Marek,
I may have gotten your explanation wrong but I think you are taking a
very complicated approach - why not simply do what the reviewer
suggested, i.e., count number of scrubbed scans per condition? I think
trying to determine whether the impact of scrubbing is different would
only be my second step, after ascertaining that an impact is to be
expected in the first place...
Or in other words - if all subjects had a comparable number of scans
removed, and these were randomly distributed across conditions - why
bother determining BOLD signal amplitude etc.?
Cheers
Marko
Marek Wypych wrote:
> Dear SPMers
>
> In the review of our paper on children (who move quite a lot, and we
> used ART to regress out moved volumes) one of the Reviewers asked: “Did
> the authors verify that the number of “rejected” scans was equally
> distributed across conditions?” So we want to check it now.
>
> In the experiment we had four conditions: two visual and two auditory.
> The experimental design was quite rapid – visual trial lasted about 2
> seconds and auditory about 4 seconds. The ITI was randomized and
> differed between 4-7 seconds. Thus, after convolution of the design with
> the standard HRF (which has max about 12 seconds after the onset), the
> conditions in the model partly overlap, and “rejection“ of one volume
> may affect few conditions in the same time.
>
> My idea is to read the (absolute) values of predicted BOLD signal in the
> moment of volume rejection across all conditions from design matrix in
> the estimated SPM.mat (SPM.xX.X) and then to sum it within each condition.
> 1. First: do you think it is a good idea? Or maybe you have other
> suggestions?
>
> 2. Assuming this is a reasonable idea, I have the second question. As I
> have already mentioned the trials differed in length – thus the
> predicted BOLD will have higher amplitude in longer (auditory) trials,
> than in shorter (visual) trials. Should I normalize the values by the
> length of the trials? As I understand GLM normalizes the condition to
> calculate betas (am I right?), so to estimate the influence of motion on
> betas I should also normalize it?
>
> I’ll be grateful for your comments and suggestions.
>
> Best regards
> Marek
>
>
>
>
--
____________________________________________________
Prof. Dr. med. Marko Wilke
Facharzt für Kinder- und Jugendmedizin
Leiter, Experimentelle Pädiatrische Neurobildgebung
Universitäts-Kinderklinik
Abt. III (Neuropädiatrie)
Marko Wilke, MD, PhD
Pediatrician
Head, Experimental Pediatric Neuroimaging
University Children's Hospital
Dept. III (Pediatric Neurology)
Hoppe-Seyler-Str. 1
D - 72076 Tübingen, Germany
Tel. +49 7071 29-83416
Fax +49 7071 29-5473
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http://www.medizin.uni-tuebingen.de/kinder/epn/
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