Decomposition of Magnetoencephalographic Data Into Components Corresponding to Deep and Superficial Sources

@article{zkurt2008DecompositionOM,
  title={Decomposition of Magnetoencephalographic Data Into Components Corresponding to Deep and Superficial Sources},
  author={Tolga Esat {\"O}zkurt and Mingui Sun and Robert J. Sclabassi},
  journal={IEEE Transactions on Biomedical Engineering},
  year={2008},
  volume={55},
  pages={1716-1727}
}
We extend the signal space separation (SSS) method to decompose multichannel magnetoencephalographic (MEG) data into regions of interest inside the head. It has been shown that the SSS method can transform MEG data into a signal component generated by neurobiological sources and a noise component generated by external sources outside the head. In this paper, we show that the signal component obtained by the SSS method can be further decomposed by a simple operation into signals originating from… CONTINUE READING
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