[Eeglablist] About ERSP averaging and normalisation
marco.buiatti at univ-paris5.fr
Tue Oct 19 08:01:32 PDT 2004
Dear eeglab people,
I have some questions about how to normalise and average ERSPs across
electrodes and subjects. I saw that eeglab performs the following steps:
a) for every electrode, subject and frequency, normalisation is
performed by dividing the ERSP by the mean ERSP along the baseline.
Then, 10log10 is taken.
b) Bootstrap analysis sets a threshold for statistical significance.
c) Average/RMS is taken over all subjects and electrodes (optionally
with another threshold on the minumum number of significant
Here the questions:
1) Why not normalising by subtracting the mean and dividing by the std
of the baseline? Intuitively, I guess this has something to do with the
fact that ERSP>0, and your normalisation preserves this, but I cannot
find a deeper explanation.
2) The non-linearity of the log causes averages over electrodes/subjects
to be biased: don't you think this can be misleading?
3) What is the advantage to use RMS instead of averaging? On one hand
RMS enhances differences (w.r.t. baseline), but on the other it could
enhance noise. Again, is there any deeper explanation?
4) This is more a prayer than a question, since the question has been
asked several times: a tool to quantify the statistical difference
between two conditions would be highly appreciated!
Little thing to correct: when using tftopo, 'mode','ave', the message
'RMS averaging' is printed, while it seems to me that normal averaging
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