[Mne_analysis] Unbalanced number of trials between individuals: problem in sources

[Denis-Alexander Engemann]

I think there is actually no strong reason for that. Maybe some
unintentionally copied line.

On Thu, Mar 3, 2016 at 5:02 PM, Laetitia Grabot <laetitia.grabot at gmail.com>
wrote:

> Ok, thanks, I was still applying the old advice of equalizing epochs
> between conditions! But so, why in certain statistical examples of the
> website, you're still equalizing conditions (like in the Reapeated-measures
> ANOVA in sources)?
>
> 2016-03-03 16:43 GMT+01:00 Denis-Alexander Engemann <
> denis.engemann at gmail.com>:
>
>> Yes that's the idea. Amplitudes of the inverse solution are scaled by the
>> number of trials (.nave). This should work as an heuristic unless you
>> compare rare to frequent events (e.g. oddball).
>> Hope this helps.
>>
>> On Thu, Mar 3, 2016 at 4:38 PM, Laetitia Grabot <
>> laetitia.grabot at gmail.com> wrote:
>>
>>> So does that mean that we need not to equalize epochs between conditions
>>> (within one subject)?
>>>
>>> 2016-03-03 16:23 GMT+01:00 Denis-Alexander Engemann <
>>> denis.engemann at gmail.com>:
>>>
>>>> Hi Laetitia,
>>>>
>>>> I I'm understanding you correctly this should not be an issue for
>>>> evoked data as long as you are using the .average method that will tell the
>>>> inverse routines how to scale the data via its .nave attribute.
>>>> Did you have any particular problems?
>>>>
>>>> Cheers,
>>>> Denis
>>>>
>>>> On Thu, Mar 3, 2016 at 3:09 PM, Laetitia Grabot <
>>>> laetitia.grabot at gmail.com> wrote:
>>>>
>>>>> Dear MNE-users,
>>>>>
>>>>> I am aware of the fact that when contrasting two conditions, the
>>>>> epochs within each condition should be equalized before reconstructing in
>>>>> source space, otherwise the SNR would be different between the two
>>>>> conditions. That also means that if two subjects have a different number of
>>>>> epochs, the SNR of each subject will be different. It is often the case
>>>>> that the number of epochs doubled between subjects (50 vs. 100) so I guess
>>>>> that it is an issue when looking at group averaged stc for instance.
>>>>> A possible solution would be to normalize the stc to correct for the
>>>>> number of trials. What do you think of that? What would be the proper
>>>>> normalization?
>>>>>
>>>>> Thanks,
>>>>> Best,
>>>>> Laetitia G.
>>>>>
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