- MNE version: e.g. 1.5.0
- operating system: e.g. macOS M2
Hi everyone,
I have a problem with my data analysis. I’m working with two types of events: 2 different auditory events and R-peaks from ECG recordings. The auditory ones are automatically recorded in my data, and I manually detect the R-peaks.
When I check the raw data, everything looks fine—no overlaps. But when I create the epochs, I start seeing overlaps, which doesn’t make sense.
I’ve tried looking at the raw data without any annotations and run the code with the events separately, but nothing’s really helped. Interestingly, the epoch content varies with different tmin and tmax settings. Although there’s a minimum of 300 ms between auditory events, which should prevent overlap with a tmax of 300 ms, the output still differs significantly between tmax settings of 0.2 and 0.3 seconds.
Could someone help me understand why these overlaps are occurring in the epochs and not in the raw data? Any advice would be helpful!
Thank you in advance,
Hande
event_dict = { 'audi_loud':60, 'audi_low':40}
raw.plot(events=events, block=True)
epochs_audi_loud = mne.Epochs(raw, events, tmin=-0.1, tmax=0.2, baseline=(-0.1, 0), event_id=60, event_repeated='drop')
epochs_audi_loud.drop_bad()
epochs_audi_loud.plot_drop_log()
epochs_audi_loud.plot(n_epochs=10, events=events)
# tmax=300 ms (second image)
epochs_audi_loud = mne.Epochs(raw, events, tmin=-0.1, tmax=0.3, baseline=(-0.1, 0), event_id=60, event_repeated='drop')
epochs_audi_loud.drop_bad()
epochs_audi_loud.plot_drop_log()
epochs_audi_loud.plot(n_epochs=10, events=events)