[Mne_analysis] Making Functional labels from spatial temporal clustering
董群喜
dongqunxi at gmail.com
Fri Aug 12 10:53:42 EDT 2016
Thanks for your patience, nice explanation!
Best wishes,
Qunxi Dong
2016-08-12 16:10 GMT+02:00 Marijn van Vliet <w.m.vanvliet at gmail.com>:
> Dear Qunxi,
>
> if I understand correctly, then the permutation cluster tests in MNE may
> not be suitable for what you want to do.
>
> Consider this figure:
> http://imgur.com/a/E8ais
>
> This is the time course for a single dipole on the brain (simulated data).
> If I understand your goal correctly, you would like to include this vertex
> as part of a ROI, because it has increased activity after the stimulus has
> been shown.
>
> A cluster test as implemented in MNE would determine whether any
> post-stimulus samples are higher than pre-stimulus samples *in a pairwise
> fashion*. Thus, whether pre-stimulus sample 1 is higher than
> post-stimulus sample 1, pre-stimulus sample 2 is higher than post-stimulus
> sample 2, etc.
>
> What you most likely want instead is estimate some confidence interval for
> the pre-stimulus values in general (red dashed line in the figure) and then
> determine, given the post-interval data, whether to include the vertex yes
> or no.
>
> It is not surprising that the cluster test marked the entire brain as ROI,
> because it is very likely for the time course of a vertex to be higher than
> the pre-stimulus at some point, even if the stimulus didn't activate the
> vertex at all (and the pre-stimulus and post-stimulus data were drawn from
> the same distribution).
>
> At this point, a thresholding operation that only passes vertices for
> which the activation surpasses the pre-stimulus activity for a minimum
> amount of time makes sense. However, you would need to be careful to set it
> to a sensible value.
>
> I think you'll need to implement the procedure to mark the vertices to
> include yourself. Then, you can use the stc_to_label function to cut it up
> in spatially connected ROIs.
>
> At any rate, I think the result of "showing a stimulus activates the
> entire brain" actually makes sense. Showing a stimulus would do that,
> although not all parts in the equal amounts.
>
> That's all the help I can give you. Good luck with your study. May your
> p-values be significant! :-)
>
> Kind regards,
> Marijn.
>
> On Fri, Aug 12, 2016 at 2:24 PM 董群喜 <dongqunxi at gmail.com> wrote:
>
>> Dear Marijin,
>>
>> OK. We have the MEG data related with visual task. By comparing data of
>> prestimulus and poststimulus, we want to find focal functional labels
>> related with visual cognitive process.
>> And then we want to make network analysis between the identified regions
>> of interest.
>>
>>
>> Best wishes,
>> Qunxi Dong
>>
>> 2016-08-12 13:17 GMT+02:00 Marijn van Vliet <w.m.vanvliet at gmail.com>:
>>
>>> if you threshold the data in the STC, it means you are thresholding
>>> based on the length of the cluster in time. So if you threshold by a value
>>> of 190, any vertices that survive are significantly different for at least
>>> 190 consecutive samples.
>>>
>>> I'm sorry, but I'm unable to follow your logic. What do you mean by
>>> *meaningful* ROIs?
>>>
>>> Right now, it sounds to me like: if we manipulate the data so and so we
>>> get the picture we want. Now we want a justification for our manipulation.
>>> But that is probably not what you meant.
>>>
>>> Maybe I can be of more help if you explain a bit more about your data
>>> and what effect you are trying to visualize.
>>>
>>> On Fri, Aug 12, 2016 at 1:34 PM 董群喜 <dongqunxi at gmail.com> wrote:
>>>
>>>> Dear Marijin,
>>>>
>>>> We prefer to get focal clusters attributed to the stimulus, and if we
>>>> use 95 percentile as the threshold to shrink the clusters, it can show some
>>>> meaningful ROIs. But we do not know how to explain the threshold (such
>>>> as 190).
