[Mne_analysis] Reliability of a source

[Alexandre Gramfort]

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Hi Irina,

I am sure other MNE users have suggestions on this but I can answer with
what
MNE-Python can offer at this stage which is to do: FDR correction on a
paired t-test
or spatio-temporal cluster level stats in source space.

Alex



On Sun, Feb 9, 2020 at 1:36 PM Irina Anurova <anurova.irina at gmail.com>
wrote:

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>
> Hi Alex,
> Thank you very much for your reply,
> I meant a group averaged evoked response (ERP/ERF) to auditory stimulation
> (when subjects are performing an active task). The individual dSPMs were
> morphed beforehand to a standard template. The group average shows strong
> activation within the auditory cortex, and weaker activation in another
> region of interest. The second region can be seen at a lower threshold,
> that can be adjusted using the interactive scale. So, I would like to find
> out whether this second activation is significant. Is there an objective
> way to set up the threshold for the significant activation (versus
> baseline)? Is it necessary to perform the FDR correction to the group
> averaged evoked responses (like we do for fMRI data)?
> Thank you very much for your help!
> Irina.
>
> On Sat, Feb 8, 2020 at 3:29 PM Alexandre Gramfort <
> alexandre.gramfort at inria.fr> wrote:
>
>>         External Email - Use Caution
>>
>> hi Irina,
>>
>> you should give us for details. What conditions / statistical test you
>> have in mind?
>> is it at the group level ?
>>
>> you can find on the mne.tools website some examples eg using
>> spatio-temporal cluster level stats.
>>
>> HTH
>> Alex
>>
>>
>> On Tue, Feb 4, 2020 at 2:05 PM Irina Anurova <anurova.irina at gmail.com>
>> wrote:
>> >
>> >         External Email - Use Caution
>> >
>> > Dear friends,
>> > I would like to proof reliability of a source reconstructed with dSPM.
>> How to apply correction for multiple comparison (FDR or cluster-size) at
>> the source level? How to setup a threshold for significant activation?
>> > Thank you very much for your help,
>> > Irina
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