This proposal aims to support the development of a new """"""""Connectom"""""""" diffusion imaging system, designed with advanced gradient technology (300 mT/m gradient set in an advanced 3T instrument), and optimized for the collection of in vivo structural connectivity data from healthy adult humans. Following installation and optimization of this novel system, we will scan normal human subjects, including a number of subjects recruited from the other HCP site, and begin initial development of software to analyze this data and compare, document and disseminate the results obtained against those developed by other connectomics efforts, including the other HCP site. This work will be integral part of the collaborative HCP effort to construct a map of the human connectome that represents the structural and functional connections in vivo within a brain and across individuals. As a result, this work has significant potential to dramatically advance capabilities to measure the human Connectome, by aggressively optimizing non-invasive imaging technology toward Connectome measurements. This effort builds upon existing multidisciplinary collaboration between Massachusetts General Hospital/Harvard Medical School (MGH) and the University of California-Los Angeles (UCLA), and employs a multiple PI leadership approach, providing a rigorous system of leadership, organization, and oversight to this program of bioengineering, optimization and validation that aims to improve the ability of Diffusion Spectrum Imaging (DSI) to map connectivity in the living human brain.

Public Health Relevance

By fostering investigation of human neural connectivity, the new technology developed through this project has potential to improve understanding of the structure and function relationship in the human brain, and therefore, ultimately facilitate advances in the diagnosis and treatment of many psychiatric and neurological diseases.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project--Cooperative Agreements (U01)
Project #
5U01MH093765-02
Application #
8143497
Study Section
Special Emphasis Panel (ZMH1-ERB-C (04))
Program Officer
Farber, Gregory K
Project Start
2010-09-15
Project End
2013-08-31
Budget Start
2011-09-01
Budget End
2012-08-31
Support Year
2
Fiscal Year
2011
Total Cost
$3,325,813
Indirect Cost
Name
Massachusetts General Hospital
Department
Type
DUNS #
073130411
City
Boston
State
MA
Country
United States
Zip Code
02199
Li, Yi; Barkovich, Matthew J; Karch, Celeste M et al. (2018) Regionally specific TSC1 and TSC2 gene expression in tuberous sclerosis complex. Sci Rep 8:13373
Siless, Viviana; Chang, Ken; Fischl, Bruce et al. (2018) AnatomiCuts: Hierarchical clustering of tractography streamlines based on anatomical similarity. Neuroimage 166:32-45
Fan, Qiuyun; Nummenmaa, Aapo; Wichtmann, Barbara et al. (2018) Validation of diffusion MRI estimates of compartment size and volume fraction in a biomimetic brain phantom using a human MRI scanner with 300?mT/m maximum gradient strength. Neuroimage 182:469-478
Polimeni, Jonathan R; Renvall, Ville; Zaretskaya, Natalia et al. (2018) Analysis strategies for high-resolution UHF-fMRI data. Neuroimage 168:296-320
Li, Hua; Chow, Ho Ming; Chugani, Diane C et al. (2018) Linking spherical mean diffusion weighted signal with intra-axonal volume fraction. Magn Reson Imaging 57:75-82
Amiez, Céline; Wilson, Charles R E; Procyk, Emmanuel (2018) Variations of cingulate sulcal organization and link with cognitive performance. Sci Rep 8:13988
Zaretskaya, Natalia; Fischl, Bruce; Reuter, Martin et al. (2018) Advantages of cortical surface reconstruction using submillimeter 7 T MEMPRAGE. Neuroimage 165:11-26
Uesaki, Maiko; Takemura, Hiromasa; Ashida, Hiroshi (2018) Computational neuroanatomy of human stratum proprium of interparietal sulcus. Brain Struct Funct 223:489-507
Wang, Hui; Magnain, Caroline; Wang, Ruopeng et al. (2018) as-PSOCT: Volumetric microscopic imaging of human brain architecture and connectivity. Neuroimage 165:56-68
Li, Hua; Chow, Ho Ming; Chugani, Diane C et al. (2018) Minimal number of gradient directions for robust measurement of spherical mean diffusion weighted signal. Magn Reson Imaging 54:148-152

Showing the most recent 10 out of 137 publications