Sparse current source estimation for MEG using loose orientation constraints

被引:7
作者
Chang, Wei-Tang [1 ]
Ahlfors, Seppo P. [2 ,3 ]
Lin, Fa-Hsuan [1 ,2 ,4 ]
机构
[1] Natl Taiwan Univ, Inst Biomed Engn, Taipei 10764, Taiwan
[2] Massachusetts Gen Hosp, Dept Radiol, Athinoula A Martinos Ctr Biomed Imaging, Charlestown, MA USA
[3] MIT, Harvard Mit Div Hlth Sci & Technol, Cambridge, MA 02139 USA
[4] Aalto Univ, Sch Sci, Dept Biomed Engn & Computat Sci, Espoo, Finland
基金
美国国家卫生研究院; 芬兰科学院;
关键词
inverse problem; l(1)-norm; convex optimization; MEG; EEG; orientation constraint; SURFACE-BASED ANALYSIS; CORTICAL ACTIVITY; HUMAN BRAIN; EEG; MAGNETOENCEPHALOGRAPHY; RECONSTRUCTION; LOCALIZATION;
D O I
10.1002/hbm.22057
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Spatially focal source estimates for magnetoencephalography (MEG) and electroencephalography (EEG) data can be obtained by imposing a minimum (1)-norm constraint on the distribution of the source currents. Anatomical information about the expected locations and orientations of the sources can be included in the source models. In particular, the sources can be assumed to be oriented perpendicular to the cortical surface. We introduce a minimum (1)-norm estimation source modeling approach with loose orientation constraints ((LOC)-L-1), which integrates the estimation of the orientation, location, and strength of the source currents into a cost function to jointly model the residual error and the (1)-norm of the source estimates. Evaluation with simulated MEG data indicated that the (LOC)-L-1 method can provide low spatial dispersion, high localization accuracy, and high source detection rates. Application to somatosensory and auditory MEG data resulted in physiologically reasonable source distributions. The proposed (LOC)-L-1 method appears useful for incorporating anatomical information about the source orientations into sparse source estimation of MEG data. Hum Brain Mapp 34:2190-2201, 2013. (c) 2011 Wiley Periodicals, Inc.
引用
收藏
页码:2190 / 2201
页数:12
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