TY - JOUR
T1 - Pushing spatial and temporal resolution for functional and diffusion MRI in the Human Connectome Project
AU - Uǧurbil, Kamil
AU - Xu, Junqian
AU - Auerbach, Edward J.
AU - Moeller, Steen
AU - Vu, An T.
AU - Duarte-Carvajalino, Julio M.
AU - Lenglet, Christophe
AU - Wu, Xiaoping
AU - Schmitter, Sebastian
AU - Van de Moortele, Pierre Francois
AU - Strupp, John
AU - Sapiro, Guillermo
AU - De Martino, Federico
AU - Wang, Dingxin
AU - Harel, Noam
AU - Garwood, Michael
AU - Chen, Liyong
AU - Feinberg, David A.
AU - Smith, Stephen M.
AU - Miller, Karla L.
AU - Sotiropoulos, Stamatios N.
AU - Jbabdi, Saad
AU - Andersson, Jesper L R
AU - Behrens, Timothy E J
AU - Glasser, Matthew F.
AU - Van Essen, David C.
AU - Yacoub, Essa
N1 - Funding Information:
The work reported in this article was supported by the Human Connectome Project ( 1U54MH091657 ) from the 16 Institutes and Centers of the National Institutes of Health that support the NIH Blueprint for Neuroscience Research and by the Biotechnology Research Center (BTRC) grant P41 EB015894 from NIBIB , and NINDS Institutional Center Core Grant P30 NS076408 .
Funding Information:
A 10.5 T system, funded by NIH grants other than HCP and non-NIH sources, is being developed in CMRR. This system is currently delayed due to world-wide helium shortages. Should it become operational within the funding period of the current HCP initiative, it will be explored for HCP studies as well.
PY - 2013/10/15
Y1 - 2013/10/15
N2 - The Human Connectome Project (HCP) relies primarily on three complementary magnetic resonance (MR) methods. These are: 1) resting state functional MR imaging (rfMRI) which uses correlations in the temporal fluctuations in an fMRI time series to deduce '. functional connectivity'; 2) diffusion imaging (dMRI), which provides the input for tractography algorithms used for the reconstruction of the complex axonal fiber architecture; and 3) task based fMRI (tfMRI), which is employed to identify functional parcellation in the human brain in order to assist analyses of data obtained with the first two methods. We describe technical improvements and optimization of these methods as well as instrumental choices that impact speed of acquisition of fMRI and dMRI images at 3. T, leading to whole brain coverage with 2. mm isotropic resolution in 0.7. s for fMRI, and 1.25. mm isotropic resolution dMRI data for tractography analysis with three-fold reduction in total dMRI data acquisition time. Ongoing technical developments and optimization for acquisition of similar data at 7. T magnetic field are also presented, targeting higher spatial resolution, enhanced specificity of functional imaging signals, mitigation of the inhomogeneous radio frequency (RF) fields, and reduced power deposition. Results demonstrate that overall, these approaches represent a significant advance in MR imaging of the human brain to investigate brain function and structure.
AB - The Human Connectome Project (HCP) relies primarily on three complementary magnetic resonance (MR) methods. These are: 1) resting state functional MR imaging (rfMRI) which uses correlations in the temporal fluctuations in an fMRI time series to deduce '. functional connectivity'; 2) diffusion imaging (dMRI), which provides the input for tractography algorithms used for the reconstruction of the complex axonal fiber architecture; and 3) task based fMRI (tfMRI), which is employed to identify functional parcellation in the human brain in order to assist analyses of data obtained with the first two methods. We describe technical improvements and optimization of these methods as well as instrumental choices that impact speed of acquisition of fMRI and dMRI images at 3. T, leading to whole brain coverage with 2. mm isotropic resolution in 0.7. s for fMRI, and 1.25. mm isotropic resolution dMRI data for tractography analysis with three-fold reduction in total dMRI data acquisition time. Ongoing technical developments and optimization for acquisition of similar data at 7. T magnetic field are also presented, targeting higher spatial resolution, enhanced specificity of functional imaging signals, mitigation of the inhomogeneous radio frequency (RF) fields, and reduced power deposition. Results demonstrate that overall, these approaches represent a significant advance in MR imaging of the human brain to investigate brain function and structure.
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U2 - 10.1016/j.neuroimage.2013.05.012
DO - 10.1016/j.neuroimage.2013.05.012
M3 - Article
C2 - 23702417
AN - SCOPUS:84880328621
SN - 1053-8119
VL - 80
SP - 80
EP - 104
JO - NeuroImage
JF - NeuroImage
ER -