Toward discovery science of human brain function.
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/.
Biswal
Bharat B
BB
Department of Radiology, New Jersey Medical School, Newark, NJ 07103, USA.
Mennes
Maarten
M
Zuo
Xi-Nian
XN
Gohel
Suril
S
Kelly
Clare
C
Smith
Steve M
SM
Beckmann
Christian F
CF
Adelstein
Jonathan S
JS
Buckner
Randy L
RL
Colcombe
Stan
S
Dogonowski
Anne-Marie
AM
Ernst
Monique
M
Fair
Damien
D
Hampson
Michelle
M
Hoptman
Matthew J
MJ
Hyde
James S
JS
Kiviniemi
Vesa J
VJ
Kötter
Rolf
R
Li
Shi-Jiang
SJ
Lin
Ching-Po
CP
Lowe
Mark J
MJ
Mackay
Clare
C
Madden
David J
DJ
Madsen
Kristoffer H
KH
Margulies
Daniel S
DS
Mayberg
Helen S
HS
McMahon
Katie
K
Monk
Christopher S
CS
Mostofsky
Stewart H
SH
Nagel
Bonnie J
BJ
Pekar
James J
JJ
Peltier
Scott J
SJ
Petersen
Steven E
SE
Riedl
Valentin
V
Rombouts
Serge A R B
SA
Rypma
Bart
B
Schlaggar
Bradley L
BL
Schmidt
Sein
S
Seidler
Rachael D
RD
Siegle
Greg J
GJ
Sorg
Christian
C
Teng
Gao-Jun
GJ
Veijola
Juha
J
Villringer
Arno
A
Walter
Martin
M
Wang
Lihong
L
Weng
Xu-Chu
XC
Whitfield-Gabrieli
Susan
S
Williamson
Peter
P
Windischberger
Christian
C
Zang
Yu-Feng
YF
Zhang
Hong-Ying
HY
Castellanos
F Xavier
FX
Milham
Michael P
MP
D000293:Adolescent; D000328:Adult; D000367:Age Factors; D000368:Aged; D000465:Algorithms; D000704:Analysis of Variance; D001921:Brain / Q000033:anatomy & histology* / Q000502:physiology*; D001931:Brain Mapping / Q000379:methods*; D005260:Female; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008875:Middle Aged; D009434:Neural Pathways / Q000033:anatomy & histology / Q000502:physiology; D012737:Sex Factors; D055815:Young Adult