Hiya Steve
Thanks for all you're help I really appreciate it. I was wondering, if it's
not too much trouble, if you could explain to me why PE is a better measure
for me to use (just in case this comes up in my viva) - I have read a few
bits and pieces (attached) that suggest that PE isn't suitable.
Apologies for taking up so much of your time
Cheers
Hilary
>>> Stephen Smith <[log in to unmask]> 30/11/2009 10:08:31 >>>
Hi - I would say that there is no need to worry about converting to %
signal change in this scenario, and that if anything the PE values are
probably slightly more 'robust'.
Cheers.
On 30 Nov 2009, at 09:55, Hilary Watson wrote:
> Hiya Steve
>
> Thanks so much for getting back to me - I did a little extra
> research after
> emailing last night and it turns out I was looking in an older
> version of
> the FSL manual so I guess point three doesn't really apply.
>
> I just wanted to ask - in light of the fact that my experiments are
> event-related, the design is the same across runs and participants
> (in that
> I make the same contrasts and efficiency of these are quite similar
> although
> timings are not because presentation of items is random and coded to
> subsequent memory accuracy) and I get different things for % signal
> change
> and PEs - would it be incorrect to use parameter estimate values to
> analyse
> my data sets?
>
> Cheers
>
> Hilary
>
>>>> Stephen Smith <[log in to unmask]> 30/11/2009 08:18 >>>
> Hi,
>
> On 29 Nov 2009, at 22:48, Hilary Watson wrote:
>
>> Hi FSL users
>>
>> I have run a total of three fMRI studies for my PhD and I am in the
>> process
>> of re-analysing to write them up.
>>
>> A lot of my work requires extraction of effect sizes in different
>> ROIs and
>> then running stats on these values - generally I have run functional
>> localisers to create functional ROIs and then queried subsequent
>> memory
>> effects across a variety of conditions against an active baseline
>> condition
>> within these.
>>
>> For example
>>
>> objects later remebered - active baseline
>> objects later forgotten - active baseline
>>
>> I orginally extracted the PEs (betas) using Featquery, however I have
>> recently come across some literature that suggests that you
>> shouldn't use PE
>> for your stats, instead you should use % signal change (that said I
>> have
>> seen plenty of recent published papers in decent journals that have
>> used FSL
>> PEs).
>>
>> First question is whether I can stick with PEs for my stats?
>
> Sure - in many cases there's little difference anyway. All data is
> normalised across the entire 4D dataset to have a fixed mean value, so
> as long as comparable designs are used for all subjects there won't be
> much difference. Either choice should be acceptable, and Featquery
> makes it easy to do either, by turning the relevant button on or off.
>
>> Secondly I have also extracted % signal change for my data and have
>> already
>> seen there is not a simple one to one mapping to PE. For two of my
>> data
>> sets the numerical patterns are pretty much the same but for another
>> it only
>> appears to have an effect on one of the contrasts I am interested in
>> looking
>> at. Surely if the baseline used to covert these %s is the same
>> across
>> conditions (within participants) why would these conversions have a
>> greater
>> effect on one contrast? Obviously if it ok for me to use PE then
>> this is so
>> much of an issue
>
> This can happen, for example where a voxel has a fairly different mean
> intensity to the brain as a whole (e.g. if it's on the edge of the
> brain and hence partial-volumed between grey-matter and non-brain
> matter) then PE and %change will be more different. Also, for some
> contrasts the height of that contrast's 'effective regressor' (see our
> NeuroImage paper on design efficiency) can be different from what you
> might expect, particularly for more complex designs and differential
> contrasts.
>
>> Thirdly, I have checked the FSL Feat manual and it says that you
>> cannot use
>> the 'covert PE into % signal change' option in Featquery for event
>> related
>> designs (which all of my experiments are) as this assumes the height
>> of the
>> waveform is 1, which is only appropriate for blocked designs. Is
>> there a
>> simple way to calculate % signal change using my PEs - say a formula
>> and
>> somewhere I can extract a waveform height value?
>
> Are you sure the manual says that? I'm not sure it does but I may be
> missing something. For most event-related designs even the simple
> conversion in Featquery is accurate enough; if you have a concern then
> have a look at J Mumford's website/tool that looks at this issue more
> thoroughly.
>
> Cheers.
>
>
>> I am desperately confused and there is quite a lot riding on this so
>> any
>> help at all will be greatly appreciated. Let me know if you need me
>> to
>> clarify anything.
>>
>> Thanks in advance
>>
>> Hilary
>>
>
>
> ---------------------------------------------------------------------------
> Stephen M. Smith, Professor of Biomedical Engineering
> Associate Director, Oxford University FMRIB Centre
>
> FMRIB, JR Hospital, Headington, Oxford OX3 9DU, UK
> +44 (0) 1865 222726 (fax 222717)
> [log in to unmask] http://www.fmrib.ox.ac.uk/~steve
> ---------------------------------------------------------------------------
>
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Stephen M. Smith, Professor of Biomedical Engineering
Associate Director, Oxford University FMRIB Centre
FMRIB, JR Hospital, Headington, Oxford OX3 9DU, UK
+44 (0) 1865 222726 (fax 222717)
[log in to unmask] http://www.fmrib.ox.ac.uk/~steve
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