Measuring functional connectivity in MEG: A multivariate approach insensitive to linear source leakage

被引:241
作者
Brookes, M. J. [1 ]
Woolrich, M. W. [2 ]
Barnes, G. R. [3 ]
机构
[1] Univ Nottingham, Sch Phys & Astron, Sir Peter Mansfield Magnet Resonance Ctr, Nottingham NG7 2RD, England
[2] Univ Oxford, Warneford Hosp, Oxford Ctr Human Brain Act, Oxford, England
[3] UCL, Wellcome Trust Ctr Neuroimaging, London, England
基金
英国惠康基金; 英国医学研究理事会;
关键词
MEG; Neural oscillations; Functional connectivity; Multivariate analysis; RESTING STATE NETWORKS; HUMAN BRAIN; EEG DATA; MAGNETOENCEPHALOGRAPHY; LOCALIZATION; BEAMFORMER; HUMANS;
D O I
10.1016/j.neuroimage.2012.03.048
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
A number of recent studies have begun to show the promise of magnetoencephalography (MEG) as a means to non-invasively measure functional connectivity within distributed networks in the human brain. However, a number of problems with the methodology still remain - the biggest of these being how to deal with the non-independence of voxels in source space, often termed signal leakage. In this paper we demonstrate a method by which non-zero lag cortico-cortical interactions between the power envelopes of neural oscillatory processes can be reliably identified within a multivariate statistical framework. The method is spatially unbiased, moderately conservative in false positive rate and removes linear signal leakage between seed and target voxels. We demonstrate this methodology in simulation and in real MEG data. The multivariate method offers a powerful means to capture the high dimensionality and rich information content of MEG signals in a single imaging statistic. Given a significant interaction between two areas, we go on to show how classical statistical tests can be used to quantify the importance of the data features driving the interaction. (C) 2012 Elsevier Inc. All rights reserved.
引用
收藏
页码:910 / 920
页数:11
相关论文
共 43 条
[1]  
[Anonymous], 1998, Recent Advances in Biomagnetism
[2]   Controlling false positive rates in mass-multivariate tests for electromagnetic responses [J].
Barnes, Gareth R. ;
Litvak, Vladimir ;
Brookes, Matt J. ;
Friston, Karl J. .
NEUROIMAGE, 2011, 56 (03) :1072-1081
[3]   Optimising experimental design for MEG beamformer imaging [J].
Brookes, Matthew J. ;
Vrba, Jiri ;
Robinson, Stephen E. ;
Stevenson, Claire M. ;
Peters, Andrew M. ;
Barnes, Gareth R. ;
Hillebrand, Arjan ;
Morris, Peter G. .
NEUROIMAGE, 2008, 39 (04) :1788-1802
[4]   Investigating the electrophysiological basis of resting state networks using magnetoencephalography [J].
Brookes, Matthew J. ;
Woolrich, Mark ;
Luckhoo, Henry ;
Price, Darren ;
Hale, Joanne R. ;
Stephenson, Mary C. ;
Barnes, Gareth R. ;
Smith, Stephen M. ;
Morris, Peter G. .
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2011, 108 (40) :16783-16788
[5]   Measuring functional connectivity using MEG: Methodology and comparison with fcMRI [J].
Brookes, Matthew J. ;
Hale, Joanne R. ;
Zumer, Johanna M. ;
Stevenson, Claire M. ;
Francis, Susan T. ;
Barnes, Gareth R. ;
Owen, Julia P. ;
Morris, Peter G. ;
Nagarajan, Srikantan S. .
NEUROIMAGE, 2011, 56 (03) :1082-1104
[6]   Investigating spatial specificity and data averaging in MEG [J].
Brookes, Matthew J. ;
Zumer, Johanna M. ;
Stevenson, Claire M. ;
Hale, Joanne R. ;
Barnes, Gareth R. ;
Vrba, Jiri ;
Morris, Peter G. .
NEUROIMAGE, 2010, 49 (01) :525-538
[7]   High gamma power is phase-locked to theta oscillations in human neocortex [J].
Canolty, R. T. ;
Edwards, E. ;
Dalal, S. S. ;
Soltani, M. ;
Nagarajan, S. S. ;
Kirsch, H. E. ;
Berger, M. S. ;
Barbaro, N. M. ;
Knight, R. T. .
SCIENCE, 2006, 313 (5793) :1626-1628
[8]  
Chatfield C., 1980, Introduction to Multivariate Analysis
[9]   Temporal dynamics of spontaneous MEG activity in brain networks [J].
de Pasquale, Francesco ;
Della Penna, Stefania ;
Snyder, Abraham Z. ;
Lewis, Christopher ;
Mantini, Dante ;
Marzetti, Laura ;
Belardinelli, Paolo ;
Ciancetta, Luca ;
Pizzella, Vittorio ;
Romani, Gian Luca ;
Corbetta, Maurizio .
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2010, 107 (13) :6040-6045
[10]   Dual-Core Beamformer for obtaining highly correlated neuronal networks in MEG [J].
Diwakar, Mithun ;
Huang, Ming-Xiong ;
Srinivasan, Ramesh ;
Harrington, Deborah L. ;
Robb, Ashley ;
Angeles, Annemarie ;
Muzzatti, Laura ;
Pakdaman, Reza ;
Song, Tao ;
Theilmann, Rebecca J. ;
Lee, Roland R. .
NEUROIMAGE, 2011, 54 (01) :253-263