DocumentCode :
2501676
Title :
Investigation of EEG and MEG source imaging accuracy in reconstructing extended cortical sources
Author :
Ding, Lei ; Yuan, Han
Author_Institution :
Sch. of Electr. & Comput. Eng., Univ. of Oklahoma, Norman, OK, USA
fYear :
2011
fDate :
Aug. 30 2011-Sept. 3 2011
Firstpage :
7013
Lastpage :
7016
Abstract :
Electroencephalography (EEG) and magneto-encephalography (MEG) are both currently used to reconstruct brain activity. The performance of inverse source reconstructions is dependent on the modality of signals in use as well as inverse techniques. Here we used a recently proposed sparse source imaging technique, i.e., the variation-based sparse cortical current density (VB-SCCD) algorithm to compare the use of EEG or MEG data in reconstructing extended cortical sources. We conducted Monte Carlo simulations as comparison to two other widely used source imaging techniques. The VB-SCCD technique was further evaluated in experimental EEG and MEG data. Our present results indicate that EEG and MEG have similar reconstruction performance as indicated by a metric, the area under the receiver operating characteristic curve (AUC). Furthermore, EEG and MEG have different advantages and limitations in revealing different aspects of features of extended cortical sources, which are complimentary to each other. A simultaneous EEG and MEG analysis framework is thus promising to produce much improved source reconstructions.
Keywords :
Monte Carlo methods; electroencephalography; feature extraction; inverse problems; magnetoencephalography; medical signal processing; sensitivity analysis; signal reconstruction; EEG; MEG; Monte Carlo simulations; brain activity; electroencephalography; extended cortical sources; feature extraction; inverse source reconstructions; magneto-encephalography; receiver operating characteristic curve; source imaging accuracy; sparse source imaging technique; variation-based sparse cortical current density; Accuracy; Brain modeling; Charge coupled devices; Electroencephalography; Image reconstruction; Magnetic resonance imaging; Algorithms; Area Under Curve; Brain; Brain Mapping; Cerebral Cortex; Computer Simulation; Electroencephalography; Humans; Image Processing, Computer-Assisted; Magnetoencephalography; Models, Statistical; Monte Carlo Method; Normal Distribution; ROC Curve; Reproducibility of Results;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society, EMBC, 2011 Annual International Conference of the IEEE
Conference_Location :
Boston, MA
ISSN :
1557-170X
Print_ISBN :
978-1-4244-4121-1
Electronic_ISBN :
1557-170X
Type :
conf
DOI :
10.1109/IEMBS.2011.6091773
Filename :
6091773
Link To Document :
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