Splitting epoch data

Support & Discussions
1
  • MNE version:1.9
  • operating system: macOS 15

I have managed to read my EEG data with mne.io.read_raw_egi, managed to setup the montage with raw_data_t1.set_montage. From talking to the PI, it is my understanding that the recording is broken into an initial setup, then the recording starts (denoted by DIN1), then a transition of some sort happens during which the recording is still going on and then the second part of the experiment begins (denoted by DIN2). When I create the epochs I do it using 1 second based events per the PI instructions -which I have done with mne.make_fixed_length_events. The PI now wants the epochs based on the times the experiment was running - say DIN1 to about 3 minutes (180 seconds) and DIN2 to the end basically skipping the gap while some transition was going on. What is the best way to achieve this? I was thinking you can create raw objects based on the two events an then create the epochs -which seems cumbersome, or create the epochs and then split the data somehow. Any ideas?

	input_fname_t1 = data_path + t1_file

	# Load the raw data files 
	raw_data_t1 = mne.io.read_raw_egi(input_fname_t1, eog=None, misc=None, include=None, exclude=None, preload=True, channel_naming='E%d', events_as_annotations=True, verbose=None)
	     						   	     						   	
    t1_DIN1 = mne.find_events(raw_data_t1, stim_channel='DIN1', output='onset')
	t1_DIN2 = mne.find_events(raw_data_t1, stim_channel='DIN2', output='onset')

    raw_data_t1.set_montage(montage, match_alias=True, match_case=False, on_missing='warn') 

    epoch_events = mne.make_fixed_length_events(raw_data_t1, id=1, start=0, stop=None, duration=1.0, first_samp=True)

    epoch_t1 = mne.Epochs(raw_data_t1_DIN1, events=epoch_events, event_id=None, tmin=0, tmax=1, baseline=(None, None), picks=None, preload=True, reject=None, flat=None, proj=True, decim=1, reject_tmin=None, reject_tmax=None, detrend=None, on_missing='raise', reject_by_annotation=False, metadata=None, event_repeated='error', verbose=None)

Thanks

2

btw I tried doing something like …

t1_onset_DIN1 = t1_DIN1[0][0]/1000
print(f"Onset for t1_DIN1: {t1_onset_DIN1}")

test = epoch_t1[round(t1_onset_DIN1):180]

My thinking is this would go from the onset on DN1 (aprox 16 seconds into the recording to the 3 minute mark, but I am unsure if this is indeed what I need to do -i.e. all events in the epoch between DN1 and the 180 seconds mark.