Rik,
Thanks for clarifying this.
Regards,
Greig
> From: Rik Henson <[log in to unmask]>
> Reply-To: Rik Henson <[log in to unmask]>
> Date: Thu, 13 Sep 2001 16:10:23 +0100
> To: [log in to unmask]
> Subject: Re: FIR basis and second level analyses
>
> Greig -
>
> F-constrasts of the type [eye(N) -eye(N)], to compare
> two event-types modelled with N FIR bins, are appropriate
> for detecting any difference between the two event-related
> responses. However, there is nothing wrong with testing
> more focused contrasts if you want to make more constrained
> assumptions about the shape of the response: for example,
> that it peaks between 2-8s poststimulus (when allowing for
> slice-timing differences of 4s, as in the Scandinavian Journal
> of Psychology article you mention), and hence use t-contrasts
> averaged over a subset of bins. You could even constrain
> your constrasts to look for "canonical" responses by choosing
> a "canonical-weighted" constrast of FIR parameters, eg:
> [spm_hrf(b) -spm_hrf(b)], where b is the FIR bin-width and
> spm_hrf.m is the SPM function that returns the canonical HRF
> (assuming in this case that N*b=32s, the default duration
> of the canonical HRF). These more focused constrasts will
> generally buy you more power at the expense of missing
> other shapes of event-locked responses.
>
> The problem comes when you want to do second-level tests
> (eg treating subjects as "random effects"). Though you can
> put the N FIR parameter estimates into a 2XN repeated-measures
> ANOVA (using the SPM PET interface), and test for an event-type-
> by-time interaction, you will need to make some correction for
> nonsphericity (the fact that the N parameters are unlikely to be
> independent or identically distributed over subjects - this is why
> Andrew labelled such designs "'Dodgy' population inference"!).
> We have been working on this in the development version of SPM
> (see Glaser et al, HBM 2001), in the context of more general
> variance-component estimation, but it is not quite ready for release.
> Alternatively, you could use the "hidden" SPM feature of multivariate,
>
> second-level statistics, which evade (or "eschew" perhaps? ;-)
> the problem of nonsphericity - see our HBM2000 abstract on my
> webpage if interested - though are generally less powerful.
>
> Note one nice thing about the "canonical-weighted" contrasts on
> an FIR model that I mentioned above is that you can take the
> resulting con*imgs into a second-level, one-sample t-test, just
> as if you can used an canonical HRF basis function in the first-
> level model, rather than the FIR basis set. Provided that the binsize
> equals the effective peristimulus sampling rate, you will get
> mathematically the same parameter estimate for the canonical-
> HRF-first-level-model as you do for the canonical-HRF-weighted-
> constrast-on-an-FIR-first-level-model. The nice thing about putting
> constraints on the shape of the HRF into the contrasts of an FIR
> model, rather than into the original regressors (at least for
> subsequent
> second-level analyses), is that you can test for different shaped
> responses simply by adding new contrasts, without needing to
> re-fit a (typically large) first-level model.
>
> Hope this makes sense
> Rik
>
>
> Dear Rik,
>
> I note that your HBM abstract describes F-contrasts with the FIR
> method and
> that the SPM99 manual also suggests F-contrasts are need for
> meaningful
> inference (p. 39). However, your paper on repetition priming in the
>
> Scandinavian Journal of Psychology reports t-contrasts performed on
>
> parameter estimates from several bins. This suggests that a
> second-level
> analysis might be conducted with t-contrast images derived using
> the FIR
> method. Could you clarify whether this is the case?
>
> Regards,
>
> Greig
>
>> From: Rik Henson <[log in to unmask]>
>> Reply-To: Rik Henson <[log in to unmask]>
>> Date: Thu, 6 Sep 2001 18:22:50 +0100
>> To: [log in to unmask]
>> Subject: Re: FIR basis?
>>
>>
>> Attached is an extended version of spm_get_bf.m that
>> includes an FIR basis set for event-related analyses (which
>> prompts for binsize, in seconds, and number of bins - see
>> SPM manual for more details) and that should work fine
>> with the released version of SPM99.
>>
>> For the pros and cons of an FIR model to make inferences,
>> see Henson et al. (2001), HBM01 abstract, Neuroimage, 13, 149,
>> though note erroneous labelling of figures in published version;
>> correct version available from:
>>
>> http://www.fil.ion.ucl.ac.uk/~rhenson/refs.html
>>
>> and for the use of an FIR model to plot data as a function of
>> peristimulus time, see recent posting by Russ Poldrack:
>>
>>
> http://www.jiscmail.ac.uk/cgi-bin/wa.exe?A2=ind0108&L=spm&P=R6690
>>
>> http://www.nmr.mgh.harvard.edu/~poldrack/spm/pst_avg.html
>>
>> Best wishes
>> Rik
>>
>
> --
> Dr Greig de Zubicaray
> Centre for Magnetic Resonance
> The University of Queensland
> Brisbane, QLD 4072
> AUSTRALIA
>
> Tel: +61 (0) 7 3365 4250 [direct]
> +61 (0) 7 3365 4100 [CMR]
> Fax: +61 (0) 7 3365 3833
> --
> ---------------------------8-{)}-------------------------
>
> DR R HENSON
> Wellcome Department of Cognitive Neurology
> & Institute of Cognitive Neuroscience
> University College London
> 17 Queen Square
> London, WC1N 3AR
> England
>
> EMAIL: [log in to unmask]
> URL: http://www.fil.ion.ucl.ac.uk/~rhenson
> TEL1 +44 (0)20 7679 1131
> TEL2 +44 (0)20 7833 7472
> MOB +44 (0)794 1377 345
> FAX +44 (0)20 7813 1420
>
> ---------------------------------------------------------
> --
--
Dr Greig de Zubicaray
Centre for Magnetic Resonance
The University of Queensland
Brisbane, QLD 4072
AUSTRALIA
Tel: +61 (0) 7 3365 4250 [direct]
+61 (0) 7 3365 4100 [CMR]
Fax: +61 (0) 7 3365 3833
|