Dear Cyril and Amitai,
Just so support Cyril's answer. In a variable epoch approach you are
dealing with HRF duration, not amplitude. Alternatively, in a
parametric modulation you are dealing with amplitude changes, not
length. The paper above and these ones:
http://www.columbia.edu/cu/psychology/tor/Posters/grinband_HBM06.pdf
http://www.fmri.org/pdfs/RT%20in%20fMRI.pdf
show that RTs has to do more with HRF length, instead of amplitude.
Their method is better to capture RTs regressors. However optimizing
the model to check RTs and then trying te remove them with a
parametric modulation will have the opposite effect. The modulation
will catch much less variability in amplitude because it's actually
explained in length. Then the following regressors will have a lot of
RTs effect (even though orthogonalized) because it is inherent to the
model and cannot be removed.
Hope I'm right and this helps.
Regards.
Dorian
2009/3/4 cyril pernet <[log in to unmask]>:
> Hi Amitai
>>
>> Hi Cyril,
>>
>> There was a recent paper, in neuroimage I think, where RT of each
>> trials was used to model the hrf (instead of 0 modeling an
>> inpulse) and this model was compared with a standard approach (1
>> column for the regressor + modulation by RT) -- clearly it was
>> better to directly 'modulate' the 1st regressor, but it may not
>> always be possible to do so .. cannot think of anything else here ...
>>
>>
>> I would love to get the reference for the paper you mentioned if you
>> happen to have any more information about it.
>
> Dorian pointing me the paper I was referring to
>
> Grinband et al, Detection of time-varying signals in event-related
> fMRI designs, NeuroImage, Volume 43, Issue 3, 15 November 2008
> (http://www.sciencedirect.com/science/article/B6WNP-4T77G33-4/2/cc5ef4a8e9fbff5b4a99bd5f05663bf9)
>
>
>> Also, when the discussion is raised over the use of variable duration HRF
>> and utilizing an RT regressor, they are generally suggested as alternatives
>> to one another. Is there a concern regarding the use of both of these in
>> unison (i.e., modeling the HRF with trial-specific RTs and then regressing
>> out RT before adding additional parametric regressors)?
>>
> well you would model the hrf using RT so that it accommodates natural
> cognitive and motor related variations in the neural dynamic - of course you
> may loose some info regarding the sensorial/perceptive processing which
> would not vary according to this.. - anyway; now you try to regress out RT
> for each trial - how would you do that? even if you could, what would that
> mean? remember that the 1st part in about making a model of the hrf with
> variation in shape (time and amplitude) then you would try to regress out
> something like the amplitude or so ?? I'm really unsure about all this ...
> sorry
>
> cyril
>
>
>
>
> --
> The University of Edinburgh is a charitable body, registered in
> Scotland, with registration number SC005336.
>
|