Title :
A comparative study of localization approaches to EEG source imaging
Author :
Yildiz, Gokcen ; Duru, A. Deniz ; Ademoglu, Ahmet
Author_Institution :
Katholieke Univ. Leuven, Leuven
Abstract :
The EEG inverse problem of reconstructing the neural electrical current that produced a given measurement is ill-posed and many different source configurations can yield the same scalp potentials. In this study, we compared localizing capabilities or three EEG inverse algorithms: MUSIC, LORETA and Bayesian MCMC method. Simulations on a realistic head model show that comparing to MUSIC and LORETA, the computational power of MCMC methods offers a flexible and robust tool for EEG source imaging.
Keywords :
Bayes methods; Markov processes; Monte Carlo methods; bioelectric potentials; electroencephalography; inverse problems; medical signal processing; Bayesian MCMC method; EEG source imaging; LORETA; MUSIC; Markov chain Monte Carlo methods; head model; inverse problem; neural electrical current; scalp potentials; signal reconstruction; Bayesian methods; Brain modeling; Computational modeling; Current measurement; Electric variables measurement; Electroencephalography; Image reconstruction; Inverse problems; Multiple signal classification; Scalp; EEG inverse problem; LORETA; MCMC; MUSIC; Realistic head model;
Conference_Titel :
Life Science Systems and Applications Workshop, 2007. LISA 2007. IEEE/NIH
Conference_Location :
Bethesda, MD
Print_ISBN :
978-1-4244-1813-8
Electronic_ISBN :
978-1-4244-1813-8
DOI :
10.1109/LSSA.2007.4400908
