Dear Rik,
thank you a lot for your clarifications, they have been very helpful!
Sorry for asking some follow-up questions...
> Note that the overall pattern in a voxel depends on both the 1st and 2nd
> order estimates and could be monotonic or non-monotonic (depending on the
> relative weight of the two estimates). If monotonic, you could, I suppose,
> label as an overall increase or decrease.
After modelling both 1st and 2nd order modulations, I assume that a plot of
parametric responses shows a linear combination of both estimates. Is there
any way to tease the contribution of the two estimates apart and plot them
separately?
> It depends on 1) what F-test you did in the model with both A and B
> modulations, and 2) what contrasts you used to create the con*.img files
> that comprise the data for the model.
Sorry, I didn't mention the contrasts as I did not want my previous message to
be too long. I am actually using a FIR model, so the contrasts are almost
intelligible. But let say I only model the canonical hrf with 1st and 2nd
order parametric estimates. The t-contrasts I entered in the RFX analysis
were:
[0 1 0 0 0 0] and [0 0 1 0 0 0] for condition A
[0 0 0 0 1 0] and [0 0 0 0 0 1] for condition B
At the 2nd level I entered an F-contrast [-1 0 1 0; 0 -1 0 1] that yielded a
significant effect in area X, and the sign of this effect was negative.
So, If I have understood you correctly, there may be several alternative
interpretions, and the correct one may be inferred by having a look at data
plots:
1) both show U-shaped modulations (just larger for A)
2) both show inverted-U-shaped modulations (just smaller for A)
3) A shows a U-shape and B an inverted U-shape.
The average parametric plot actually presents yet a different situation with A
showing an inverse U-shaped response and B a U-shaped response.
But maybe I am looking at data plots in the wrong way... Does it make any
sense to extract individual parametric plots and then look at the average
response? The variability across subjects/sessions is quite high: is there
any way to gain a measure of variability from the SPM parametric plot
facility?
Again, thanks a lot for your help!
Marco
--
Marco Tettamanti, Ph.D.
Department of Neuroscience
Scientific Institute San Raffaele
c/o L.I.T.A. - room 25/5
Via Fratelli Cervi 93
I-20090 Segrate (MI)
Italy
Tel. +39-02-21717552
Fax +39-02-21717558
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