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