Title :
Maximum likelihood estimation of low rank signals for multiepoch MEG/EEG data
Author :
Baryshnikov, Boris V. ; Van Veen, Barry D. ; Wakai, Ronald Z.
Author_Institution :
Dept. of Med. Phys., Wisconsin Univ., Madison, WI, USA
fDate :
28 Sept.-1 Oct. 2003
Abstract :
An algorithm for reducing spatially colored noise in evoked response magneto- and electro-encephalography data is presented. The algorithm models the repeatable component of the data, or signal of interest, as the mean, while the noise is modeled as Gaussian with unknown covariance structure. The mean matrix has a low rank structure due to the temporal and spatial structure of the data. Maximum likelihood estimates of the components of the low-rank signal structure are derived in order to estimate the signal component. The effectiveness of this approach is demonstrated using simulated and real MEG data.
Keywords :
Gaussian noise; electroencephalography; magnetoencephalography; maximum likelihood estimation; medical signal processing; EEG data; Gaussian noise; MEG data; covariance structure; electro-encephalography data; magneto-encephalography data; maximum likelihood estimation; mean matrix; spatially colored noise; Brain modeling; Colored noise; Covariance matrix; Electroencephalography; Gaussian noise; Maximum likelihood estimation; Noise measurement; Physics; Signal to noise ratio; Statistics;
Conference_Titel :
Statistical Signal Processing, 2003 IEEE Workshop on
Print_ISBN :
0-7803-7997-7
DOI :
10.1109/SSP.2003.1289398
