Hi everyone, I’m searching for some input in the following matter: The study I’m working on is using a paradigm with spoken sentences wich have two signalwords (the triggers). I’m epoching and averaging each trigger seperately so I’m missing a timeperiod to use for baseline correction in front of …

Just wannan update, I found the answer here applying baseline extracted from another epoched object

I would simply create epochs with a pre-stimulus period that reaches back to the baseline you want to use, then use this baseline period (not the entire pre-stimulus period!) for baseline correction, and then crop the epochs to the time period you actually want to analyze.

Thank you very much! I didn’t realise there is a crop method for epochs. There is no fixed time between the first and the second trigger, but I think it’s manageable to find a way to set the baseline before the first trigger. Best wishes, Leoni

[image] LeLoewenherz: There is no fixed time between the first and the second trigger, but I think it’s manageable to find a way to set the baseline before the first trigger. Oh, this is a non-trivial issue then, as MNE expects the baseline period to be the same across epochs, and all epochs …

Ah yes, I know. It would be a little bit of an ugly solution, but I just thought I will be able to find a baseline period that works for all trials. [image] richard: Do you always have both triggers in all of your epochs / trials? Yes (at least in an ideal scenario). I tried to visualize it …

@richard , did you find a solution for this ? I have a similar situation. I need to baseline correct each of my events from the “fixed” or inter-trial-interval (ITI ) epoch. All events need to be subtracted from the ITI occuring at EACH trial. Apoorva.

I think this got answered during live office hours today. @apoorva6262 can you post the solution you came up with?

epochs = mne.Epochs(raw_tmp, events, tmin= -2.0, tmax=1.0, event_id=event_dict,baseline=None, preload=True) start_stim_data=epochs.get_data() start_stim_times=epochs.times start_data_baseline=mne.baseline.rescale(start_stim_data, start_stim_times, baseline=(-2.0,0), mode='zscore') …

I didn’t test this, but I believe a cleaner solution that is also shorter would be to use Epochs.apply_function(): epochs = mne.Epochs( raw=raw_tmp, events=events, tmin=-2.0, tmax=1.0, event_id=event_dict, baseline=None, preload=True ) epochs.apply_function( fun=mne.baseline.rescale, …

Hi everyone, It’s seem that the problem has been solved by using Epochs.apply_function. However, I didn’t get why apply_function provides baseline period data before the first trigger to epoch 2. Can anyone explain this to me? Thank you, Sherry

I am stuck with the same issue. I need to correct epochs (post-stimulus) from offset to response, but the periods before the epochs of interest are the stimulus itself… I have difficulties understanding how I can do that. According to me it’s not possible to use the periods pre stimulus. …

Baselinecorrection for epoch without baseline period

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Baselinecorrection for epoch without baseline period

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