Dynamic Neuroscience by Zhe Chen & Sridevi V. Sarma

Author:Zhe Chen & Sridevi V. Sarma
Language: eng
Format: epub
Publisher: Springer International Publishing, Cham

2.Detect bad electrodes from EEGtemp based on the maximum correlation coefficient and add them to the bad electrode list;

3.EEGtemp = EEG −mean(EEG), where mean(EEG) is the mean of the EEG with all the bad electrodes interpolated;

4.Repeat steps 2–3 until the bad electrode list does not change.

5.Reject and interpolate the bad electrodes in EEG;

6.EEG = EEG −mean(EEG).

The maximum correlation criterion can only identify single noisy electrodes not resembling any other electrodes. However, in some situations a local cluster of electrodes may become artifactual together in which case electrode correlations will be high within each cluster. To address this issue, the random consensus (RANSAC) method is employed to detect noisy clusters of electrodes following the maximum correlation criterion (Bigdely-Shamlo et al. 2015). More specifically, RANSAC uses a random subset (25% by default) of electrodes to predict the EEG of each electrode (excluded from the subset) in each epoch. The prediction is repeated 50 times. The correlation coefficients of the predicted EEGs and the actual EEG of each electrode are then calculated. An electrode is bad if the 50 percentile of the correlation coefficients is less than a threshold (0.75 by default) on more than a certain fraction of epochs (0.4 by default).

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