There's the general issue of whether one can compare conditions that aren't in every session, and then there's the specific question of Marta's set-up.
Generally, I think it's OK, meaning its valid. My recollection is that there's a concern with experimental power, but that's besides the point if there's no other way to design the experiment. Penny's link you provided below has a good summary of the issues.
Best,
Stephen J. Fromm, PhD
Contractor, NIMH/MAP
(301) 451--9265
________________________________________
From: Guillaume Sescousse [[log in to unmask]]
Sent: Tuesday, November 03, 2009 6:34 PM
To: Fromm, Stephen (NIH/NIMH) [C]
Cc: [log in to unmask]
Subject: Re: [SPM] two sessions analysis
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
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