> I think this is important to note.
> So do you see any problems in applying FLOBS or filmbabe at the first
> level with regards to higher-level stats?
The problems are not above and beyond using _any_ basis set approach at
the first level - and those problems were sketched out in my last email.
> -----Ursprüngliche Nachricht-----
> Von: Mark Woolrich [mailto:[log in to unmask]]
> Gesendet: Mi 24.11.2004 12:49
> An: [log in to unmask]
> Betreff: Re: [FSL] FLOBS?
> >I am looking for a method to test for differences in the BOLD-time course
> >between two groups. Ideally, I would like to test for differences in time
> >to peak, full width half maximum, time to onset etc.
> >Perhaps FLOBS can be used to do this.
> Unfortunately, not easily. You probably have in mind the parameterised HRF
> made up of half cosines upon which FLOBs is based. However, FLOBS only
> uses this parameterised HRF to generate a linear basis set. Hence any
> explicit parameterisation of time to peak etc. is lost. It is possible to
> recover the time to peak etc. by extracting them from the inferred basis
> set impulse response function (IRF) (e.g. finding the time to peak for the
> smoothed basis set IRF is not difficult).
> >I have one condition only: when I
> >use FLOBS using the default functions, I can ask for 3 contrasts (one for
> >each regressor) and for the F-test giving me a linear combination of the
> >3 functions.
> >My question now is: how can I use these FLOBS results at second level?
> >Are there ways to compare the best fit of the BOLD response between group
> >A and B?
> >Is there perhaps a way to extract measures such as time to peak, fwhm
> >etc, and then use these at second level?
> This relates to a general problem that exists when we try to use basis
> sets with group studies. That is, if we pass up the COPEs for each of the
> basis functions to a second level, and then look for differences between
> groups of subjects, then we could get a significant difference not only
> for a difference in size of effect, but also for a difference in
> shape of effect. There is no simple way to separate out this two
> possiblities using basis functions. Instead, you would need to recover
> explicit estimates of size, time to peak etc. from the inferred basis set
> IRF from the output from the first level (see above) and then
> pass them to the second level. There is then the question of whether you
> can assume gaussianity at the second level for these sorts of parameters,
> I have no experience of this - so couldn't say definitively. If they are
> Gaussian then you can do a traditional OLS random effects analysis, if not
> then you could still use nonparametric stats.
> Cheers, Mark.
> Mark Woolrich.
> Oxford University Centre for Functional MRI of the Brain (FMRIB),
> John Radcliffe Hospital, Headington, Oxford OX3 9DU, UK.
> Tel: (+44)1865-222782 Homepage: http://www.fmrib.ox.ac.uk/~woolrich