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Hi Daniel,
    I would tend to enter each session separately and not to concatenate
into one long session per subject.
I can think of a few reasons for this, primarily b/c the event-related
response do not overlap across sessions.  Using this procedure one can still
create a subject specific contrast for random effects analyses.  I would use
the default settings for the high pass filter.  Low pass filtering is a
little different story - I believe it is recommended to use the hrf, but we
typically filter our data outside spm b/c we (and others) have noticed high
frequency noise can be prevalent in some scanners.  I also would realign
each of the sessions separately.
Other groups may have different opinions.

Best regards,
Kent
______________________________
Kent A. Kiehl, Ph.D.
2255 Wesbrook Mall
Departments of Psychology and Psychiatry
University of British Columbia
Vancouver, B.C., Canada, V6T 2A1
http://www.psychiatry.ubc.ca/sz/nilab/personnel/kiehl/
Office 604-822-0777; Lab 604-822-7128; Fax: 604-822-7756

----- Original Message -----
From: Daniel Weissman <[log in to unmask]>
To: spm <[log in to unmask]>
Cc: <[log in to unmask]>
Sent: Monday, March 13, 2000 12:30 PM
Subject: Number of Sessions per subject


> Hi,
> I've just run an event-related fMRI study that in which I
> collected 8 "blocks" of data for each subject.  Each block was a 6-minute
> long scan.  I'm wondering whether it is better to enter each "block" as a
> separate session in the analysis (i.e., 8 sessions per subject), or to
> "pool" all 8 blocks from each subject into one huge session (i.e., one
session
> per subject).
>
> In the discussion list, some have recommended "pooling"
> multiple sessions into one big session for each subject (9/22/98),
> but others have argued that such pooling might not be a good idea
> (10/15/99).
>
> I'd appreciate any advice and, if it is possible to perform the
> analysis in both ways, I'd be interested to know whether and how the
> high- and low-pass filters should be set in each case.
>
> Thanks,
> Daniel Weissman



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