[Eeglablist] EEGlab function to trim datasets

[Brent A. Field]

I running a computationally intensive analysis on a high-end cluster, but have been confounded because I periodically hit a Matlab Out of Memory error. The input data has a high sampling rate, has a lot of channels, and is collected over a long period. These can be simplified at later stages, but the first step requires inputting roughly a 4 GB continuous data file, with memory requirement far beyond that to actually run the analysis. I won't go into it, but there is a reason why the data needs processed as one block.

There are other tricks I can try, but one obviously one is just to slim down the input. And fortunately there is some fat I can trim out of input datasets. But it seems that EEGlab deals with this by offering the option to mark data in continuous files as irrelevant, not by making a new copy of the dataset which just contains the data of interest. Is this correct?

Obviously I can write my own function to remove irrelevant sections from the dataset, but I just wanted to check that there wasn't already some function out there first that chopped data out of EEG datasets.

Thanks for any thoughts on this matter!

Brent Field


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