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Identifying true cortical interactions in MEG using the nulling beamformer

Hua Brian Hui, Dimitrios Pantazis, Steven L. Bressler, Richard M. Leahy
2010 NeuroImage  
We estimate interaction measures from the output of the modified beamformer and test for statistical significance using permutation tests.  ...  In this article, we describe a modified beamforming approach to accurately measure cortical interactions from EEG/MEG data, designed to suppress cross-talk between cortical regions.  ...  Acknowledgments This work was supported by National Institute of Biomedical Imaging and BioEngineering under Grants No R01-EB002010 and No R01-EB000473.  ... 
doi:10.1016/j.neuroimage.2009.10.078 pmid:19896541 pmcid:PMC2818446 fatcat:p2iyrzulbjelffkeqk4o6pdhba

Partial Least Square Aided Beamforming Algorithm in Magnetoencephalography Source Imaging

Yegang Hu, Chunli Yin, Jicong Zhang, Yuping Wang
2018 Frontiers in Neuroscience  
Noise was then removed by reconstructing the MEG arrays based on those components. The minimum variance beamforming method was used to estimate a source model.  ...  The proposed method may provide a new imaging marker for localization of epileptogenic zones.  ...  LCMV beamforming optimizes the objective function subject to a linear constraint, and therefore is a type of vector beamforming.  ... 
doi:10.3389/fnins.2018.00616 pmid:30233299 pmcid:PMC6134212 fatcat:nycy5obq55dnnh2uulaffpsanm

Mapping the topological organisation of beta oscillations in motor cortex using MEG

Eleanor L. Barratt, Susan T. Francis, Peter G. Morris, Matthew J. Brookes
2018 NeuroImage  
In this paper we first show, in simulation, how to optimise experimental design and beamformer spatial filtering techniques to increase the spatial specificity of MEG derived functional images.  ...  A B S T R A C T The spatial topology of the human motor cortex has been well studied, particularly using functional Magnetic Resonance Imaging (fMRI) which allows spatial separation of haemodynamic responses  ...  ELB was funded by a research studentship by the University of Nottingham. We also acknowledge Medical Research Council Partnership Grant (MR/K005464/1).  ... 
doi:10.1016/j.neuroimage.2018.06.041 pmid:29960087 pmcid:PMC6150950 fatcat:jkcujzngnzfmddxbeoq4iwinwy

Closely Spaced MEG Source Localization and Functional Connectivity Analysis Using a New Prewhitening Invariance of Noise Space Algorithm

Junpeng Zhang, Yuan Cui, Lihua Deng, Ling He, Junran Zhang, Jing Zhang, Qun Zhou, Qi Liu, Zhiguo Zhang
2016 Neural Plasticity  
This paper proposed a prewhitening invariance of noise space (PW-INN) as a new magnetoencephalography (MEG) source analysis method, which is particularly suitable for localizing closely spaced and highly  ...  Therefore, the proposed PW-INN method is a promising MEG source analysis to provide a high spatial-temporal characterization of cortical activity and connectivity, which is crucial for basic and clinical  ...  LCMV beamformer, sLORETA, and INN are all based on the assumption of uncorrelated noise, which is actually not true for real MEG signals. Generally, MEG noise is correlated between MEG channels.  ... 
doi:10.1155/2016/4890497 pmid:26819768 pmcid:PMC4706973 fatcat:xxic5ecvynhylaz6zut2fqvsw4

Measuring electrophysiological connectivity by power envelope correlation: a technical review on MEG methods

George C O'Neill, Eleanor L Barratt, Benjamin A E Hunt, Prejaas K Tewarie, Matthew J Brookes
2015 Physics in Medicine and Biology  
In this paper we discuss measurement of network connectivity using magnetoencephalography (MEG), a technique capable of imaging electrophysiological brain activity with good (~5mm) spatial resolution and  ...  ABSTRACT The human brain can be divided into multiple areas, each responsible for different aspects of behaviour.  ...  Substituting for the MEG data using Equation 5, and noting the linear constraint for beamformer weights that 1 1 = 1, ̂1 = 1 1 1 + 1 2 2 = 1 + 1 2 2 .  ... 
doi:10.1088/0031-9155/60/21/r271 pmid:26447925 fatcat:igdd6wljdzamllba3mxojwcdaa

