Probabilistic algorithms for MEG/EEG source reconstruction using temporal basis functions learned from data

@article{Zumer2008ProbabilisticAF,
  title={Probabilistic algorithms for MEG/EEG source reconstruction using temporal basis functions learned from data},
  author={Johanna M. Zumer and Hagai Attias and Kensuke Sekihara and Srikantan S. Nagarajan},
  journal={NeuroImage},
  year={2008},
  volume={41 3},
  pages={924-40}
}
We present two related probabilistic methods for neural source reconstruction from MEG/EEG data that reduce effects of interference, noise, and correlated sources. Both methods localize source activity using a linear mixture of temporal basis functions (TBFs) learned from the data. In contrast to existing methods that use predetermined TBFs, we compute TBFs from data using a graphical factor analysis based model [Nagarajan, S.S., Attias, H.T., Hild, K.E., Sekihara, K., 2007a. A probabilistic… CONTINUE READING
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