Dear Anusha and Karl,

We have used a similar paradigm in our experiments (something we call
event triggerred scanning):

Stim1->ISI1->TR1->TR2->ISI2->Stim2->ISI1->TR1->TR2...
The exact values depended on the study.
TR1 = TR2 = 2 to 3 seconds
ISI1 = 4 to 5 seconds
ISI2 = 10.5 to 18 seconds

We have analyzed it in SPM to using an FIR design with onsets defined
as scans and FIR length of TR1+TR2. We are interested in the magnitude
of the response and not in the temporal profile. And this has worked
very well.

Hope this helps,

Satra

On Thu, 17 Mar 2005 15:32:41 +0000, Karl Friston
<[log in to unmask]> wrote:
> Dear Anusha,
>
> >I am trying to analyse fmri data collected using sparse temporal sampling
> >technique using SPM2.
> >
> >The experimental design as follows:
> >
> >For a TR of 12 secs a partial volume of brain is acquired for first 1.5
> >sec and the scanner is silent for 10.5 sec. This pattern was repeated for
> >about 8 mins acquirinng in total 40 partial volumes. The task was a
> >listening task where the auditory stimuli was presented during the silent
> >period alternated with silent base line. Basically it is an ABAB design
> >with partial volumes acquired at the begining and at the end of a block.
> >
> >I have analsyed this data set using spm99 with TR=12sec and boxcar basis
> >function convolved with heamodynamic response function. The results looked
> >very good with very strong activation in the auditory regions.
> >
> >Howevr, I am unable get the same results with spm2. I dont get the
> >auditory regions activated, even at very low significant level. I have
> >tried with TR = 12 sec, basis function as heamodynamic response function
> >wih time derivatives and 0 sec duritaiion for the trials. I have also
> >tried 12 sec duration for the trial as I thought this may produce a basis
> >function similar to a boxcar function.
> >
> >What is the correct method to analyse this data ? what are the correct
> >inputs to spm2 to reproduce spm99 results ?
>
> That's an interesting question.  I think the problem is in the convolution
> with the HRF, with such a long TR.  First, with this TR there is no
> information
> in your data to estimate efficiently the temporal derivative.  Therefore, you
> should just use the canonical HRF.  Second the default bin sizes for the
> convolution
> are 1/16 of the TR.  This is getting a bit long for a 12 sec. TR.  Could you
> change the defaults to 1/64 of a TR?  If this does not work I would trick SPM2
> into not convolving at all;  You can do this by using a single basis function
> which is 1 for one time bin.  e.g. a Fourier set with one component and a
> very small duration (temporal support).
>
> If this does not work, use PET models and simply construct the ABAB regressors
> by hand (serial correlations in fMRI can be discounted with a 12 sec TR).
> If you do this, do not forget to put the low frequency confounds (i.e. drift
> terms) in the design matrix.
>
> I hope this helps - Karl
>


--
--
Satrajit Ghosh
Postdoctoral Associate
Speech Communications Group
Research Lab of Electronics, MIT