Dear Jeff, Alle, List,

isn' t it the case that the HRF, dHRF/dt and dHRF/dD (D=duration) are
by itself orthogonal basis functions? To my experience regressors for
the basis functions only become colinear when one uses a rapid
event-related design, where the HRF of event N can be colinear with,
say, the dHRF/dt of trial N+1. That of course is only the case for short
inter-event-intervals with respect to the duration of the BOLD response....

Correct me if i'm wrong...

cheers,

Bas

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Dr. S.F.W. Neggers
Division of Brain Research
Rudolf Magnus Institute for Neuroscience Utrecht University Medical
Center

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Alle Meije Wink wrote:
> Hi Jeff,
>
> In situations where the HRF is a bad fit, it may be a good idea to use
> derivatives. But this does come at a cost, because you have three
> times as many regressors that, in general, are not orthogonal. There
> is variance that is explained by the HRF, and variance explained by
> the derivatives, but there is also variance that could be attributed
> to both.
>
> In the case of a consistent mismatch of the HRF, it may be better to
> - look for a different HRF (ths may sound a bit drastic)
> - use AR modelling to get rid of autocorrelations in the noise
> The second option is available in SPM. Kalina Christoff made a tool to
> do the first option
> (http://www-psych.stanford.edu/~kalina/SPM99/Tools/eHRF.html). It's a
> very simple tool, but it does the job.
>
> Best,
> Alle Meije
>
> Jeff Browndyke, Ph.D. wrote:
>> A few questions about the use of time and dispersion derivatives:
>>
>> If one uses time and dispersion derivatives in a model, does this
>> mean that
>> error variance associated with the canonical HRF is "soaked up" in the
>> model? If this is the case, then why wouldn't these be included as a
>> matter
>> of routine when employing the standard HRF? I understand there are
>> waveforms that are devoid of some of the canonical HRF constraints, but
>> wouldn't using one of these mean that you are just incorporating into
>> your
>> model what would otherwise be error variance in the canonical HRF
>> situation?