Dear Klaas
Thanks for your fast response.
please see my followup questions below.
On Mon, 14 Nov 2005 19:35:23 +0000, Klaas Enno Stephan
<[log in to unmask]> wrote:
>Dear Tali,
>
>it is usually not a good idea to use the same
>input as a driving input to one region and as a
>modulator of an afferent connection originating
>in that region. The reason is that the
>conditional estimates of both parameters will be
>highly correlated and, given that the prior
>variance for driving inputs is higher than for
>modulatory ones, this will tend to over-estimate
>the driving parameters and under-estimate the
>modulatory parameters. In other words, your
>estimates are based. (In complex networks this
>is not always true, but it is a good
>rule-of-thumb. Individual cases are best checked using simulations.)
>
>In your case, it seems best to define an input
>that includes words and symbols (assuming that
>they equally activate the input region, let's
>call it A1) but not fixation (assuming that this
>does not activate A1) and define a second,
>modulatory input that only includes words. In
>this way, you are testing whether a word-related
>activation in the target region (A2) can be
>explained by a selective increase of the
>connection from A1 to A2 during the presentation of words.
1- Would this affect also the modulatory effects on connections that DO
NOT involve the input region (i.e. in your example a connection from A2 to
A3)?
2- If we define an input of both 'words+symbols' (mixed) and another input
of just 'words' in the conventional analysis, they are going to be non-
orthogonal, and no variance will be left for the 'words' contrast. Is this
appropriate to do in the conventional model?
>
>All things above are independent of whether you
>use a blocked or event-related design.
>
>Best wishes,
>Klaas
>
>PS. When you say "adjust" to you mean the
>adjustment in the extraction of data (VOI tool)?
3- yes, by "adjusting the ROI" I refer to the extraction of the data in
the VOI tool. If I only adjust for an F contrast of 'words'
and 'fixation', does it make any difference? Would I still need to
use 'symbols' as a driving input?
Thanks a lot.
Tali
>
>
>At 17:50 14/11/2005, Tali Bitan wrote:
>>Dear DCM Experts:
>>
>>We have a question about how to best disabmiguate
>>between driving inputs and bilinear effects using
>>a non-factorial, event-related study.
>>
>>We have 3 conditions in the time series: 'words',
>>'symbols' and 'fixation'. We have adjusted the
>>ROI to include all 3 effects. We are only
>>interested in the effect of words, so in the DCM
>>model we only have 'words' as the driving input
>>to the input region, and also as exerting a
>>bilinear effect on all connections, except for
>>the connections that go back to the input region.
>>Is this the correct way to go?
>>
>>Or - do we need to include all 3 effects (words,
>>symbols and fixation) as (separate vs. a single
>>combined) driving input(s) on the input region,
>>while only the 'words' would have a bilinear effect on all connections?
>>
>>If so - would the situation be different if we
>>only adjust the ROI for 'words' (rather than all
>>three effects)? Do we still need to include
>>'symbols' and 'fixation' as driving inputs?
>>
>>Is all this true only for an event-related design, or also for a block
>>design?
>>
>>thanks a lot.
>>Tali Bitan
>>
>>-------------------------------------------------------------------------
--
>>----------------------
>>Dear Tali here is my first crack at the question:
>>
>>I've looked through the DCM code. As we thought,
>>what it does is it takes the a, b, and c
>>parameters and the hemodynamic priors and then
>>sets up the expected neuronal and then
>>hemodynamic responses. The c parameters determine
>>the activity in the system, so no c parameters =
>>no system activity. I have tried this and
>>verified it. In a sense it almost seems as if DCM
>>creates signals in a networks based on the
>>driving inputs, and then sees if that signal can
>>be alternatively modeled by some combination of
>>an interaction and the signals from other
>>regions ((signal x input) + multi-regional
>>signal). I think this is why DCM seems best
>>conceived when the experiment allows different
>>driving and modulatory effects (i.e., based on an ANOVA model)
>>
>>In usual GLM statistics, if your design matrix
>>leaves out (regressors, covariates, conditions)
>>that specify important aspects of variance, that
>>variance ends up in the residuals and affects the
>>p-values. If this variance substantially
>>contributes to the residuals and has some defined
>>structure it may violate some assumptions of the GLM as well.
>>
>>I don't know whether the same is true in DCM. If
>>you include words as driving inputs and as
>>modulatory effects, but the data is based
>>on words+symbols+fixation then 1) the design
>>will only generate activity related to words. 2)
>>This will potentially work against you when you
>>then try to use the same input as a modulatory
>>effect. 3) When DCM tries to compare the expected
>>signal vs. the actual signal there will be a significant discrepancy.
>>
>>What does this all mean about how best to use DCM
>>given the difficulty of some experimental
>>designs? I'm not sure but I think you should
>>probably use words+symbols+fixation as an input
>>and just words as your modulatory effect. If you
>>just use words as input then the design would
>>probably be best for just examining differences
>>in the intrinsic models for the network. See
>>Ethofer et al., Cerebral pathways in processing
>>of affective prosody: A dynamic causal modeling study. Neuroimage, in
>>press.
>>
>>I would be very interested in the thoughts and
>>commentary from real DCM experts on your questions and my reply.
>>
>>Darren
>>
>> >----------------------------------------------
>> >Tali Bitan, PhD
>> >Department of Communication Sciences & Disorders
>> >Northwestern University, IL
>> >Phone (847)467-1549
>>
>>-------------------------------------------------------------------------
>>Darren R. Gitelman, M.D.
>>Cognitive Neurology and Alzheimer¹s Disease Center
>>Northwestern Univ., 320 E. Superior St., Searle 11-470, Chicago, IL 60611
>>Voice: (312) 908-9023 Fax: (312) 908-8789
>>-------------------------------------------------------------------------
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