Scanning Reduction Strategy in MEG/EEG Beamformer Source Imaging

Jun Hee Hong, Sung Chan Jun
2012 Journal of Applied Mathematics  
MEG/EEG beamformer source imaging is a promising approach which can easily address spatiotemporal multi-dipole problems without a priori information on the number of sources and is robust to noise.  ...  Despite such promise, beamformer generally has weakness which is degrading localization performance for correlated sources and is requiring of dense scanning for covering all possible interesting (entire  ...  Haruta at Yokogawa Electric Corp for his assistance with MEG data acquisition.  ... 
doi:10.1155/2012/528469 fatcat:z6dca2nepjbcxheizntv2ukfzy

GLM-beamformer method demonstrates stationary field, alpha ERD and gamma ERS co-localisation with fMRI BOLD response in visual cortex

Matthew J. Brookes, Andrew M. Gibson, Stephen D. Hall, Paul L. Furlong, Gareth R. Barnes, Arjan Hillebrand, Krish D. Singh, Ian E. Holliday, Sue T. Francis, Peter G. Morris
2005 NeuroImage  
This provides a useful framework for comparison of the full range of MEG responses with fMRI BOLD results.  ...  Recently, we introduced a new dGLM-beamformerT technique for MEG analysis that enables accurate localisation of both phase-locked and non-phase-locked neuromagnetic effects, and their representation as  ...  Acknowledgments We are grateful to the Wellcome Trust for a Major Equipment Grant, and for continuing support of the MEG laboratory at Aston University and G.R.B.  ... 
doi:10.1016/j.neuroimage.2005.01.050 pmid:15862231 fatcat:5uoy3bfs4zbltcxpbva3j6dadq

Optimized beamforming for simultaneous MEG and intracranial local field potential recordings in deep brain stimulation patients

Vladimir Litvak, Alexandre Eusebio, Ashwani Jha, Robert Oostenveld, Gareth R. Barnes, William D. Penny, Ludvic Zrinzo, Marwan I. Hariz, Patricia Limousin, Karl J. Friston, Peter Brown
2010 NeuroImage  
In this work, we show that MEG beamforming is capable of suppressing these artefacts and quantify the optimal regularization required.  ...  Our findings demonstrate that physiologically meaningful information can be extracted from heavily contaminated MEG signals and pave the way for further analysis of combined MEG-LFP recordings in DBS patients  ...  Acknowledgments We would like to thank David Bradbury, Janice Glensman, Zoe Chen and James Kilner for their assistance with conducting the experiments and Jan-Mathijs Schoffelen and Stefan Debener for  ... 
doi:10.1016/j.neuroimage.2009.12.115 pmid:20056156 pmcid:PMC3221048 fatcat:zxtaztyvvjfhhnqwyb6j3nkrq4

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

M.J. Brookes, M.W. Woolrich, G.R. Barnes
2012 NeuroImage  
The multivariate method offers a powerful means to capture the high dimensionality and rich information content of MEG signals in a single imaging statistic.  ...  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.  ...  The WTCN at UCL is supported by a strategic award from the Wellcome Trust. We also gratefully acknowledge the Medical Research Council and The University of Nottingham for financial support.  ... 
doi:10.1016/j.neuroimage.2012.03.048 pmid:22484306 pmcid:PMC3459100 fatcat:ydqurrdgwvcidpyeqioios2di4

BrainWave: A Matlab Toolbox for Beamformer Source Analysis of MEG Data

Cecilia Jobst, Paul Ferrari, Silvia Isabella, Douglas Cheyne
2018 Frontiers in Neuroscience  
It provides a graphical user interface for performing minimumvariance beamforming analysis with rapid and interactive visualization of evoked and induced brain activity.  ...  This includes data selection and preprocessing, magnetic resonance image co-registration and normalization procedures, and the generation of volumetric (whole-brain) or cortical surface based source images  ...  This will generate a 3D rendered image (using 3D linear interpolation) of the group beamformer source volume of the current latency onto the Freesurfer extracted brain surface of the Colin-27 (CH2.nii)  ... 
doi:10.3389/fnins.2018.00587 pmid:30186107 pmcid:PMC6113377 fatcat:3v4p6oa55vberb7adt7epvlusi

