Correspondence of the brain's functional architecture during activation and rest

被引:3851
作者
Smith, Stephen M. [1 ]
Fox, Peter T. [2 ]
Miller, Karla L. [1 ]
Glahn, David C. [2 ,3 ]
Fox, P. Mickle [2 ]
Mackay, Clare E. [1 ]
Filippini, Nicola [1 ]
Watkins, Kate E. [1 ]
Toro, Roberto [4 ]
Laird, Angela R. [2 ]
Beckmann, Christian F. [1 ,5 ]
机构
[1] Univ Oxford, Ctr Funct MRI Brain, Oxford OX3 9DU, England
[2] Univ Texas Hlth Sci Ctr San Antonio, Res Imaging Ctr, San Antonio, TX 78229 USA
[3] Yale Univ, Inst Living, Olin Neuropsychiat Res Ctr, New Haven, CT 06106 USA
[4] Inst Pasteur, F-75724 Paris, France
[5] Univ London Imperial Coll Sci Technol & Med, Dept Clin Neurosci, London SW7 2AZ, England
基金
英国工程与自然科学研究理事会;
关键词
brain connectivity; BrainMap; FMRI; functional connectivity; resting-state networks; INDEPENDENT COMPONENT ANALYSIS; BLIND SEPARATION; STATE NETWORKS; MOTOR CORTEX; DEFAULT-MODE; CONNECTIVITY; FMRI; FLUCTUATIONS; METAANALYSIS; MRI;
D O I
10.1073/pnas.0905267106
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Neural connections, providing the substrate for functional networks, exist whether or not they are functionally active at any given moment. However, it is not known to what extent brain regions are continuously interacting when the brain is "at rest.'' In this work, we identify the major explicit activation networks by carrying out an image-based activation network analysis of thousands of separate activation maps derived from the BrainMap database of functional imaging studies, involving nearly 30,000 human subjects. Independently, we extract the major covarying networks in the resting brain, as imaged with functional magnetic resonance imaging in 36 subjects at rest. The sets of major brain networks, and their decompositions into subnetworks, show close correspondence between the independent analyses of resting and activation brain dynamics. We conclude that the full repertoire of functional networks utilized by the brain in action is continuously and dynamically "active'' even when at "rest.''
引用
收藏
页码:13040 / 13045
页数:6
相关论文
共 40 条
  • [1] Probabilistic independent component analysis for functional magnetic resonance imaging
    Beckmann, CF
    Smith, SA
    [J]. IEEE TRANSACTIONS ON MEDICAL IMAGING, 2004, 23 (02) : 137 - 152
  • [2] Investigations into resting-state connectivity using independent component analysis
    Beckmann, CF
    DeLuca, M
    Devlin, JT
    Smith, SM
    [J]. PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES, 2005, 360 (1457) : 1001 - 1013
  • [3] AN INFORMATION MAXIMIZATION APPROACH TO BLIND SEPARATION AND BLIND DECONVOLUTION
    BELL, AJ
    SEJNOWSKI, TJ
    [J]. NEURAL COMPUTATION, 1995, 7 (06) : 1129 - 1159
  • [4] The effect of respiration variations on independent component analysis results of resting state functional connectivity
    Birn, Rasmus M.
    Murphy, Kevin
    Bandettini, Peter A.
    [J]. HUMAN BRAIN MAPPING, 2008, 29 (07) : 740 - 750
  • [5] Separating respiratory-variation-related neuronal-activity-related fluctuations in fluctuations from fMRI
    Birn, RM
    Diamond, JB
    Smith, MA
    Bandettini, PA
    [J]. NEUROIMAGE, 2006, 31 (04) : 1536 - 1548
  • [6] FUNCTIONAL CONNECTIVITY IN THE MOTOR CORTEX OF RESTING HUMAN BRAIN USING ECHO-PLANAR MRI
    BISWAL, B
    YETKIN, FZ
    HAUGHTON, VM
    HYDE, JS
    [J]. MAGNETIC RESONANCE IN MEDICINE, 1995, 34 (04) : 537 - 541
  • [7] Unrest at rest: Default activity and spontaneous network correlations
    Buckner, Randy L.
    Vincent, Justin L.
    [J]. NEUROIMAGE, 2007, 37 (04) : 1091 - 1096
  • [8] INDEPENDENT COMPONENT ANALYSIS, A NEW CONCEPT
    COMON, P
    [J]. SIGNAL PROCESSING, 1994, 36 (03) : 287 - 314
  • [9] Cordes D, 2000, AM J NEURORADIOL, V21, P1636
  • [10] Consistent resting-state networks across healthy subjects
    Damoiseaux, J. S.
    Rombouts, S. A. R. B.
    Barkhof, F.
    Scheltens, P.
    Stam, C. J.
    Smith, S. M.
    Beckmann, C. F.
    [J]. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2006, 103 (37) : 13848 - 13853