[Eeglablist] What to do with more than one IC per subject in a cluster

[Makoto Miyakoshi]

Dear Salim,

I don't know any paper for that, but the approach is reasonable. Be
confident.

Makoto

On Sat, Mar 21, 2015 at 4:51 AM, Salim Al-wasity <salim_alwasity at yahoo.com>
wrote:

> Dear Mr. Makoto
> Thanks for your reply.
> Would you recommend a reference paper for the advantages of manual
> pre-selection.
> I read the Nima's paper of measure projection analysis, and he used the
> same dataset form both clustering approaches.
> In my study I am comparing the results of these two approaches to discover
> which one the best for clustering.
>
> Sincerely
> Salim
>
>
>
>
>
>   On Thursday, 19 March 2015, 17:12, Makoto Miyakoshi <mmiyakoshi at ucsd.edu>
> wrote:
>
>
> Dear Salim,
>
> Sorry for slow response.
>
> > for PCA-clustering I removed the noisy ICs and then I preselected ICs
> which are located in the Sensorimotor cortex, after that I created a STUDY
> and used a PCA for clustering and ensured each cluster has at most 2
> components from the same subject to avoid biasing.
>
> Interesting. As long as you choose them by anatomical locations, I believe
> you are fine.
>
> > and Whether these results are comparable to those of MPT?
>
> First you have to check how much overlap between MPT-selected ICs and your
> selections.
>
> MPT is, to my understanding, a 'similarity filter'. Therefore, I expect
> that MPT-selected ICs could be more consistent in the selected measure than
> k-mean clustering (well, you can still tweak the parameters in k-mean
> clustering so that the result is maximally similar to that of MPT).
>
> Sorry it could be confusing that there are two solutions for the
> group-level analysis.
> By the way, before running MPT I recommend you clean the ICs in the
> following way (did I tell this to you before? If so excuse me)
> http://sccn.ucsd.edu/wiki/Backproject_clustered_ICs
>
> Makoto
>
>
>
> On Thu, Feb 26, 2015 at 2:29 AM, Salim Al-wasity <salim_alwasity at yahoo.com
> > wrote:
>
> Dears
> As I understood from the following discussion (
> http://sccn.ucsd.edu/pipermail/eeglablist/2013/006353.html), its not
> recommended to pre-select the components for a PCA-clustering approach?
>
> I am comparing between the ERSP results of using MPT approach and
> PCA-clustering approach. In the first STUDY, I used the MPT to cluster the
> ICs (after removing the noisy ones). and for PCA-clustering I removed the
> noisy ICs and then I preselected ICs which are located in the Sensorimotor
> cortex, after that I created a STUDY and used a PCA for clustering and
> ensured each cluster has at most 2 components from the same subject to
> avoid biasing.
> Is this technique of pre-selecting ICs based on ROI (Region Of Interest)
> prior to PCA-clustering is a good way to avoid biasing?  and Whether these
> results are comparable to those of MPT?
>
> Sincerely
> Salim
>
>
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>
>
> --
> Makoto Miyakoshi
> Swartz Center for Computational Neuroscience
> Institute for Neural Computation, University of California San Diego
>
>
>


-- 
Makoto Miyakoshi
Swartz Center for Computational Neuroscience
Institute for Neural Computation, University of California San Diego
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