Redefine Epochs based on different events

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  Dear MNE experts,

My experiment contains two cues in each trial with a variable delay in
between, I defined each condition base on cue and target cue with
mne.define_target_events. Now my '0' in time is related to the first cue.
How I can redefine my epochs based on the target cue (using the time lag
between the two) so that the time '0' correspond to the appearance of the
target cue on each trial? Is there a function similar to ft_redefinetrial ?

Thanks
Edoardo
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hi,

this is no straightforward equivalent to ft_redefinetrial in mne-python as
this stage.

if you keep the stim channel in the epochs you have the information to do
this.

someone with a clearer idea of the use case can maybe share some code.

I never had to do this myself

Alex

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I can do it manually: getting the data, cut every trial based on the time
lags (all trials same length) and redefine the time axis with epochs.times
, Is there a way to put back the data in the epoch object or create another
one where an array (events,channels,time_points) can be passed? epochs.data
does not work

Thanks

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A similar question came up just a few weeks ago on the mailing list, but it involved baselining epochs. See this thread:

https://mail.nmr.mgh.harvard.edu/pipermail//mne_analysis/2020-March/006551.html

-- dan
Daniel McCloy
https://dan.mccloy.info
Research Scientist
Institute for Learning and Brain Sciences
University of Washington

??? Original Message ???

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Hi Edoardo,

With define_target_events, you can use a negative value in tmin to detect
targets that were preceded within some time window by a cue. If I'm
remembering correctly, the target cue would be reference_id, the initial
cue would be the target_id, tmin would be the maximum lag between the two
(e.g., -3.0 if your variable delay can be up to 3 seconds), and tmax would
be 0. You would want to look at both the original events and new_events
ndarrays to be sure that new_events contains only the targets of interest.

Hope this helps,

Jon