Abstract

This subproject is one of many research subprojects utilizing theresources provided by a Center grant funded by NIH/NCRR. The subproject andinvestigator (PI) may have received primary funding from another NIH source,and thus could be represented in other CRISP entries. The institution listed isfor the Center, which is not necessarily the institution for the investigator.In our previous studies we have introduced fMRI-weighted MEG and EEG source estimates employing cortical constraints. In this approach, fMRI and MEG/EEG data are analyzed independently and the locations of significant fMRI activity are employed in the MEG/EEG inverse model to bias the solution toward the fMRI result.
The aim of this project is to extend this approach by refining the use of cortical constraints, by creating novel ways to utilize fMRI information in MEG/EEG source modeling, and by integrating the analysis of fMRI/MEG/EEG to a single combined inverse model. The prerequisite of the combined modeling approach is a model for the relationship between the hemodynamic and electromagnetic signals that are being studied in our combined human fMRI, MEG, EEG, and optical studies as well as experiments in animal models conducted by our collaborators.

  Funding Agency

Agency
National Institute of Health (NIH)
Institute
National Center for Research Resources (NCRR)
Type
Biotechnology Resource Grants (P41)
Project #
5P41RR014075-09
Application #
7602565
Study Section
Special Emphasis Panel (ZRG1-SSS-X (40))
Project Start
2007-09-01
Project End
2008-08-31
Budget Start
2007-09-01
Budget End
2008-08-31
Support Year
9
Fiscal Year
2007
Total Cost
$141,214
Indirect Cost

  Institution

Name
Massachusetts General Hospital
Department
Type
DUNS #
073130411
City
Boston
State
MA
Country
United States
Zip Code
02199

  Publications

Lee, Jeungchan; Mawla, Ishtiaq; Kim, Jieun et al. (2018) Machine learning-based prediction of clinical pain using multimodal neuroimaging and autonomic metrics. Pain :
Ina Ly, K; Vakulenko-Lagun, Bella; Emblem, Kyrre E et al. (2018) Probing tumor microenvironment in patients with newly diagnosed glioblastoma during chemoradiation and adjuvant temozolomide with functional MRI. Sci Rep 8:17062
Ellingsen, Dan-Mikael; Napadow, Vitaly; Protsenko, Ekaterina et al. (2018) Brain Mechanisms of Anticipated Painful Movements and Their Modulation by Manual Therapy in Chronic Low Back Pain. J Pain 19:1352-1365
Sawyer, Kayle S; Maleki, Nasim; Papadimitriou, George et al. (2018) Cerebral white matter sex dimorphism in alcoholism: a diffusion tensor imaging study. Neuropsychopharmacology 43:1876-1883
Lee, Jeungchan; Protsenko, Ekaterina; Lazaridou, Asimina et al. (2018) Encoding of Self-Referential Pain Catastrophizing in the Posterior Cingulate Cortex in Fibromyalgia. Arthritis Rheumatol 70:1308-1318
Cushing, Cody A; Im, Hee Yeon; Adams Jr., Reginald B et al. (2018) Neurodynamics and connectivity during facial fear perception: The role of threat exposure and signal congruity. Sci Rep 8:2776
Izen, Sarah C; Chrastil, Elizabeth R; Stern, Chantal E (2018) Resting State Connectivity Between Medial Temporal Lobe Regions and Intrinsic Cortical Networks Predicts Performance in a Path Integration Task. Front Hum Neurosci 12:415
Kang, Dong-Wha; Kim, Dongho; Chang, Li-Hung et al. (2018) Structural and Functional Connectivity Changes Beyond Visual Cortex in a Later Phase of Visual Perceptual Learning. Sci Rep 8:5186
Farrar, Christian T; Gale, Eric M; Kennan, Richard et al. (2018) CM-101: Type I Collagen-targeted MR Imaging Probe for Detection of Liver Fibrosis. Radiology 287:581-589
Gale, Eric M; Wey, Hsiao-Ying; Ramsay, Ian et al. (2018) A Manganese-based Alternative to Gadolinium: Contrast-enhanced MR Angiography, Excretion, Pharmacokinetics, and Metabolism. Radiology 286:865-872

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