Abstrakt
Originalsprog | Engelsk |
---|---|
Tidsskrift | Proceedings of the National Academy of Sciences of the United States of America |
Vol/bind | 107 |
Udgave nummer | 10 |
Sider (fra-til) | 4734-9 |
Antal sider | 5 |
ISSN | 0027-8424 |
DOI | |
Status | Udgivet - 2010 |
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Toward discovery science of human brain function. / Biswal, Bharat B; Mennes, Maarten; Zuo, Xi-Nian et al.
I: Proceedings of the National Academy of Sciences of the United States of America, Bind 107, Nr. 10, 2010, s. 4734-9.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › peer review
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TY - JOUR
T1 - Toward discovery science of human brain function
AU - Biswal, Bharat B
AU - Mennes, Maarten
AU - Zuo, Xi-Nian
AU - Gohel, Suril
AU - Kelly, Clare
AU - Smith, Steve M
AU - Beckmann, Christian F
AU - Adelstein, Jonathan S
AU - Buckner, Randy L
AU - Colcombe, Stan
AU - Dogonowski, Anne-Marie
AU - Ernst, Monique
AU - Fair, Damien
AU - Hampson, Michelle
AU - Hoptman, Matthew J
AU - Hyde, James S
AU - Kiviniemi, Vesa J
AU - Kötter, Rolf
AU - Li, Shi-Jiang
AU - Lin, Ching-Po
AU - Lowe, Mark J
AU - Mackay, Clare
AU - Madden, David J
AU - Madsen, Kristoffer H
AU - Margulies, Daniel S
AU - Mayberg, Helen S
AU - McMahon, Katie
AU - Monk, Christopher S
AU - Mostofsky, Stewart H
AU - Nagel, Bonnie J
AU - Pekar, James J
AU - Peltier, Scott J
AU - Petersen, Steven E
AU - Riedl, Valentin
AU - Rombouts, Serge A R B
AU - Rypma, Bart
AU - Schlaggar, Bradley L
AU - Schmidt, Sein
AU - Seidler, Rachael D
AU - Siegle, Greg J
AU - Sorg, Christian
AU - Teng, Gao-Jun
AU - Veijola, Juha
AU - Villringer, Arno
AU - Walter, Martin
AU - Wang, Lihong
AU - Weng, Xu-Chu
AU - Whitfield-Gabrieli, Susan
AU - Williamson, Peter
AU - Windischberger, Christian
AU - Zang, Yu-Feng
AU - Zhang, Hong-Ying
AU - Castellanos, F Xavier
AU - Milham, Michael P
PY - 2010
Y1 - 2010
N2 - Although it is being successfully implemented for exploration of the genome, discovery science has eluded the functional neuroimaging community. The core challenge remains the development of common paradigms for interrogating the myriad functional systems in the brain without the constraints of a priori hypotheses. Resting-state functional MRI (R-fMRI) constitutes a candidate approach capable of addressing this challenge. Imaging the brain during rest reveals large-amplitude spontaneous low-frequency (<0.1 Hz) fluctuations in the fMRI signal that are temporally correlated across functionally related areas. Referred to as functional connectivity, these correlations yield detailed maps of complex neural systems, collectively constituting an individual's "functional connectome." Reproducibility across datasets and individuals suggests the functional connectome has a common architecture, yet each individual's functional connectome exhibits unique features, with stable, meaningful interindividual differences in connectivity patterns and strengths. Comprehensive mapping of the functional connectome, and its subsequent exploitation to discern genetic influences and brain-behavior relationships, will require multicenter collaborative datasets. Here we initiate this endeavor by gathering R-fMRI data from 1,414 volunteers collected independently at 35 international centers. We demonstrate a universal architecture of positive and negative functional connections, as well as consistent loci of inter-individual variability. Age and sex emerged as significant determinants. These results demonstrate that independent R-fMRI datasets can be aggregated and shared. High-throughput R-fMRI can provide quantitative phenotypes for molecular genetic studies and biomarkers of developmental and pathological processes in the brain. To initiate discovery science of brain function, the 1000 Functional Connectomes Project dataset is freely accessible at www.nitrc.org/projects/fcon_1000/.
AB - Although it is being successfully implemented for exploration of the genome, discovery science has eluded the functional neuroimaging community. The core challenge remains the development of common paradigms for interrogating the myriad functional systems in the brain without the constraints of a priori hypotheses. Resting-state functional MRI (R-fMRI) constitutes a candidate approach capable of addressing this challenge. Imaging the brain during rest reveals large-amplitude spontaneous low-frequency (<0.1 Hz) fluctuations in the fMRI signal that are temporally correlated across functionally related areas. Referred to as functional connectivity, these correlations yield detailed maps of complex neural systems, collectively constituting an individual's "functional connectome." Reproducibility across datasets and individuals suggests the functional connectome has a common architecture, yet each individual's functional connectome exhibits unique features, with stable, meaningful interindividual differences in connectivity patterns and strengths. Comprehensive mapping of the functional connectome, and its subsequent exploitation to discern genetic influences and brain-behavior relationships, will require multicenter collaborative datasets. Here we initiate this endeavor by gathering R-fMRI data from 1,414 volunteers collected independently at 35 international centers. We demonstrate a universal architecture of positive and negative functional connections, as well as consistent loci of inter-individual variability. Age and sex emerged as significant determinants. These results demonstrate that independent R-fMRI datasets can be aggregated and shared. High-throughput R-fMRI can provide quantitative phenotypes for molecular genetic studies and biomarkers of developmental and pathological processes in the brain. To initiate discovery science of brain function, the 1000 Functional Connectomes Project dataset is freely accessible at www.nitrc.org/projects/fcon_1000/.
KW - Adolescent
KW - Adult
KW - Age Factors
KW - Aged
KW - Algorithms
KW - Analysis of Variance
KW - Brain
KW - Brain Mapping
KW - Female
KW - Humans
KW - Magnetic Resonance Imaging
KW - Male
KW - Middle Aged
KW - Neural Pathways
KW - Sex Factors
KW - Young Adult
U2 - 10.1073/pnas.0911855107
DO - 10.1073/pnas.0911855107
M3 - Journal article
C2 - 20176931
VL - 107
SP - 4734
EP - 4739
JO - National Academy of Sciences. Proceedings
JF - National Academy of Sciences. Proceedings
SN - 0027-8424
IS - 10
ER -