Hi, Andre, 

To continue with this issue. I think from a user point of view, it would be better to follow option (2) because you then do analyses as usual treating all the data for each subjects as you would if you did not have memory limitation.

If people have complicated designs, as  it is normally the case for people who need to scan for a long time, the data analysis becomes even more complicated, and the room for errors increases. 

I think I was wrong to suggest earlier that FSL would automatically deal with this problem. If I understand it correctly, the problem is that for different scans, the arbitrary intensity values are going to be very different, right?.  So the mean intensity for one scan can be, say, 1000, while for another scan of the same individual, it could be 4000. Doing grand-mean scaling does not seem right here, which is what FSL automatically does. But if you de-mean each scan (i.e., subtract its raw mean intensity, which results in a mean intensity of 0 for each scan), there should be no problem then combining the scans as if they were all coming from the same one, as the mean intensity would be the same for all.  The 'avwmaths' commands in FSL will compute this very easily  (assuming I am getting this right). 

Apparently, people did this routinely at the Waismann Institute, so I actually never heard of someone having to analyze the data separately for each scan. Maybe some softwares do this pre-processing by default. My experience with Voxbo was such that, even when we had 8 or 10 different scans per person (an hour of scanning), we did not have to worry about it in the analysis.  

Silvia


On 8 Jul 2008, at 16:20, Tim Andrews wrote:

Hi Andre,

We are doing this at the moment with FSL.  Our design has 10 subjects 
who each do 2 sessions (however, the number of sessions each subject 
does could vary).  We do a first level analysis on the 20 (10 * 2) 
scans.  We then do a second higher-level analysis in which we combine 
the two sessions from each subject.  This is followed by a 3rd 
higher-level analysis in which we look at the activation across subjects 
for each contrast.

Cheers,

Tim

andre@ynic.york.ac.uk wrote:

Dear Users,

Concatenation or higher level stats?

We would value the input of any users who have experience of 'combining'
fMRI data across multiple runs for more robust averaging.

The issue arises when trials of an experient are acquired in different
data blocks due to technical limitations of scan scquisition protocols or
often to reduce the strain on participants in a single session.

I have searched many available resources. There are well documented
routines for (1) analysinng the sessions individually and then compring
them with a higher level analysis or (2) demeaning the two timeseries and
combining them into a single one .. then following the standard analysis
individual subject routine.

Comments would be appreciated (especially from anyone has first hand
experience of doing this).

Thanks

Andre'





-- 
Dr Tim Andrews
Department of Psychology
University of York
York, YO10 5DD
UK

Tel: 44-1904-434356
Fax: 44-1904-433181

http://www-users.york.ac.uk/~ta505/
http://www.york.ac.uk/depts/psych/www/admissions/cns/



-- 
ynic-users mailing list
ynic-users@ynic.york.ac.uk
https://www.ynic.york.ac.uk/mailman/listinfo/ynic-users



Silvia Gennari
Department of Psychology
University of York
York, YO10 5DD
United Kingdom