Toward discovery science of human brain function

Bharat B Biswal; Maarten Mennes; Xi-Nian Zuo; Suril Gohel; Clare Kelly; Steve M Smith; Christian F Beckmann; Jonathan S Adelstein; Randy L Buckner; Stan Colcombe; Anne-Marie Dogonowski; Monique Ernst; Damien Fair; Michelle Hampson; Matthew J Hoptman; James S Hyde; Vesa J Kiviniemi; Rolf Kötter; Shi-Jiang Li; Ching-Po Lin; Mark J Lowe; Clare Mackay; David J Madden; Kristoffer H Madsen; Daniel S Margulies; Helen S Mayberg; Katie McMahon; Christopher S Monk; Stewart H Mostofsky; Bonnie J Nagel; James J Pekar; Scott J Peltier; Steven E Petersen; Valentin Riedl; Serge A R B Rombouts; Bart Rypma; Bradley L Schlaggar; Sein Schmidt; Rachael D Seidler; Greg J Siegle; Christian Sorg; Gao-Jun Teng; Juha Veijola; Arno Villringer; Martin Walter; Lihong Wang; Xu-Chu Weng; Susan Whitfield-Gabrieli; Peter Williamson; Christian Windischberger; Yu-Feng Zang; Hong-Ying Zhang; F Xavier Castellanos; Michael P Milham

doi:10.1073/pnas.0911855107

Toward discovery science of human brain function

Bharat B Biswal, Maarten Mennes, Xi-Nian Zuo, Suril Gohel, Clare Kelly, Steve M Smith, Christian F Beckmann, Jonathan S Adelstein, Randy L Buckner, Stan Colcombe, Anne-Marie Dogonowski, Monique Ernst, Damien Fair, Michelle Hampson, Matthew J Hoptman, James S Hyde, Vesa J Kiviniemi, Rolf Kötter, Shi-Jiang Li, Ching-Po LinMark J Lowe, Clare Mackay, David J Madden, Kristoffer H Madsen, Daniel S Margulies, Helen S Mayberg, Katie McMahon, Christopher S Monk, Stewart H Mostofsky, Bonnie J Nagel, James J Pekar, Scott J Peltier, Steven E Petersen, Valentin Riedl, Serge A R B Rombouts, Bart Rypma, Bradley L Schlaggar, Sein Schmidt, Rachael D Seidler, Greg J Siegle, Christian Sorg, Gao-Jun Teng, Juha Veijola, Arno Villringer, Martin Walter, Lihong Wang, Xu-Chu Weng, Susan Whitfield-Gabrieli, Peter Williamson, Christian Windischberger, Yu-Feng Zang, Hong-Ying Zhang, F Xavier Castellanos, Michael P Milham

Funktions- og Billeddiagnostisk Enhed, MR-Forskningssektionen

2156 Citationer (Scopus)

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Udgivelsesdato: 2010-Mar-9

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	https://doi.org/10.1073/pnas.0911855107
Status	Udgivet - 2010

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10.1073/pnas.0911855107

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Biswal, B. B., Mennes, M., Zuo, X-N., Gohel, S., Kelly, C., Smith, S. M., Beckmann, C. F., Adelstein, J. S., Buckner, R. L., Colcombe, S., Dogonowski, A-M., Ernst, M., Fair, D., Hampson, M., Hoptman, M. J., Hyde, J. S., Kiviniemi, V. J., Kötter, R., Li, S-J., ... Milham, M. P. (2010). Toward discovery science of human brain function. Proceedings of the National Academy of Sciences of the United States of America, 107(10), 4734-9. https://doi.org/10.1073/pnas.0911855107

Biswal, BB, Mennes, M, Zuo, X-N, Gohel, S, Kelly, C, Smith, SM, Beckmann, CF, Adelstein, JS, Buckner, RL, Colcombe, S, Dogonowski, A-M, Ernst, M, Fair, D, Hampson, M, Hoptman, MJ, Hyde, JS, Kiviniemi, VJ, Kötter, R, Li, S-J, Lin, C-P, Lowe, MJ, Mackay, C, Madden, DJ, Madsen, KH, Margulies, DS, Mayberg, HS, McMahon, K, Monk, CS, Mostofsky, SH, Nagel, BJ, Pekar, JJ, Peltier, SJ, Petersen, SE, Riedl, V, Rombouts, SARB, Rypma, B, Schlaggar, BL, Schmidt, S, Seidler, RD, Siegle, GJ, Sorg, C, Teng, G-J, Veijola, J, Villringer, A, Walter, M, Wang, L, Weng, X-C, Whitfield-Gabrieli, S, Williamson, P, Windischberger, C, Zang, Y-F, Zhang, H-Y, Castellanos, FX & Milham, MP 2010, 'Toward discovery science of human brain function', Proceedings of the National Academy of Sciences of the United States of America, bind 107, nr. 10, s. 4734-9. https://doi.org/10.1073/pnas.0911855107

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title = "Toward discovery science of human brain function",

abstract = "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/.",

keywords = "Adolescent, Adult, Age Factors, Aged, Algorithms, Analysis of Variance, Brain, Brain Mapping, Female, Humans, Magnetic Resonance Imaging, Male, Middle Aged, Neural Pathways, Sex Factors, Young Adult",

author = "Biswal, {Bharat B} and Maarten Mennes and Xi-Nian Zuo and Suril Gohel and Clare Kelly and Smith, {Steve M} and Beckmann, {Christian F} and Adelstein, {Jonathan S} and Buckner, {Randy L} and Stan Colcombe and Anne-Marie Dogonowski and Monique Ernst and Damien Fair and Michelle Hampson and Hoptman, {Matthew J} and Hyde, {James S} and Kiviniemi, {Vesa J} and Rolf K{\"o}tter and Shi-Jiang Li and Ching-Po Lin and Lowe, {Mark J} and Clare Mackay and Madden, {David J} and Madsen, {Kristoffer H} and Margulies, {Daniel S} and Mayberg, {Helen S} and Katie McMahon and Monk, {Christopher S} and Mostofsky, {Stewart H} and Nagel, {Bonnie J} and Pekar, {James J} and Peltier, {Scott J} and Petersen, {Steven E} and Valentin Riedl and Rombouts, {Serge A R B} and Bart Rypma and Schlaggar, {Bradley L} and Sein Schmidt and Seidler, {Rachael D} and Siegle, {Greg J} and Christian Sorg and Gao-Jun Teng and Juha Veijola and Arno Villringer and Martin Walter and Lihong Wang and Xu-Chu Weng and Susan Whitfield-Gabrieli and Peter Williamson and Christian Windischberger and Yu-Feng Zang and Hong-Ying Zhang and Castellanos, {F Xavier} and Milham, {Michael P}",

year = "2010",

doi = "10.1073/pnas.0911855107",

language = "English",

volume = "107",

pages = "4734--9",

journal = "National Academy of Sciences. Proceedings",

issn = "0027-8424",

publisher = "National Academy of Sciences",

number = "10",

}

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 -

Toward discovery science of human brain function

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