[Eeglablist] Splitting the data for ICA

[Jan Karsten]

Dear list members,

I am currently working on a preprocessing procedure for EEG data with the aim to analyse the movement-cortical potential. My main purpose for the preprocessing  is to reduce the amount of artefact contamination (especially eye blinks) using ICA. Since we are interested in the MRCP, I am following the suggestion to split the data before the ICA to apply a high-pass filter (1 Hz) to the data I am running the ICA algorithm on and attach the solution to the second dataset I am using for the analysis.


Now my question is:

Because the ICA is trained with data that does not contain low frequency content (due to the high pass filter at 1 Hz), I am concerned, that this low frequency content will be randomly distributed across the ICA components when applied to the second dataset (in my case with a band pass filter of 0.05 - 5 Hz). Hence, in the worst case, an ICA component that contains mostly eye blinks will also contains more valuable information than usual in the low frequency domain. Do you think that the low-frequency data within the ICA sources is problematic or can it be ignored? What are your suggestions on how to best deal with such data?



I attached a picture to the mail for clarification (I hope it can be seen through the list), showing an ICA component containing eye blinks acquired from the split datasets.

Thanks in advance for your help and I am looking forward for your replies,

Jan