Dear Christopher,
1) Yes – see my email to Amit.
2) This is a useful analogy for most cases,
but the relationship may not always hold. There
are two main reasons. First, remember that the
hemodynamic model in DCM is not equivalent to
convolution with a canonical HRF but can cover
more general forms of hemodynamic responses that
you would, in a GLM, model as a linear
combination of basis functions. If you happen to
have a biphasic BOLD response, for example, which
resembles the superposition of a canonical and a
first derivative, then you can model this by
feeding a negative neural state in the Balloon
model, and this negative neural state may require
that the driving input to that region becomes
negative. Second, the influence of
back-connections in the model may be able to
explain parts of the dynamics in the input
regions, thus changing the numerical value of the driving input.
Put a different way: the analogy is tight if (i)
the GLM uses several basis functions and (ii) the
DCM feeds all inputs to all areas but does not
use any connections between areas (compare Figure
2 in Stephan 2004, Journal of Anatomy).
3) Ideally, one would want to incorporate
all experimental manipulations into the
DCM. Whether or not this is necessary, depends
on how much of the dynamics can be modelled by
the unaccounted manipulations. The same kind of
question arises for any other model, of course, including the GLM.
4) Not sure I understand this
question. What do you mean by "there are more
zeros than non-zero datapoints"? Note it is not
unusual to find the B values to be rather close
to zero. After all, they are estimated using shrinkage priors.
Best wishes,
Klaas
At 13:05 28/04/2006, Christopher Summerfield wrote:
>hi Will & Klaas & others....
>
>1) to repeat Amit's recent question - I think he didn't receive a
>reply - how can one interpret a significant modulatory connection (B) when
>the intrinsic connection (A) is not significant? is is something like: at
>baseline, these regions show little or no coupling, but they begin to do
>so following that particular task peturbation??
>
>2) Am I right in assuming that inputs in the C matrix should pretty much
>track GLM effects - for example, a region defined by its GLM repsonsivity
>to a regressor coding all visual inputs (like 'photic' in the worked
>example) should be modulated by that regressor in the DCM analysis (like
>'connect photic to V1/V2' in the worked example? If this is *not* the
>case...are the DCM and GLM results contradicting each other?
>
>3) In the GLM analysis, variance which is not modelled in the design
>matrix will either be captured by other regressors, or find its way
>into the residuals. Does the same apply for DCM? I remember reading
>something to the contrary on this list, or perhaps in the 2003 paper.
>Practically, does this mean that it is not mandatory to model all visual
>events? for example, in the worked example, there were presumably stimulus
>events such as task instructions - were these modelled in 'photic'? or
>were they just left out?
>
>4) My DCM.B matrix is peppered with zeros (for
>those modulations specified in DCM.b). Why might the modulation be
>exactly zero for a given subject/session? is it because the GLM data for
>that subject/session/voxel don't reach a certain threshold? For some
>modulations, there are more zeros than non-zero datapoints.
>
>many thanks,
>Chris
>
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>Christopher Summerfield
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