Application of an MEG eigenspace beamformer to reconstructing spatio-temporal activities of neural sources.

@article{Sekihara2002ApplicationOA,
  title={Application of an MEG eigenspace beamformer to reconstructing spatio-temporal activities of neural sources.},
  author={Kensuke Sekihara and Srikantan S. Nagarajan and David Poeppel and Alec Marantz and Yasushi Miyashita},
  journal={Human brain mapping},
  year={2002},
  volume={15 4},
  pages={199-215}
}
We have applied the eigenspace-based beamformer to reconstruct spatio-temporal activities of neural sources from MEG data. The weight vector of the eigenspace-based beamformer is obtained by projecting the weight vector of the minimum-variance beamformer onto the signal subspace of a measurement covariance matrix. This projection removes the residual noise-subspace component that considerably degrades the signal-to-noise ratio (SNR) of the beamformer output when errors in estimating the sensor… CONTINUE READING

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