Hi Susie,
assuming you are referring to page 43 in the PDF which is currently
online (and don't happen to have an earlier version a hand) this slide
has been included to show that such noise effects can be detected
simultaneously in a single FMRI data set, all previous slides discuss
separate artefacts in turn but never explicitly state that various
different ones can be present at the same time.
Wrt head motion I need to point out that the ability to denoise data
using ICA (or any other linear technique) is limited - head motions
are very non-liear in nature, so ICA typicaly fractionates the effect
across multiple components in order to account for it. This makes
identifying motion related components somewhat difficult. Having said
all this I find that in a lot of cases such a denoising approach can
still improve the later stats a lot and is worth a try
hopt this helps
Christian
_______________________________________________
Christian F. Beckmann, DPhil
Senior Lecturer, Clinical Neuroscience Department
Division of Neuroscience and Mental Health
Imperial College London
Hammersmith Hospital - London W12 0NN
Tel.: +44 (0) 208 383 3722 --- Fax: +44 (0) 208 383 2029
Email: [log in to unmask]
http://www.imperial.ac.uk/medicine/people/c.beckmann/
Senior Research Fellow, FMRIB Centre
University of Oxford
JR Hospital - Oxford OX3 9DU
Tel.: +44 (0) 1865 222551 --- Fax: +44 (0) 1865 222717
Email: [log in to unmask]
http://www.fmrib.ox.ac.uk/~beckmann
On 20 Jun 2008, at 17:41, Susie Heo wrote:
> Hello,
> I am trying to denoise data from subjects with excessive movement in
> a fast event-related design
> but am having difficulty determining which components extracted
> through MELODIC can be
> definitively considered as noise. I have looked at the MELODIC
> lecture and it has helped a bit,
> however I am not sure what is the take-home-message behind slide
> 43. I would appreciate any help
> or suggestions!
>
> Susie
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