[Mne_analysis] permutation cluster analysis only shows significant results on right hemisphere

Alexandre Gramfort alexandre.gramfort at telecom-paristech.fr
Tue Sep 9 05:41:32 EDT 2014
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hi,

as denis suggested I would give a try to step_down_p.
Non-parametric cluster stats tend to be dominated by strongest effect
which you can sequentially exclude using the so called "step-down" procedure.

Alex

On Tue, Sep 9, 2014 at 1:05 AM, Denis-Alexander Engemann
<denis.engemann at gmail.com> wrote:
> Hi Xing,
>
> the probem is that the two hemispheres don't share any connections as
> defined by the spatial connectivity matrix.
> under favorable circumstances you might discover two clusters, one in each
> hemisphere,  which, functionally, belong togethe.
> often this is not the case though.
> sometimes using the `step_down_p` paremter can help which might lead to
> detecting the second cluster.
> separate tests for each hemisphere are possible, but I fear you will then
> need to apply e.g. a bonferroni correction.
> you can only test one hemisphere like that:
>
> http://martinos.org/mne/stable/auto_examples/stats/plot_cluster_stats_spatio_temporal_repeated_measures_anova.html
>
> HTH,
> Denis
>
>
>
>
> 2014-09-08 20:07 GMT+02:00 Xing Tian <xt235 at nyu.edu>:
>>
>> Can anyone who is familiar with permutation cluster analysis help me on
>> this?
>> I used 'permutation_cluster_1samp_test' in MNE python on my data and
>> only the right hemisphere showed significant results. Is it possible
>> that the effects on right hemisphere is so strong that the weaker
>> effects on the left was washed out by the permutation significant test?
>> Is so, can I run the permutation cluster analysis for each hemisphere
>> separately?
>>
>> Thanks,
>> Xing
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