Learning Spatiotemporal Brain Dynamics in Adolescents via Multimodal MEG and fMRI Data Fusion Using Joint Tensor/Matrix Decomposition-Reference-Cited by-同舟云学术

Learning Spatiotemporal Brain Dynamics in Adolescents via Multimodal MEG and fMRI Data Fusion Using Joint Tensor/Matrix Decomposition

Published:2024-07 Issue:7 Volume:71 Page:2189-2200
ISSN:0018-9294
Container-title:IEEE Transactions on Biomedical Engineering
language:
Short-container-title:IEEE Trans. Biomed. Eng.

Author:

Belyaeva Irina¹^ORCID,Gabrielson Ben²^ORCID,Wang Yu-Ping³^ORCID,Wilson Tony W.⁴^ORCID,Calhoun Vince D.⁵^ORCID,Stephen Julia M.⁶^ORCID,Adali Tülay²^ORCID

Affiliation:

1. University of Maryland, Baltimore County, Baltimore, MD, USA

2. Department of Computer Science and Electrical Engineering, University of Maryland, Baltimore County, USA

3. Department of Biomedical Engineering, Tulane University, USA

4. Institute for Human Neuroscience, Boys Town National Research Hospital, USA

5. Tri-institutional Center for Translational Research in Neuroimaging and Data Science, USA

6. Mind Research Network a Division of Lovelace Biomedical Research Institute, USA

Funder

NSF-NCS

NSF

NIH

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

https://ieeexplore.ieee.org/ielam/10/10564800/10432933-aam.pdf

Reference68 articles.

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2. Unraveling Diagnostic Biomarkers of Schizophrenia Through Structure-Revealing Fusion of Multi-Modal Neuroimaging Data

3. A M/EEG-fMRI Fusion Primer: Resolving Human Brain Responses in Space and Time

4. A review of multivariate methods for multimodal fusion of brain imaging data

5. Neuronal chronometry of target detection: Fusion of hemodynamic and event-related potential data

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