Hi Andreas,
motion explains a large part of the variance in the data even after
"motion correction". The following may be things you could try (in no
particular order):
- use an expanded set of motion regressors (e.g., include shifted and
squared versions)
- include an extra regressor for seriously affected volumes
- try my motion fingerprint which may be better able to differentiate
motion and activation (at least I hope so :)
- interpolate/replace severely affected volumes (for example using art
repair)
Cheers,
Marko
Andreas Lidström wrote:
> Hello SPM,
>
> I am doing fmri covariation analyses and for some subjects I am picking
> up covariation along the edges of the brain. This is clearly due to
> movement and I can see a clear shift in the estimated motion regressor
> for the relevant axis.
>
> My question is why this regressor is not enough to combat the misplaced
> covariation.
> I am using SPM8. Is there something else besides excluding images I can
> do to maybe improve the model? Do you recommend using programs like
> ArtRepair?
>
> /Andreas
--
____________________________________________________
PD 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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