# non uniform epochs

**URL:** <https://mne.discourse.group/t/non-uniform-epochs/6598>\
**Category:** Support & Discussions\
**Tags:** preprocessing, eeg\
**Created:** [March 27, 2023, 4:33am UTC](https://mne.discourse.group/t/non-uniform-epochs/6598 "2023-03-27T04:33:58Z")\
**Posts on this page:** 3\
**Page:** 1

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**Author:** ![poorva31](https://yyz2.discourse-cdn.com/free1/user_avatar/mne.discourse.group/poorva31/32/738_2.png) [@poorva31](https://mne.discourse.group/u/poorva31)\
**Post date:** [March 27, 2023, 4:33am UTC](https://mne.discourse.group/t/non-uniform-epochs/6598/1 "2023-03-27T04:33:58Z")

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- MNE version: 1.2.3
- operating system: Windows 11

I am currently working on an EEG dataset with 5 EEG channels, 2 EOG channels, and 1 ECG.

I am creating non-uniform events based on each trial’s start and end times for the task. I wanted to create epochs with the same start and end times as events. Is there a way I can do this? Each signal has around 530 trials. My main goal is then to reject these bad epochs (i.e., trials)

Thanks in advance.

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**Author:** ![sappelhoff](https://yyz2.discourse-cdn.com/free1/user_avatar/mne.discourse.group/sappelhoff/32/3276_2.png) [@sappelhoff](https://mne.discourse.group/u/sappelhoff)\
**Post date:** [March 28, 2023, 8:35am UTC](https://mne.discourse.group/t/non-uniform-epochs/6598/2 "2023-03-28T08:35:26Z")

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As far as I know there is currently no way in MNE-Python to have an [Epochs object](https://mne.tools/stable/generated/mne.Epochs.html#mne-epochs) where individual epochs have different lengths (time dimension).

I am not 100% sure, but I think FieldTrip does support this.

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**Author:** ![cbrnr](https://yyz2.discourse-cdn.com/free1/user_avatar/mne.discourse.group/cbrnr/32/1409_2.png) [@cbrnr](https://mne.discourse.group/u/cbrnr)\
**Post date:** [March 28, 2023, 9:15am UTC](https://mne.discourse.group/t/non-uniform-epochs/6598/3 "2023-03-28T09:15:06Z")

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You don’t need to create non-uniform epochs for this use case. I would create annotations starting with the word “bad” based on your stop and start events. That way, these segments will be ignored by most MNE functions.