A new approach to neuroimaging with magnetoencephalography

Arjan Hillebrand, Krish D. Singh, Ian E. Holliday, Paul L. Furlong, Gareth R. Barnes
2005 Human Brain Mapping  
We discuss the application of beamforming techniques to the field of magnetoencephalography (MEG).  ...  We review several experiments that have used beamformers, with special emphasis on those in which the results have been compared to those observed in functional magnetic resonance imaging (fMRI) and on  ...  Increasing the sensitivity to signals coming from a location of interest, for example a region in the brain, can obviously be exploited for reconstruction of the neuronal sources generating EEG and MEG  ... 
doi:10.1002/hbm.20102 pmid:15846771 fatcat:xej6cd5manc6va2tkujqi4s64y

Applied Mathematics in Biomedical Sciences and Engineering

Chang-Hwan Im, Kiwoon Kwon, Venky Krishnan, Pedro Serranho
2012 Journal of Applied Mathematics  
In the paper, "Scanning reduction strategy in MEG/EEG beamformer source imaging" by J. Hong and S.  ...  The proposed linear method proved to be robust to noise as compared with standard approaches. In the paper "Modeling of brain shift phenomenon for different craniotomies and solid models" by A.  ...  We hope you will find this special issue helpful for your future study.  ... 
doi:10.1155/2012/187252 fatcat:45bbmnlo4nc4nmfokvij4dtoke

MEG Analysis with Spatial Filtered Reconstruction

S. OKAWA
2006 IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences  
Magnetoencephalography (MEG) is a method to measure a magnetic field generated by electrical neural activity in a brain, and it plays increasingly important role in clinical diagnoses and neurophysiological  ...  We also investigate the differences among SFR, the LCMV (linearly constrained minimum variance) beamformer and the SAM (synthetic aperture magnetometry), the representatives of spatial filters in MEG analyses  ...  We construct a multiple linear regression model with the current dipoles estimated by the proposed spatial filter.  ... 
doi:10.1093/ietfec/e89-a.5.1428 fatcat:u3wngvj3szd23mchbgwihu6qru

Source Activity Correlation Effects on LCMV Beamformers in a Realistic Measurement Environment

Paolo Belardinelli, Erick Ortiz, Christoph Braun
2012 Computational and Mathematical Methods in Medicine  
A linear constrained minimum variance (LCMV) beamformer is applied to the oscillating signals generated by the current dipoles within the phantom.  ...  Beamformers are well-established source-localization tools for MEG/EEG signals, being employed in source connectivity studies both in time and frequency domain.  ...  Acknowledgment The present work is supported by an award from the Center for Integrated Neuroscience (CIN) of Tübingen (Germany) (Pool Project no. 2010-17).  ... 
doi:10.1155/2012/190513 pmid:22611439 pmcid:PMC3351244 fatcat:oobpeiogxffh5ps7fujgauxmkm

Comparing EEG/MEG neuroimaging methods based on localization error, false positive activity, and false positive connectivity [article]

Roberto D Pascual-Marqui, Pascal L Faber, Toshihiko Kinoshita, Kieko Kochi, Patricia Milz, Keiichiro Nishida, Masafumi Yoshimura
2018 biorxiv/medrxiv   pre-print
The aim here is to provide a guideline for choosing the best (i.e. least bad) imaging method.  ...  These methods are linear, except for the LCMVBs that make use of the quadratic EEG covariances.  ...  The toy data: head model, voxels, electrodes A unit radius three-shell spherical head model was used, as described in (Ary et al 1981 was computed for this simple head model using the approximations  ... 
doi:10.1101/269753 fatcat:yiezxnv6ynejpfozew5fvvgrpe
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