[FieldTrip] regressconfound

[Raghavan Gopalakrishnan]

Arjen,

Thanks for all your previous help on using regressconfound.
It would be great if you can shed light on some questions I asked earlier
(See below).
Also, when applying regressconfound to time-frequency (TF) data,
regressconfound removes variance from TF from individual trials. So,
utimately regressconfound helps to improve the induced TF responses rather
than evoked responses. (By induced, I mean calculating TF on trial by trial
basis and then computing average, But evoked I mean calculating TF on
averaged data)
If one is interested in only evoked, then regressconfound would not be of
much help. Is that correct?

Thanks,
Raghavan






Date: Wed, 26 Feb 2014 11:38:23 -0500
From: Raghavan Gopalakrishnan <gopalar.ccf at gmail.com>
To: fieldtrip at science.ru.nl
Subject: [FieldTrip] regressconfound and statistics
Message-ID: <A36DB35E-1C8A-4C8A-A0F3-083B8E1131C1 at gmail.com>
Content-Type: text/plain; charset=windows-1252

Arjen,

I agree with your steps and your assumptions about my data, though I am
only interested in evoked activity. I am indeed doing the steps 1 and 2 in
the correct order. I just kept the 4 blocks and confounds associated with
them separate from each other (for book keeping purposes), but I used the
mean head position of all 4 blocks to demean the translations and rotations
in each block. Technically, I guess this is the same as appending the
blocks prior to running regress confound.

When I said, "However, the problem is, whatever significance I found
earlier (i.e. by comparing means rather than t-statistic) doesn?t test
significant now.? I was comparing the means of the data that has been run
through regress confound. When I plot (sum square of all gradiometers in
each subject in each condition)  before and after regress confound, I see
some differences. Should I not see any differences at all?

 But there is one catch. What do I do if I am comparing a condition across
different time points, rather than 2 conditions in one time point? MEG
collected at two different time points will have different average head
positions. In that case, should I use one average head position (computed
from time point - 1) and use that to demean the translations and rotations
in rest of the time points?


Thanks for your support.
Raghavan
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