Literature DB >> 14683731

The use of anatomical constraints with MEG beamformers.

Arjan Hillebrand1, Gareth R Barnes.   

Abstract

Synthetic Aperture Magnetometry (SAM) is a beamformer approach for the localisation of neuronal activity from EEG/MEG data. SAM estimates the optimum orientation of each source in a predefined source space by a nonlinear search for the orientation that maximises the beamformer output. However, MEG is most sensitive to cortical sources and these sources are generally oriented perpendicular to the surface. The reconstructed neuronal activity can therefore reasonably be constrained to the cortical surface, orientated perpendicular to it, therefore removing the search for the optimum orientation for the computation of the beamformer weights. This paper sets out to compare the performance of a constrained and unconstrained beamformer (SAM), with respect to the localisation accuracy of the source reconstructions and the spatial resolution. Fifty sources were randomly placed on a cortical surface estimated from an MRI, and we simulated data over a range of different signal-to-noise ratios (SNRs) for each source. These datasets were analysed using both an unconstrained beamformer (SAM) and a constrained beamformer (with the sources orientated perpendicular to the cortical surface). The influence of errors in the estimation of the surface location and surface normals on the performance of the constrained beamformer, representing MEG/MRI coregistration and segmentation errors, were also examined. The spatial resolution of the beamformer improves, typically by a factor of four by applying anatomical constraints, and the localisation accuracy improves marginally. However, the advantage in spatial resolution disappears when errors are introduced into the orientation and location constraints, and, moreover, the localisation accuracy of the inaccurately constrained beamformer degrades rapidly. We conclude that the use of anatomical constraints is only advantageous if the MEG/MRI coregistration error is smaller than 2 mm and the error in the estimation of the cortical surface orientation is smaller than 10 degrees.

Entities:  

Mesh:

Year:  2003        PMID: 14683731     DOI: 10.1016/j.neuroimage.2003.07.031

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  43 in total

1.  Realistic spatial sampling for MEG beamformer images.

Authors:  Gareth R Barnes; Arjan Hillebrand; Ian P Fawcett; Krish D Singh
Journal:  Hum Brain Mapp       Date:  2004-10       Impact factor: 5.038

2.  Sensitivity of beamformer source analysis to deficiencies in forward modeling.

Authors:  Olaf Steinsträter; Stephanie Sillekens; Markus Junghoefer; Martin Burger; Carsten H Wolters
Journal:  Hum Brain Mapp       Date:  2010-05-24       Impact factor: 5.038

3.  Temporal microstructure of cortical networks (TMCN) underlying task-related differences.

Authors:  Arpan Banerjee; Ajay S Pillai; Justin R Sperling; Jason F Smith; Barry Horwitz
Journal:  Neuroimage       Date:  2012-06-19       Impact factor: 6.556

Review 4.  A new approach to neuroimaging with magnetoencephalography.

Authors:  Arjan Hillebrand; Krish D Singh; Ian E Holliday; Paul L Furlong; Gareth R Barnes
Journal:  Hum Brain Mapp       Date:  2005-06       Impact factor: 5.038

5.  Spatiotemporal mapping of cortical activity accompanying voluntary movements using an event-related beamforming approach.

Authors:  Douglas Cheyne; Leyla Bakhtazad; William Gaetz
Journal:  Hum Brain Mapp       Date:  2006-03       Impact factor: 5.038

6.  Electromagnetic source imaging: Backus-Gilbert resolution spread function-constrained and functional MRI-guided spatial filtering.

Authors:  Xiaohong Wan; Atsushi Sekiguchi; Satoru Yokoyama; Jorge Riera; Ryuta Kawashima
Journal:  Hum Brain Mapp       Date:  2008-06       Impact factor: 5.038

7.  MEG source imaging method using fast L1 minimum-norm and its applications to signals with brain noise and human resting-state source amplitude images.

Authors:  Ming-Xiong Huang; Charles W Huang; Ashley Robb; AnneMarie Angeles; Sharon L Nichols; Dewleen G Baker; Tao Song; Deborah L Harrington; Rebecca J Theilmann; Ramesh Srinivasan; David Heister; Mithun Diwakar; Jose M Canive; J Christopher Edgar; Yu-Han Chen; Zhengwei Ji; Max Shen; Fady El-Gabalawy; Michael Levy; Robert McLay; Jennifer Webb-Murphy; Thomas T Liu; Angela Drake; Roland R Lee
Journal:  Neuroimage       Date:  2013-09-19       Impact factor: 6.556

8.  MEG beamforming using Bayesian PCA for adaptive data covariance matrix regularization.

Authors:  Mark Woolrich; Laurence Hunt; Adrian Groves; Gareth Barnes
Journal:  Neuroimage       Date:  2011-05-08       Impact factor: 6.556

9.  Lamina-specific cortical dynamics in human visual and sensorimotor cortices.

Authors:  Gareth R Barnes; Sven Bestmann; James J Bonaiuto; Sofie S Meyer; Simon Little; Holly Rossiter; Martina F Callaghan; Frederic Dick
Journal:  Elife       Date:  2018-10-22       Impact factor: 8.140

10.  MNE software for processing MEG and EEG data.

Authors:  Alexandre Gramfort; Martin Luessi; Eric Larson; Denis A Engemann; Daniel Strohmeier; Christian Brodbeck; Lauri Parkkonen; Matti S Hämäläinen
Journal:  Neuroimage       Date:  2013-10-24       Impact factor: 6.556

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.