[Mne_analysis] permutation_cluster_test precision

[Alexandre Gramfort]

        External Email - Use Caution        

hi Pieter,

you can pass an explicit threshold rather than use None.

the higher the threshold you more you will be sensitive only
to stronger effects.

HTH
Alex


On Mon, Mar 23, 2020 at 4:41 PM Pieter Huycke <Pieter.Huycke at ugent.be>
wrote:

>         External Email - Use Caution
>
> Dear MNE community,
>
>
>
> I have been using the function *mne.stats.permutation_cluster_test
> <https://mne.tools/stable/generated/mne.stats.permutation_cluster_test.html>
> *as a statistical test to compare clusters in time-frequency power
> estimates between conditions.
>
> Then, I plot the clusters that survived the cluster correction on top of
> the original data, in line with the docs.
>
>
>
> The results make sense, but I have the idea that the cluster is quite
> ‘spread’.
>
> Specifically, the surviving cluster spans multiple frequency bands, and
> extends pretty far in time.
>
> Is there a way to make the resulting cluster more restricted, both in the
> time- and frequency domain?
>
> I can, for example, now mask the resulting image and only keep the
> resulting, more significant ‘blobs’, but this is of course not as clean as
> an algorithm that outputs these blobs without extra steps.
>
>
>
> Perhaps relevant: the parameters I used so far (with d1 being the data in
> condition 1)
>
> *mne.stats.permutation_cluster_test([d1, d2],*
>
> *                                                         n_permutations =
> 1000,*
>
> *                                                         step_down_p    =
> 0.05,*
>
> *                                                         threshold
>      = None, *
>
> *                                                         out_type
>      = "indices",*
>
> *                                                         verbose
>        = True)*
>
>
>
> Thank you,
>
>
>
> Kind regards,
>
>
>
> Pieter
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