Hi,
I'm very interested in this issue, related to a new study we are currently designing in our lab.
Like Stephen, I was under the impression that comparisons across sessions were valid as long as one modeled session effects with a "constant regressor" (based on this old post by Will Penny: https://www.jiscmail.ac.uk/cgi-bin/webadmin?A2=ind04&L=SPM&P=R147846&m=9593).
Did I misinterpret something ?...
Guillaume

Stephen J. Fromm a écrit :

On Tue, 3 Nov 2009 12:22:12 +0000, Jonathan Peelle <[log in to unmask]> wrote:

Jonathan,

Maybe I'm interpreting Marta's design matrix schematic incorrectly, but doesn't it look like there's an implicit baseline in each of the sessions?  (The dark bands in the regressors for the conditions.)  If so, that would serve as your "C" below.

Of course, everything you wrote stands on its own.

 

Hi Marta

The problem is that the effect in which you are interested (right vs.
left ankle dorsiflexion) is also a difference between sessions.  By
modeling session effects (which is the right thing to do) (columns 3
and 4 of your design matrix), you essentially remove any overall
difference between sessions, making it difficult or impossible to pull
out differences in your conditions.  Put another way, your effects of
interest are confounded with session effects.

If you have a chance to change the design, you could consider one of
the following alternatives:

1) Have both conditions of interest in both sessions (i.e. alternate
left and right ankle movements within both sessions).  This way you
have the same number of events of each type but they are not related
to session effects.

2) Have some baseline condition you can compare the ankle dorsiflexion
to.  This is no doubt explained in more detail somewhere previously on
the list, but the idea is that it's possible to look at an interaction
across sessions, but not really main effects.  I.e.

Session 1: condition A and condition C
Session 2: condition B and condition C

contrast A > B is problematic because of session effects;
contrast: (A > C) > (B > C) would be fine.

If you are stuck with the data as it stands (and no possibility of
finding a baseline condition to add to the model), I don't know if
there is a particularly good solution.  You can choose not to model
session effects, but this will add noise, and I think be a bit harder
to interpret (e.g., is higher signal in a region actually due to your
task, or could it just be a byproduct of one session by chance having
a different level of activity than another?).

Hope this helps,
Jonathan


On Tue, Nov 3, 2009 at 11:46 AM, Gandolla Marta
<[log in to unmask]> wrote:
   

Hi everyone,

  I have some problems in two sessions analysis. I want to compare two
activation maps from the same subject in two different conditions. I built
the design matrix with two sessions (using first level analysis) so I ended
up with four columns as you can see from the first figure of the attached
file. I then did inference analysis with contrast vector of [1 -1 0 0] and I
suppose I shoud get a map with the significative differences between the      

two
 

conditions.
my problem is that if I implement this same approach with maps that are
significantly different for sure (right ankle dorsiflexion and left ankle
dorsiflexion) I get a "difference map" that is not at all as expected. so as
you can see what I'm talking about, the second figure of the attached file
is the result I got.
     

--
___________________________________

Guillaume Sescousse, PhD student
'Reward and decision making' group
Centre de Neuroscience Cognitive
CNRS UMR5229 - UCB Lyon 1
67 Bd Pinel, 69675 Bron, France

tel: 00 33 (0)4 37 91 12 44
fax: 00 33 (0)4 37 91 12 10
http://www.cnc.isc.cnrs.fr
http://www.isc.cnrs.fr/dre
___________________________________