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Correct continuous EEG data using regression in Matlab

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djh0808

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I am a lowly undergraduate researcher trying to navigate Matlab for the first time. I am stuck on correcting for ocular artifacts in EEG data using regression. My data is a continuous 8 min long (no events) with 128 channels. All of the toolboxes I've found are geared for rejecting trials in an ERP context. I am analyzing continuous resting EEG data. Any advice or suggestions would be helpful at this point.
 


How ingenious. I never thought to SEARCH for my answers. All kidding aside, I too am under the age of 45 and therefore proficient in Google searching. Unfortunately, most of the scholarly articles I've read have only theoretical explanations about the process. I was hoping for a resource more specific to Matlab programming. I am reading a book entitled "Matlab for Neuroscientists," but the going is slow. I am several chapters in, and the book is nowhere near explaining specifics about waveform analysis.

To be clear: I understand what needs to be done to my data, but I don't yet understand how to preform the actions in Matlab. There are many toolboxes that have been developed to help with this, but I haven't found one that supports continuous data (without events) and performs regression to correct the data. Most of them are set up to remove bad data rather than correct it.
 

It sounds like maybe you need to just "bite the bullet" and immerse yourself in doing some Matlab programming.
Have you done much programming, of any kind? If so, especially if it was plain C, then it shouldn't be too bad.

Maybe it would be much easier to find some Matlab code etc that is geared toward using regression on continuous data, but has nothing to do with EEG, and then learn and/or borrow most of the Matlab-specific methods from there, and then figure out how to modify it for your specific application (or maybe how to go back and create add-ons for some of the existing toolkits).

P.S. I am 56.

Cheers,

Tom
 

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