9 Jul
2008
9 Jul
'08
11:22 a.m.
Hi, again,
Just one more comment. What I just said only holds if you are
scanning people in the same day one run after the other. If one scan
people in different days, there are additional complications having
to do with motion correction and alignment of the images over time.
Are you talking about sessions in different days?
Silvia
On 9 Jul 2008, at 12:11, Silvia Gennari wrote:
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:
Silvia Gennari
Department of Psychology
University of York
York, YO10 5DD
United Kingdom
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(a)ynic.york.ac.uk wrote:
Silvia Gennari
Department of Psychology
University of York
York, YO10 5DD
United Kingdom
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ynic-users(a)ynic.york.ac.uk
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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/
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