leighton,Hinkley ^[2] ; Yijing,Gao ^[2] ; Ali,Hashemi ^[3] ; Stefan,Haufe ^[4] ; Kensuke,Sekihara ^[5] ; Srikantan S,Nagarajan ^[6]

作者单位： National Engineering Research Center for E-Learning, Central China Normal University, Wuhan, China; Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA 94143-0628, United States. Electronic address: ccai@ccnu.edu.cn. ^[1] Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA 94143-0628, United States. ^[2] Berlin Center for Advanced Neuroimaging, Charité Universitätsmedizin Berlin, Berlin, Germany; Machine Learning Group, Electrical Engineering and Computer Science Faculty, Technische Universität Berlin, Germany; Institut für Mathematik, Technische Universität Berlin, Germany. ^[3] Berlin Center for Advanced Neuroimaging, Charité Universitätsmedizin Berlin, Berlin, Germany; Bernstein Center for Computational Neuroscience Berlin, Berlin, Germany. ^[4] Department of Advanced Technology in Medicine, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo 113-8519, Japan; Signal Analysis Inc., Hachioji, Tokyo, Japan. ^[5] Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA 94143-0628, United States. Electronic address: sri@ucsf.edu. ^[6]

关键词 Bayesian inference Brain source power changes Dynamics of neural activity Electromagnetic brain imaging Five-dimensional neuroimaging

主题词算法(Algorithms);贝叶斯定理(Bayes Theorem);脑(Brain);脑图(Brain Mapping);脑电描记术(Electroencephalography);人类(Humans);脑磁图描记术(Magnetoencephalography)

DOI 10.1016/j.neuroimage.2022.119369

PMID 35700943

发布时间 2023-08-11

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