Baseline without .average()

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1

Dear all,

I have epoched data. On these data I apply ICA without baseline and then I apply the baseline.
In the tutorial, for applying baseline correction, I saw : the following line code:

trad_aud = epochs["auditory"].average().apply_baseline(baseline)

Here is my short code:

Epochs = mne.Epochs(RawData_Notched, events = Events_from_annot, tmin = Tmin, tmax = Tmax, baseline = None, preload = True, event_id = {"Stimulus/S  5": 5, "Stimulus/S 10": 10, "Stimulus/S 14": 14})
ICAOnEpochs = mne.preprocessing.ICA(n_components = 30, max_iter = "auto", random_state = 97, method = "picard").fit(Epochs)
ICAOnEpochs.exclude = [0, 1, 2, 3, 4, 5]
Epochs_AfterICA = ICAOnEpochs.apply(Epochs)
Epochs_Baselined = Epochs_AfterICA.apply_baseline(Baseline)

Is it a good way to apply the baseline correction after processing ICA? Do I need to add the .average() method before .apply_baseline() as found in the tutorial?

Thank you all!

Hugues

2

Hello, this looks good to me. The averaging step is only required if you want to create evoked data (ERPs/ERFs). But you can without any problems apply baseline correction to the epochs first and create evokeds at any later time (or never).

Best wishes,
Richard

3

Thank you so much Richard!

Best regards,

Hugues

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