Abstract：
:We propose a method that incorporates the time-frequency characteristics of neural sources into magnetoencephalographic (MEG) source estimation. The method is based on the multiple-signal-classification (MUSIC) algorithm and it calculates a time--frequency matrix in which diagonal and off-diagonal terms are the auto and crosstime--frequency distributions of multichannel MEG recordings, respectively. The method averages this time-frequency matrix over the time--frequency region of interest. The locations of neural sources are then estimated by checking the orthogonality between the noise subspace of this averaged matrix and the sensor lead field. Accordingly, the method allows us to estimate the locations of neural sources from each time--frequency component. A computer simulation was performed to test the validity of the proposed method, and the results demonstrate its effectiveness.
journal_name
IEEE Trans Med Imagingjournal_title
IEEE transactions on medical imagingauthors
Sekihara K,Nagarajan S,Poeppel D,Miyashita Ydoi
10.1109/42.750262subject
Has Abstractpub_date
1999-01-01 00:00:00pages
92-7issue
1eissn
0278-0062issn
1558-254Xjournal_volume
18pub_type
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