[Eeglablist] Query regarding ICA and data length

[Reh, Rebecca]

Hello,

I have several questions regarding best practices for ICA artifact detection on high density EEG data. I have 256 channels of resting state data, collected for 10 minutes per subject, downsampled to 250 Hz. According to the best practices outlined in Makoto’s preprocessing pipeline, the following calculation is recommended to determine the amount of data necessary for a good decomposition of the data using ICA: number of electode^2 * k (with k at 20 to 30 but potentially higher for high density recording). Using this formula, I’ve calculated I would need over an hour of data from each subject in order to run the full ICA (256 ICs). Reading through the EEGlab documentation, it looks like I can either run a PCA to reduce the dimensionality of the data before running the ICA, or I can exclude some of the channels from the analysis. I’m curious what best practices are in this case, and also how the field generally handles having less data than would be ideal for ICA (given that I don’t think most people are collecting over an hour of resting state data).

Thank you in advance for any guidance/advice!

Rebecca K Reh, PhD
Department of Psychology
2136 West Mall
The University of British Columbia
Vancouver, BC Canada V6T 1Z4

UBC Point Grey campus sits on the traditional, ancestral, and unceded territory of the Musqueam First Nation