>>>>
>>>> Best wishes,
>>>> Qunxi Dong
>>>>
>>>> 2016-08-12 11:54 GMT+02:00 Marijn van Vliet <w.m.vanvliet at gmail.com>:
>>>>
>>>>> Well, if the cluster permutation test returns clusters that span the
>>>>> entire brain, then that's the way it is. The signals are different pre- and
>>>>> post-stimulus all across the brain.
>>>>>
>>>>> On Fri, Aug 12, 2016 at 10:14 AM 董群喜 <dongqunxi at gmail.com> wrote:
>>>>>
>>>>>> Dear Marijin,
>>>>>>
>>>>>> Thanks for your response.
>>>>>> I need to introduce how I use 2sample spatial clustering on our data:
>>>>>> I make groups of prestimulus data and poststimulus data, and then the
>>>>>> comparisons are made
>>>>>> between the two groups data. I want to identify clusters significant
>>>>>> to the stimulus.
>>>>>> The p_value for f_threshold is 0.001, p_value for comparisons
>>>>>> corrected is 0.001.
>>>>>> I get two significant clusters only, that is one cluster per
>>>>>> hemisphere.
>>>>>> When I ploted as you said, the two clusters nearly cover the whole
>>>>>> Brain. For your convenience,
>>>>>> I provide one STC file for your testing, and the plot of the
>>>>>> clusters.
>>>>>>
>>>>>> Best wishes,
>>>>>> Qunxi Dong
>>>>>>
>>>>>> Best wishes,
>>>>>> Qunxi Dong
>>>>>>
>>>>>> 2016-08-12 8:09 GMT+02:00 董群喜 <dongqunxi at gmail.com>:
>>>>>>
>>>>>>> Dear Marijin,
>>>>>>>
>>>>>>> Thanks for your response.
>>>>>>> I need to introduce how I use 2sample spatial clustering on our data:
>>>>>>> I make groups of prestimulus data and poststimulus data, and then
>>>>>>> the comparisons are made
>>>>>>> between the two groups data. I want to identify clusters significant
>>>>>>> to the stimulus.
>>>>>>> The p_value for f_threshold is 0.001, p_value for comparisons
>>>>>>> corrected is 0.001.
>>>>>>> I get two significant clusters only, that is one cluster per
>>>>>>> hemisphere.
>>>>>>> When I ploted as you said, the two clusters nearly cover the whole
>>>>>>> Brain. For your convenience,
>>>>>>> I provide one STC file for your testing, and the plot of the
>>>>>>> clusters.
>>>>>>>
>>>>>>> Best wishes,
>>>>>>> Qunxi Dong
>>>>>>>
>>>>>>> 2016-08-11 20:05 GMT+02:00 Marijn van Vliet <w.m.vanvliet at gmail.com>
>>>>>>> :
>>>>>>>
>>>>>>>> Dear Qunxi,
>>>>>>>>
>>>>>>>> the output of `summarize_clusters_stc’ is a bit poorly documented
>>>>>>>> (I’ve opened a pull request for it to be fixed in future versions of MNE).
>>>>>>>>
>>>>>>>> The output is as follows:
>>>>>>>>
>>>>>>>> out : instance of SourceEstimate
>>>>>>>> A summary of the clusters. The first time point in this
>>>>>>>> SourceEstimate
>>>>>>>> object is the summation of all the clusters. Subsequent
>>>>>>>> time points
>>>>>>>> contain each individual cluster. The magniture of the
>>>>>>>> activity
>>>>>>>> corresponds to the length the cluster spans in time (in
>>>>>>>> samples).
>>>>>>>>
>>>>>>>> So it is perfectly reasonable to create labels from the clusters.
>>>>>>>> However, you do not need to take the mean across the time points or
>>>>>>>> anything like that. Also, thresholding does not do what you want. Instead,
>>>>>>>> this should work:
>>>>>>>>
>>>>>>>> stc = summarize_clusters_stc(clu, p_thre, tstep=tstep,
>>>>>>>> tmin=tmin,
>>>>>>>> vertices=fsave_vertices,
>>>>>>>> subject='fsaverage')
>>>>>>>> lh_labels, rh_labels = mne.stc_to_label(stc, src=src, smooth=True,
>>>>>>>> subjects_dir=subjects_dir,
>>>>>>>> connected=True)
>>>>>>>>
>>>>>>>> The labels look bigger than the clusters as visualised with
>>>>>>>> stc.plot(…), because the plotting functions applies its own thesholding.
