[Mne_analysis] How is the baseline correction calculated?

[Emanuela Liaci]

Hi Jaakko,

thanks for the enlightenment. Yes of course, now I understand the problem.
But then since I have to apply the correction after the averaging, how can
I do it?

Here my code:

epochs_noRef = mne.EpochsArray(ElectrodeArray, info=info,tmin=-0.06)
    # baseline = (-0.06, 0.04)
epochs_Ref,_= mne.io.set_eeg_reference(epochs_noRef, ['TP9', 'TP10'])
evoked=epochs_Ref.average()

thanks a lot for your help,
Emanuela

On Mon, Sep 5, 2016 at 4:44 PM, Emanuela Liaci <emanuela.liaci at gmail.com>
wrote:

> Hi Jaakko,
>
> thanks for the enlightenment. Yes of course, now I understand the problem.
> But then since I have to apply the correction after the emerging, how can I
> do it?
>
> Here my code:
>
> epochs_noRef = mne.EpochsArray(ElectrodeArray, info=info,tmin=-0.06)
>       # baseline = (-0.06, 0.04)
> epochs_Ref,_= mne.io.set_eeg_reference(epochs_noRef, ['TP9', 'TP10'])
> evoked=epochs_Ref.average()
>
> thanks a lot for your help,
> Emanuela
>
> On Mon, Sep 5, 2016 at 4:14 PM, Jaakko Leppäkangas <
> jaeilepp at student.jyu.fi> wrote:
>
>> Hi Emanuela,
>>
>> I assume you do the baselining when constructing the epochs
>> (mne.Epochs(..., baseline=baseline))? It simply subtracts the mean over the
>> baseline period. So the effective lines of code boil down to:
>>
>> mean = np.mean(data[..., imin:imax], axis=-1)[..., None]
>> data -= mean
>>
>> , where the baseline runs from imin to imax. And yes this should be
>> documented better. I'll make the issue to github.
>>
>> -Jaakko
>>
>> On 5 September 2016 at 14:48, Emanuela Liaci <emanuela.liaci at gmail.com>
>> wrote:
>>
>>> Hi,
>>>
>>> I am comparing the evoke data of one subject between my script in Python
>>> with mne package and the script in IGOR pro that my lab used so far.
>>>
>>> I gave the following time interval for baseline correction to both:
>>> baseline = (-0.060, 0.040). I noticed that the values of the average
>>> change: for each electrode there is always the same difference (between
>>> Python and IGOR) across data points.
>>>
>>> How come? Can I have a more detailed explanation of how the baseline
>>> correction is applied?
>>>
>>> Many thanks,
>>> Emanuela Liaci
>>>
>>>
>>>
>>>
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