[FieldTrip] regressconfound

[Stolk, A. (Arjen)]

Hey Raghavan, You're welcome. A quick solution to set you in the right direction would be to point you to the respective documentation: http://www.sciencedirect.com/science/article/pii/S1053811912011597 I believe some, maybe most, of your points are addressed by that paper (saving some copy&pasting in here). best, Arjen ----- Oorspronkelijk bericht -----
> Van: "Raghavan Gopalakrishnan" <gopalar.ccf at gmail.com>
> Aan: "fieldtrip" <fieldtrip at science.ru.nl>
> Verzonden: Maandag 7 april 2014 18:59:33
> Onderwerp: [FieldTrip] regressconfound
> 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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-- Donders Institute for Brain, Cognition and Behaviour Centre for Cognitive Neuroimaging Radboud University Nijmegen Email: a.stolk at donders.ru.nl Phone: +31(0)243 68294 Web: www.arjenstolk.nl 
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