A graphical model for estimating stimulus-evoked brain responses from magnetoencephalography data with large background brain activity

@article{Nagarajan2006AGM,
  title={A graphical model for estimating stimulus-evoked brain responses from magnetoencephalography data with large background brain activity},
  author={Srikantan S. Nagarajan and Hagai Attias and Kenneth E. Hild and Kensuke Sekihara},
  journal={NeuroImage},
  year={2006},
  volume={30},
  pages={400-416}
}
This paper formulates a novel probabilistic graphical model for noisy stimulus-evoked MEG and EEG sensor data obtained in the presence of large background brain activity. The model describes the observed data in terms of unobserved evoked and background factors with additive sensor noise. We present an expectation maximization (EM) algorithm that estimates the model parameters from data. Using the model, the algorithm cleans the stimulus-evoked data by removing interference from background… CONTINUE READING

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