[Eeglablist] PSD of resting state data

[Katherine Eskine]

Dear all,

I have been working through a data set and would deeply appreciate some
advice. I have 6 minutes of resting state data before and after exposure,
all recorded in the same session. I would like to see if there are
significant differences in frequency bands before as compared to after the
exposure.

The EEG during the exposure was removed and then the continuous data has
been post-processed and submitted to ICA analysis, where heartbeat, eye
blinks, and other noisy components were removed. Then the data was split
into the 6 minutes before and after.

How can I best determine if there are differences between the distributions
of frequencies bans (alpha, beta, etc.)?
* bandpass filtering & plotting per band
* average absolute power per band, or
* time-frequency transform using short-term Fourier transforms or wavelets
* should I epoch the data into 3-second intervals and proceed from there?

My original thinking was to find the average alpha, beta, theta, delta and
gamma for the pre and the post then submit them to a repeated measures
analysis. However, I am wondering if an analysis using the components might
provide more information? Can I identify significant differences in ICA's
between the pre and the postconditions and then look at the dipoles for the
brain source?

One follow-up question, will I run into problems because the pre and post
conditions have the same ICA components? I assume that looking for
different power of each component will get at any before and after
differences, but does the structure violate vector parameters?

Thanks so much for your help. I have been following the discussion from
Mohith, but I think my continuous data might be a slightly different case.

Best,

Kate


Katherine E. Eskine
Assistant Professor of Psychology
Mars SC 1136 / t. 508-286-3636
Wheaton College
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