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Subject:

Re: Modeling Question

From:

"n.ramnani" <[log in to unmask]>

Reply-To:

n.ramnani

Date:

Tue, 23 Oct 2001 23:05:03 +0100

Content-Type:

text/plain

Parts/Attachments:

Parts/Attachments

text/plain (106 lines)

Dear Daniel,

I thought I might have a go at answering this one...

At 13:10 23/10/2001 -0400, you wrote:
>Dear SPMers
>
>I have a question about how to best model a particular design.  In this
>design,
>  there are 8 trial types.  Each trial type has 2 stimuli  -- one cue
>and one target, which are separated by 1 TR (1.5 seconds).  This is a cued
>attention task, in which there are two types of cues (task 1 cue and task
>2 cue)
>and eight types of targets, which are defined by crossing Task (task 1,
>task 2), Visual
>Field (LVF, RVF) and Congruency (congruent, incongruent).  I've
>listed the eight types of randomized events below.
>
>1.  Task1 Cue + LVF congruent Task 1 target
>2.  Task1 Cue + LVF incongruent Task1 target
>3.  Task1 Cue + RVF congruent Task1 target
>4.  Task1 Cue + RVF incongruent Task1 target
>5.  Task2 Cue + LVF congruent Task2 target
>6.  Task2 Cue + LVF incongruent Task2 target
>7.  Task2 Cue + RVF congruent Task2 target
>8.  Task2 Cue + RVF incongruent Task2 target
>
>
>     My question concerns the best way to model these events.  One way is to
>assign one regressor to all Task1 cues, a second regressor to all Task2
>cues, and then eight more regressors, one for each type of target.  I'm
>concerned, though, that since there are no cue-only trials (i.e., trials in
>which only a cue appears) it might be difficult for the multiple regression
>technique to distinguish between responses to cue and target stimuli.
>Moreover, the SOA between cue and target stimuli is fixed (i.e., not
>jitterred).
>Would the fact that a given cue can be followed by 4 different types of
>targets
>help with distinguishing cue and target responses if the data were modeled
>in this way?

I agree with the point that you will not be able to reliably disambiguate
the cue and target, and would go further to suggest that this is the case
whatever modeling method you choose. However, you have a balanced 2 x 2 x 2
factorial design. Given that you have a sufficient number of trials and a
rapid enough TR, you will be able to test for the main effects (and the
interaction if this is relevant to your study). If you were to model the 8
event types individually, then you will be able to test for the main
effects of visual field laterality using the t-contrast [-1 -1 1 1 -1 -1 1
1].  This will localise voxels in which the mean activity for presentations
in the left visual field is greater than the mean activity for
presentations in the right, over and above all of the other factors in your
design. Obviously, you could also test for the main effect of congruence
over and above all other components using [1 -1 1 -1 1 -1 1 -1]. In answer
to your question, this is possible because the contrast is balanced across
both levels of cue, and thus the activity from each level of cue
contributes equally to each type of target.

>     A second modeling option is to model each of the 8 event-related
> trial types listed above
>separately.  This could be done by specifying an onset at the time of cue
>presentation and then using temporal and dispersion derivatives to catch the
>target response.  However, I'm concerned that this might not capture enough
>of the target response.  It could also be done by specifying an onset at
>the time of target presentation.
>In this case, however, it seems like each target regressor would probably
>model variance that was due to the target
>as well as the immediately preceding cue.  Is that correct?

That is absolutely correct. There would be little point in using a the
temporal derivative to capture target-related activity. You might, for
example, end up modeling cue-related activity that occurred late (remember
that the forms of haemodynamic responses are heterogeneous), and this would
be mis-attributed to the target. There is also no point in modeling the
targets separately for the reasons you mention.

With best wishes,

Narender


********************************************************************
Dr Narender Ramnani

Sensorimotor Control Group
Department of Physiology
University of Oxford
Parks Road
Oxford OX1 3TP
UK

Oxford University Centre for
Functional Magnetic Resonance Imaging of the Brain,
John Radcliffe Hospital,
Headington,
Oxford OX3 9DU
UK

Tel. 01865 222704 (Direct)
01865 222729 (Admin)
mob. 0771 2632785
Fax. 01865 222717
email [log in to unmask]

*******************************************************************

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