期刊论文

Cai, C.;Nagarajan, S.S.

英文

NeuroImage

1053-8119

2022

258

119369

10.1016/j.neuroimage.2022.119369

The authors would like to thank Danielle Mizuiri and Anne Findlay for collecting much of the MEG data, and all members and collaborators of the Biomagnetic Imaging Laboratory for their support. CC acknowledges support from National Natural Science Foundation of China grant 62007013 and Hubei Provincial Natural Science Foundation of China under Grant 2021CFB384. AH acknowledges scholarship support from the Machine Learning/Intelligent Data Analysis research group at Technische Universität Berlin, the Berlin Mathematical School (BMS) and the Berlin Mathematics Research Center MATH+. SSN acknowledges support from NIH grants R01EB022717, R01DC013979, R01NS10-0440, R01DC176960, R01DC017091, R01AG062196, UCOP-MRP-17-454755, T32EB001631, DOD CDMRP Grant W81XWH1810741, and an industry research contract from Ricoh MEG Inc. SH acknowledges funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (Grant agreement No. 758985).

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Accurate reconstruction of the spatio-temporal dynamics of event-related cortical oscillations across human brain regions is an important problem in functional brain imaging and human cognitive neuroscience with magnetoencephalography (MEG) and electroencephalography (EEG). The problem is challenging not only in terms of localization of complex source configurations from sensor measurements with unknown noise and interference but also for reconstruction of transient event-related time-frequency dynamics of cortical oscillations. We recently pro...