Bayesian Algorithms for Joint Estimation of Brain Activity and Noise in Electromagnetic Imaging

Author:

Cai Chang1ORCID,Kang Huicong2ORCID,Hashemi Ali3ORCID,Chen Dan4,Diwakar Mithun5,Haufe Stefan6ORCID,Sekihara Kensuke7ORCID,Wu Wei8ORCID,Nagarajan Srikantan S.9ORCID

Affiliation:

1. National Engineering Research Center for E-Learning, Central China Normal University, Wuhan, China

2. Department of Neurology, Tongji Medical College, Tongji Hospital, Huazhong University of Science and Technology, Hubei, Wuhan, China

3. Inverse Modeling and Machine Learning Group, Technische Universität Berlin, Berlin, Uncertainty, Germany

4. School of Computer Science, Wuhan University, Wuhan, China

5. Department of Radiology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA

6. Inverse Modeling and Machine Learning Group, Technische Universität Berlin, Berlin, Uncertainty, Germany,

7. Department of Advanced Technology in Medicine, Tokyo Medical and Dental University, Tokyo, Japan

8. Alto Neuroscience Inc., Los Altos, CA, USA

9. Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA

Funder

National Natural Science Foundation of China

Hubei Provincial Natural Science Foundation of China

Science and Technology Major Project of Hubei Province, China, Next-Generation Artificial Intelligence (AI) Technologies

Research Funds of CCNU from the Colleges' Basic Research and Operation of MOE

Empire State Development's Division of Science, Technology and Innovation

NIH

Department of Defense (DOD) Congressionally Directed Medical Research Program

Alzheimer's Association

Industry Research Contract from Ricoh MEG USA Inc

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Radiological and Ultrasound Technology,Software

Reference38 articles.

1. Testing covariance models for MEG source reconstruction of hippocampal activity

2. Generalized concomitant multi-task lasso for sparse multimodal regression;massias;Proc Int Conf Artif Intell Statist,2018

3. Beamformer reconstruction of correlated sources using a modified source model;brookes;NeuroImage,2006

4. Unification of sparse Bayesian learning algorithms for electromagnetic brain imaging with the majorization minimization framework

5. Probabilistic algorithms for MEG/EEG source reconstruction using temporal basis functions learned from data

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