[pymvpa] classification based on individual parameter estimates from FSL

Fri Aug 8 11:50:39 UTC 2014

hi, my thought is that, for instance, if 2 images (i.e. a PE  and its
temporal derivative OR two basis functions)
are associated with the same fMRI event, then it appears that wont be able
to contribute independently to classification
performance becos they basically relate to the same thing.

In my design, for each classification target I have little blocks of 4
trials each ---with trials separated by 2 seconds.
Initially I used the averaged COPE for the mean across the 4 trial blocks,
but this gave few COPES (only 8 as there are 8 mini-blocks per
classification target per subject,

which is little to do within subject classification.

Hence it would be great if I could get more COPES, what am doing at the
moment is to model each trial event within each of the blocks (plus its
temporal derivative) so that I can get at least 4 COPES x 8 blocks= 32
COPES per classification target for each subject, which I am hoping it may
be sufficient to carry out kNN or SVM within subject classification.
I am aware it is not possible to fully separate the HRF associated with the
4 trials of each blocks (as ISI is fixed at 2 secs)
but given each of the 4 trials are of the same classification target, I
thought it should be okay.

Of course I could try to get each PE and  its temporal derivative for each
of the 4 trials of each block which would give me
64 betas per class per subject....but I am concerned about the independence
issue outlined above

any thoughts or suggestions welcome

thanks!
ds

On Fri, Aug 8, 2014 at 11:49 AM, Meng Liang <meng.liang at hotmail.co.uk>
wrote:

> Hi David,
>
> In your case with contrasts defined as 1000, 0100, etc, the PEs and the
> corresponding COPEs should be the same, so it should not make any
> difference either using PEs or COPEs. But I don't really understand why you
> say the PEs would not be independent. Can you explain it a bit more?
>
> Best,
> Meng
>
> ------------------------------
> Date: Tue, 5 Aug 2014 16:40:39 +0100
> From: d.soto.b at gmail.com
> To: pkg-exppsy-pymvpa at lists.alioth.debian.org
> Subject: Re: [pymvpa] classification based on individual parameter
> estimates from FSL
>
>
> Hi Michael (and all), just a quick clarification on your previous response
> to my query relating classification based on individual parameter estimates
> (PEs) - you mentioned  I could use the PEs associated with the temporal
> derivative or even the PEs associated with a set of basis
> functions....however I wonder that this PEs would not be  independent (as
> would be PEs obtained from different runs)
> ....would it be okay to use those PEs anyways?
>
> A second related thing is that I have not been using the PEs  exactly but
> the Contrast of PEs (i.e. COPES in FSL)
> associated with each EV- I have 16 EVs (8 per class) and hence obtained
> COPES such that
> 1000
> 0100
> 0010
> 0001
> etc
>
> I dont see why it would make any difference to work wit COPEs rather than
> PEs, except that only with the later I could boost my dataset by using the
> temporal derivatives or basis functions....
>
> cheers
> ds
>
>
>
> On Fri, Jul 4, 2014 at 2:33 PM, Michael Hanke <mih at debian.org> wrote:
>
> Hi,
>
> On Tue, Jul 01, 2014 at 12:25:40AM +0100, David Soto wrote:
> > Hi Michael, indeed ..well done for germany today! :).
> > Thanks for the reply and the suggestion on KNN
> > I should have been  more clear that for each subject I have the
> > following *block
> > *sequences
> > ababbaabbaabbaba in TASK 1
> > ababbaabbaabbaba in TASK 2
> >
> > this explains that I have  8 a-betas and 8 b-betas for each task
> > AND for each subject..so if i concatenate & normalize all the beta data
> > across subjects I will have 8 x 19 (subjects)= 152 beta images for class
> a
> > and the same for class b
>
> Ah, I guess you model each task with two regressors (hrf + derivative?).
> You can also use a basis function set and get even more betas...
> >
> > then could I use SVM searchlight trained to discriminate a from b in
>  task1
> > betas and tested in the task2 betas?
>
> yes, no problem.
>
> Cheers,
>
> Michael
>
> PS: Off to enjoy the quarter finals ... ;-)
>
>
> --
> Michael Hanke
> http://mih.voxindeserto.de
>
> _______________________________________________
> Pkg-ExpPsy-PyMVPA mailing list
> Pkg-ExpPsy-PyMVPA at lists.alioth.debian.org
> http://lists.alioth.debian.org/cgi-bin/mailman/listinfo/pkg-exppsy-pymvpa
>
>
>
>
> --
> http://www1.imperial.ac.uk/medicine/people/d.soto/
>
> _______________________________________________ Pkg-ExpPsy-PyMVPA mailing
> list Pkg-ExpPsy-PyMVPA at lists.alioth.debian.org
> http://lists.alioth.debian.org/cgi-bin/mailman/listinfo/pkg-exppsy-pymvpa
>
> _______________________________________________
> Pkg-ExpPsy-PyMVPA mailing list
> Pkg-ExpPsy-PyMVPA at lists.alioth.debian.org
> http://lists.alioth.debian.org/cgi-bin/mailman/listinfo/pkg-exppsy-pymvpa
>

-- 
http://www1.imperial.ac.uk/medicine/people/d.soto/
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://lists.alioth.debian.org/pipermail/pkg-exppsy-pymvpa/attachments/20140808/c7882c48/attachment.html>