Toward discovery science of human brain function

Bharat B. Biswal1, Maarten Mennes2, Xi‐Nian Zuo2, Suril Gohel1, Clare Kelly2, Stephen M. Smith3, Christian F. Beckmann3, Jonathan S. Adelstein2, Randy L. Buckner4, Stan Colcombe5, Anne-Marie Dogonowski6, Monique Ernst7, Damien A. Fair8, Michelle Hampson9, Matthew J. Hoptman10, James S. Hyde11, Vesa Kiviniemi12, Rolf Kötter13, Shi-Jiang Li11, Ching‐Po Lin14, Mark J. Lowe15, Clare E. Mackay3, David J. Madden16, Kristoffer H. Madsen6, Daniel S. Margulies17, Helen S. Mayberg18, Katie L. McMahon19, Christopher S. Monk20, Stewart H. Mostofsky21, Bonnie J. Nagel22, James J. Pekar23, Scott Peltier24, Steven E. Petersen25, Valentin Riedl26, Serge A.R.B. Rombouts27, Bart Rypma28, Bradley L. Schlaggar29, Sein Schmidt30, Rachael D. Seidler20,31, Greg J. Siegle32, Christian Sorg33, Gao‐Jun Teng34, Juha Veijola35, Arno Villringer36,30, Martin Walter37, Lihong Wang16, Xuefei Weng38,39, Susan Whitfield‐Gabrieli40, Peter Williamson41, Christian Windischberger42, Yu‐Feng Zang43, Hong-Ying Zhang34, F. Xavier Castellanos10,2, Michael P. Milham2
1Rutgers, The State University of New Jersey, New Brunswick, United States
2Phyllis Green and Randolph Cōwen Institute for Pediatric Neuroscience, New York University Child Study Center, NYU Langone Medical Center, New York, NY 10016;
3FMRIB Centre, Oxford University, Oxford OX3 9DU, UK;
4Howard Hughes Medical Institute, Harvard University, Cambridge, MA 02138;
5School of Psychology, University of Wales, Bangor, UK
6Danish Research Centre for Magnetic Resonance, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark
7Mood and Anxiety Disorders Program, National Institute of Mental Health/National Institutes of Health, Department of Health and Human Services, Bethesda, MD 20892;
8Behavioral Neuroscience Department, Oregon Health & Science University, Portland, OR 97239;
9Department of Diagnostic Radiology, Yale University School of Medicine, New Haven, CT 06511;
10Division of Clinical Research, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY 10962;
11Biophysics Research Institute, Medical College of Wisconsin, Milwaukee, WI 53226
12Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland
13Donders Institute for Brain, Cognition, and Behavior, Center for Neuroscience, Radboud University Nijmegen Medical Center, 6500 HB Nijmegen, The Netherlands;
14Institute of Neuroscience, National Yang-Ming University, Taiwan
15Imaging Institute, The Cleveland Clinic, Cleveland, OH 44195;
16Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC, 27710;
17Department of Cognitive Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, 04103 Leipzig, Germany
18Department of Psychiatry and Department of Neurology, Emory University School of Medicine, Atlanta, GA 30322;
19Centre for Advanced Imaging, University of Queensland, Brisbane, Australia
20Department of Psychology, University of Michigan, Ann Arbor, MI 48109;
21Laboratory for Neurocognitive and Imaging Research, Kennedy Krieger Institute, Baltimore, MD, 21205;
22Department of Psychiatry, Oregon Health & Science University, Portland, OR 97239;
23F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD 21205;
24Functional MRI Laboratory, University of Michigan, Ann Arbor, MI 48109;
25McDonnell Center for Higher Brain Functions, Washington University School of Medicine, St. Louis, MO 63110;
26Departments of Neurology and Neuroradiology, Klinikum Rechts der Isar, Technische Universität München, 81675 Munich, Germany;
27Institute of Psychology and Department of Radiology, Leiden University Medical Center, Leiden University, Leiden, The Netherlands;
28Center for Brain Health and School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, TX 75080;
29Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
30Department of Neurology, Charité Univesitaetsmedizin-Berlin, 10117 Berlin, Germany;
31School of Kinesiology, University of Michigan, Ann Arbor, MI 48109;
32Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA 15213;
33Department of Psychiatry, Klinikum Rechts der Isar, Technische Universität München, D-81675 Munich, Germany;
34Jiangsu Key Laboratory of Molecular and Functional Imaging, Department of Radiology, Zhong-Da Hospital, Southeast University, Nanjing 210009, China;
35Department of Psychiatry, Institute of Clinical Medicine and Department of Public Health Science, Institute of Health Science, University of Oulu, Oulu 90014, Finland;
36Berlin NeuroImaging Center, 10099 Berlin, Germany;
37Department of Psychiatry, Otto-von-Guericke University of Magdeburg, Magdeburg 39106, Germany;
38Laboratory for Higher Brain Function, Institute of Psychology, Chinese Academy of Sciences, Beijing 100864, China;
39Washington University, St. Louis, MO
40Department of Brain and Cognitive Sciences, Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Boston, MA 02139;
41Department of Psychiatry, University of Western Ontario, London, ON N6A3H8, Canada;
42Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria; and
43State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China

Tóm tắt

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/ .

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