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Estimating neural sources from each time-frequency component of magnetoencephalographic data
2000
IEEE Transactions on Biomedical Engineering
We have developed a method that incorporates the time-frequency characteristics of neural sources into magnetoencephalographic (MEG) source estimation. This method, referred to as the time-frequency multiple-signal-classification algorithm, allows the locations of neural sources to be estimated from any time-frequency region of interest. In this paper, we formulate the method based on the most general form of the quadratic time-frequency representations. We then apply it to two kinds of
doi:10.1109/10.841336
pmid:10851808
fatcat:3kfolbxmhzbm7bhx6rvf3tkzpe