Adding dynamics to the Human Connectome Project with MEG

被引：156

作者：

Larson-Prior, L. J. ^{[1
,2
]}

Oostenveld, R. ^{[3
]}

Della Penna, S. ^{[4
,5
]}

Michalareas, G. ^{[6
]}

Prior, F. ^{[1
]}

Babajani-Feremi, A. ^{[7
]}

Schoffelen, J. -M. ^{[3
,10
]}

Marzetti, L. ^{[4
,5
]}

de Pasquale, F. ^{[4
,5
]}

Di Pompeo, F. ^{[4
,5
]}

Stout, J. ^{[9
]}

Woolrich, M. ^{[8
]}

Luo, Q. ^{[9
]}

Bucholz, R. ^{[9
]}

Fries, P. ^{[6
]}

Pizzella, V. ^{[4
,5
]}

Romani, G. L. ^{[4
,5
]}

Corbetta, M. ^{[1
,2
]}

Snyder, A. Z. ^{[1
,2
]}

机构：

[1] Washington Univ, Dept Radiol, St Louis, MO USA

[2] Washington Univ, Dept Neurol, St Louis, MO USA

[3] Radboud Univ Nijmegen, Donders Inst Brain Cognit & Behav, NL-6525 ED Nijmegen, Netherlands

[4] Univ G DAnnunzio, Dept Neurosci & Imaging, Chieti, Italy

[5] Univ G DAnnunzio, Inst Adv Biomed Technol, Chieti, Italy

[6] Max Planck Gesell, ESI, Frankfurt, Germany

[7] Washington Univ, Dept Anat & Neurobiol, St Louis, MO USA

[8] Univ Oxford, Oxford Ctr Human Brain Act OHBA, Oxford, England

[9] St Louis Univ, Dept Neurosurg, St Louis, MO 63103 USA

[10] Max Planck Inst Psycholinguist, Nijmegen, Netherlands

来源：

NEUROIMAGE | 2013年 / 80卷

基金：

英国惠康基金;

关键词：

Magnetoencephalography (MEG); Connectome; Processing pipeline; Functional connectivity; RESTING-STATE NETWORKS; DEPENDENT FUNCTIONAL CONNECTIVITY; INDEPENDENT COMPONENT ANALYSIS; WORKING-MEMORY; PREFRONTAL CORTEX; CAUSAL RELATIONS; BRAIN ACTIVITY; MOTOR CORTEX; ALPHA-RHYTHM; FMRI;

D O I：

10.1016/j.neuroimage.2013.05.056

中图分类号：

Q189 [神经科学];

学科分类号：

071006 ;

摘要：

The Human Connectome Project (HCP) seeks to map the structural and functional connections between network elements in the human brain. Magnetoencephalography (MEG) provides a temporally rich source of information on brain network dynamics and represents one source of functional connectivity data to be provided by the HCP. High quality MEG data will be collected from 50 twin pairs both in the resting state and during performance of motor, working memory and language tasks. These data will be available to the general community. Additionally, using the cortical parcellation scheme common to all imaging modalities, the HCP will provide processing pipelines for calculating connection matrices as a function of time and frequency. Together with structural and functional data generated using magnetic resonance imaging methods, these data represent a unique opportunity to investigate brain network connectivity in a large cohort of normal adult human subjects. The analysis pipeline software and the dynamic connectivity matrices that it generates will all be made freely available to the research community. (C) 2013 Elsevier Inc. All rights reserved.

引用

页码：190 / 201

页数：12

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