Hi Daniel,
to extend what Cyril has written: you would need [at least] one regressor
per image volume you want to 'model out', because a single block regressor
would not
be sufficient as this would assume motion affecting all volumes in the same
way. Afraim
Salek Haddadi once introduced me to an approach ("scan nulling") where he
modelled - per 'bad volume' - three regressors including the preceeding and
subsequent scan (I think).
The advantage over 'erasing' the scans is beyond saving you to recalculate
your onsets, as it also makes sure the HiPass filtering remains accurate
etc. I think there was a previous discussion related to this on the list.
Best wishes,
Helmut
----- Original Message -----
From: "cyril pernet" <[log in to unmask]>
Sent: Sunday, October 08, 2006 11:08 AM
Subject: Re: Motion during task
> Hi Daniel
>
>>Hi all,
>> I have a question about accounting for motion in the scanner. We scan
>>many children with ADHD, and they tend to move around, and occasionally
>>there is a period of about 10 seconds of fidgeting in the middle of a run.
>>In the past, we have removed these volumes and adjusted the timing files,
>>but I was wondering - would it work to create a block regressor to cover
>>the
>>period of motion, and assign it a zero in the model (and remove the events
>>during that period from the timing file), so that SPM "ignores" the data
>>from that period? Or would keeping the motion volumes in the model still
>>affect the results somehow? It would be convenient to use this technique,
>>because I was also thinking of using the same technique for the infrequent
>>times when a child falls asleep in the scanner. Does this technique sound
>>dodgy? Thanks!
>>Daniel
>>
> That sounds more reasonable to me not to remove the bad volumes and model
> the full time series.
> You can "nullify" the bad scans by adding an extra regressor to your
> design matrix with zeros for all your scans but 1 for the bad ones.
> I did use that to nullify a dummy volume, i.e. there was a missing volume
> in a series that I substituted by the mean of adjacent volumes and next
> nullify this way (thanks to Tom Nichols for the trick)
>
> I guess this is the same idea for you.
> Hope this helps
>
> Best
> Cyril
>
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