Estimating neural sources from each time-frequency component of magnetoencephalographic data

We have developed a method that incorporates the time-frequency characteristics of neural sources into magnetoencephalographic (MEG) source estimation. This method calculates a time-frequency matrix in which diagonal and off-diagonal terms are the auto- and cross-time-frequency distributions of multi-channel MEG recordings, respectively. The method averages this 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. The method therefore allows neural sources to be estimated from any time-frequency component of measured data. We applied the method to estimating sources for gamma-band (frequency range between 30 and 100 Hz) auditory activity, and the results demonstrating the method´s effectiveness were obtained