>>>>>>>> Try to visualise it without any thresholding by doing this:
>>>>>>>>
>>>>>>>> b = stc.plot(hemi=‘both’, subject=subject, subject_dir=subject_dir)
>>>>>>>> b.scale_data_colormap(0, stc.data.mean(), stc.data.max(), True)
>>>>>>>>
>>>>>>>> Let me know if you have further questions.
>>>>>>>>
>>>>>>>> Marijn.
>>>>>>>>
>>>>>>>> --
>>>>>>>> Marijn van Vliet
>>>>>>>> w.m.vanvliet at gmail.com
>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>> > On 11 Aug 2016, at 19:09, 董群喜 <dongqunxi at gmail.com> wrote:
>>>>>>>> >
>>>>>>>> > Dear all,
>>>>>>>> >
>>>>>>>> > For you easier understanding my problem, I made a gist and paste
>>>>>>>> the critical codes in the following link:
>>>>>>>> > https://gist.github.com/dongqunxi/daca753366c592927ff789c03aa6ed
>>>>>>>> 0b
>>>>>>>> > Thanks, looking forward to your response.
>>>>>>>> >
>>>>>>>> > Best wishes,
>>>>>>>> > Qunxi Dong
>>>>>>>> >
>>>>>>>> > 2016-08-11 17:52 GMT+02:00 董群喜 <dongqunxi at gmail.com>:
>>>>>>>> > Dear All,
>>>>>>>> >
>>>>>>>> > Recently, I am trying to make functional labels from a group of
>>>>>>>> subjects.
>>>>>>>> > I first refer the 2sample clustering scripts. I get some
>>>>>>>> significant clusters and derive the source estimates.
>>>>>>>> > if I apply 'stc_to_label' to make functional labels directly, the
>>>>>>>> size of the functional labels is too large.
>>>>>>>> > I also try to use percentile of 95 to restrict the size, but I
>>>>>>>> can not explain what the actual meaning
>>>>>>>> > of this threshold.
>>>>>>>> > Can someone give me some tips?
>>>>>>>> > Thanks a lot!
>>>>>>>> >
>>>>>>>> > Best wishes,
>>>>>>>> > Qunxi Dong
>>>>>>>> >
>>>>>>>> > _______________________________________________
>>>>>>>> > Mne_analysis mailing list
>>>>>>>> > Mne_analysis at nmr.mgh.harvard.edu
>>>>>>>> > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/mne_analysis
>>>>>>>> >
>>>>>>>> >
>>>>>>>> > The information in this e-mail is intended only for the person to
>>>>>>>> whom it is
>>>>>>>> > addressed. If you believe this e-mail was sent to you in error
>>>>>>>> and the e-mail
>>>>>>>> > contains patient information, please contact the Partners
>>>>>>>> Compliance HelpLine at
>>>>>>>> > http://www.partners.org/complianceline . If the e-mail was sent
>>>>>>>> to you in error
>>>>>>>> > but does not contain patient information, please contact the
>>>>>>>> sender and properly
>>>>>>>> > dispose of the e-mail.
>>>>>>>>
>>>>>>>>
>>>>>>>> _______________________________________________
>>>>>>>> Mne_analysis mailing list
>>>>>>>> Mne_analysis at nmr.mgh.harvard.edu
>>>>>>>> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/mne_analysis
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>> _______________________________________________
>>>>>> Mne_analysis mailing list
>>>>>> Mne_analysis at nmr.mgh.harvard.edu
>>>>>> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/mne_analysis
>>>>>>
>>>>>>
>>>>>> The information in this e-mail is intended only for the person to
>>>>>> whom it is
>>>>>> addressed. If you believe this e-mail was sent to you in error and
>>>>>> the e-mail
>>>>>> contains patient information, please contact the Partners Compliance
>>>>>> HelpLine at
>>>>>> http://www.partners.org/complianceline . If the e-mail was sent to
>>>>>> you in error
>>>>>> but does not contain patient information, please contact the sender
>>>>>> and properly
>>>>>> dispose of the e-mail.
