Name
Abstract | ||
|---|---|---|
Evidence suggests that magnetoencephalogram (MEG) data have characteristics with non-Gaussian distribution, however, standard methods for source localisation assume Gaussian behaviour. We present a new general method for non-Gaussian source estimation of stationary signals for localising brain activity in the MEG data. By providing a Bayesian formulation for linearly constraint minimum variance (LCMV) beamformer, we extend this approach and show that how the source probability density function (pdf), which is not necessarily Gaussian, can be estimated. The proposed non-Gaussian beamformer is shown to give better spatial estimates than the LCMV beamformer, in both simulations incorporating non-Gaussian signal and in real MEG measurements. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/ICASSP.2013.6637850 | Acoustics, Speech and Signal Processing |
Keywords | Field | DocType |
Bayes methods,Gaussian distribution,array signal processing,estimation theory,magnetoencephalography,medical signal processing,signal reconstruction,Bayesian formulation,Gaussian behaviour,MEG data,MEG source reconstruction,brain activity localisation,general nonGaussian source estimation method,linearly constraint minimum variance beamformer,magnetoencephalogram data characteristics,nonGaussian LCMV beamformer,nonGaussian distribution,nonGaussian signal,real MEG measurement,source probability density function estimation,spatial estimation,standard source localisation method,stationary signal,LCMV-beamformer,Magnetoencephalography,non-Gaussian,source reconstruction | Minimum-variance unbiased estimator,Source reconstruction,Pattern recognition,Computer science,Gaussian,Artificial intelligence,Estimation theory,Gaussian function,Probability density function,Magnetoencephalography,Signal reconstruction | Conference |
ISSN | Citations | PageRank |
1520-6149 | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hamid Reza Mohseni | 1 | 75 | 4.65 |
| Morten L. Kringelbach | 2 | 185 | 21.07 |
| Mark W Woolrich | 3 | 1723 | 94.51 |
| Tipu Z. Aziz | 4 | 168 | 13.34 |
| Penny Probert Smith | 5 | 15 | 3.59 |