2009/3/10 Todd Thompson <[log in to unmask]>

I haven't yet fully digested the Calhoun 2004 Neuroimage paper which
talks about using temporal derivatives to improve your model fit, but
if my skimming is accurate, the gist seems to be that you want to run
an f-test between the EV and the temporal derivative of the EV, and
use the result of that f-test as the input to your second level model,
rather than using the parameter estimate of the EV.

Is that the general approach FSL users take? Is that easily doable in
FSL? Or have I totally mis-skimmed the paper?

Thanks,
Todd

On Tue, Mar 10, 2009 at 4:26 AM, Steve Smith <[log in to unmask]> wrote:
> Hi,
>
> This makes sense, yes. If you are happy that the temporal derivative is
> accounting for lag changes then you could simply compare models by look at
> the zstat on the EV of interest for each model - or as you say look at
> second-level stats for further confirmation.
>
> Cheers.
>
>
> On 9 Mar 2009, at 15:30, Vishwadeep Ahluwalia wrote:
>
>> Thanks Steve! once i run the 1st level analysis using different models , i
>> was planning on
>> comparing the models by comparing the PE values extracted from an ROI
>> after running the
>> group analysis. Is this a valid approach? or is there a better way to do
>> this. Also, i'm
>> slightly confused about whether i should be using a temporal derivative at
>> the 1st level if i
>> want to compare various models. Please correct me if i'm wrong: Temporal
>> derivative
>> would absorb any differences in Onset latencies and so the model fit (and
>> hence PE)would
>> then be dependent only on height and shape of the response. So would you
>> recommend the
>> use of temp. derivatives considering i'm comparing models?
>> Thanks!
>> -Vishwadeep Ahluwalia
>>
>
>
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> Stephen M. Smith, Professor of Biomedical Engineering
> Associate Director, Oxford University FMRIB Centre
>
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