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:
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 <mailto: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-users.york.ac.uk/%7Eta505/>
http://www.york.ac.uk/depts/psych/www/admissions/cns/
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Silvia Gennari
Department of Psychology
University of York
York, YO10 5DD
United Kingdom
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Silvia Gennari
Department of Psychology
University of York
York, YO10 5DD
United Kingdom