>>>>>>
>>>>> --
>>>>> --
>>>>> Marijn van Vliet
>>>>>
>>>>> w.m.vanvliet at gmail.com
>>>>> marijn.vanvliet at aalto.fi
>>>>>
>>>>> _______________________________________________
>>>>> Mne_analysis mailing list
>>>>> Mne_analysis at nmr.mgh.harvard.edu
>>>>> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/mne_analysis
>>>>>
>>>>>
>>>>> The information in this e-mail is intended only for the person to whom
>>>>> it is
>>>>> addressed. If you believe this e-mail was sent to you in error and the
>>>>> e-mail
>>>>> contains patient information, please contact the Partners Compliance
>>>>> HelpLine at
>>>>> http://www.partners.org/complianceline . If the e-mail was sent to
>>>>> you in error
>>>>> but does not contain patient information, please contact the sender
>>>>> and properly
>>>>> dispose of the e-mail.
>>>>>
>>>>>
>>>> _______________________________________________
>>>> Mne_analysis mailing list
>>>> Mne_analysis at nmr.mgh.harvard.edu
>>>> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/mne_analysis
>>>>
>>>>
>>>> The information in this e-mail is intended only for the person to whom
>>>> it is
>>>> addressed. If you believe this e-mail was sent to you in error and the
>>>> e-mail
>>>> contains patient information, please contact the Partners Compliance
>>>> HelpLine at
>>>> http://www.partners.org/complianceline . If the e-mail was sent to you
>>>> in error
>>>> but does not contain patient information, please contact the sender and
>>>> properly
>>>> dispose of the e-mail.
>>>>
>>> --
>>> --
>>> Marijn van Vliet
>>>
>>> w.m.vanvliet at gmail.com
>>> marijn.vanvliet at aalto.fi
>>>
>>> _______________________________________________
>>> Mne_analysis mailing list
>>> Mne_analysis at nmr.mgh.harvard.edu
>>> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/mne_analysis
>>>
>>>
>>> The information in this e-mail is intended only for the person to whom
>>> it is
>>> addressed. If you believe this e-mail was sent to you in error and the
>>> e-mail
>>> contains patient information, please contact the Partners Compliance
>>> HelpLine at
>>> http://www.partners.org/complianceline . If the e-mail was sent to you
>>> in error
>>> but does not contain patient information, please contact the sender and
>>> properly
>>> dispose of the e-mail.
>>>
>>>
>> _______________________________________________
>> Mne_analysis mailing list
>> Mne_analysis at nmr.mgh.harvard.edu
>> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/mne_analysis
>>
>>
>> The information in this e-mail is intended only for the person to whom it
>> is
>> addressed. If you believe this e-mail was sent to you in error and the
>> e-mail
>> contains patient information, please contact the Partners Compliance
>> HelpLine at
>> http://www.partners.org/complianceline . If the e-mail was sent to you
>> in error
>> but does not contain patient information, please contact the sender and
>> properly
>> dispose of the e-mail.
>>
> --
> --
> Marijn van Vliet
>
> w.m.vanvliet at gmail.com
> marijn.vanvliet at aalto.fi
>
> _______________________________________________
> Mne_analysis mailing list
> Mne_analysis at nmr.mgh.harvard.edu
> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/mne_analysis
>
>
> The information in this e-mail is intended only for the person to whom it
> is
> addressed. If you believe this e-mail was sent to you in error and the
> e-mail
> contains patient information, please contact the Partners Compliance
> HelpLine at
> http://www.partners.org/complianceline . If the e-mail was sent to you in
> error
> but does not contain patient information, please contact the sender and
> properly
> dispose of the e-mail.
>
>
-------------- next part --------------
An HTML attachment was scrubbed...
URL: http://mail.nmr.mgh.harvard.edu/pipermail/mne_analysis/attachments/20160812/435975a3/attachment-0001.html
More information about the Mne_analysis
mailing list