[Mne_analysis] Epoching with stimulus in the first sample of raw data

Mainak Jas mainakjas at gmail.com
Wed Aug 24 15:58:57 EDT 2016
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Hi Leonardo,

Since find_events returns to you a plain numpy array, a simple fix could be
to just add add your event manually to the array. Something like:

pick_stim = mne.pick_channels(raw.info['ch_names'], ['STIM'])
stim_data = raw[pick_stim][0][0]
session_id = stim_data[0]
events = np.vstack(([raw.first_samp, 0, session_id], events))

It's a bit hackish but should do your job.

Mainak




On Thu, Aug 25, 2016 at 12:43 AM, Leonardo Barbosa <lsbarbosa at gmail.com>
wrote:

> Dear MNErs,
>
> This is my first project trying to use MNE in "real" data, and I'm trying
> to move datasets from eeglab / fieldtrip to MNE
>
> I run into some trouble trying to epoch the data.
>
> The data is a continuous dataset with different sessions.
> I have a STIM channel with numbers 1 and 2 for each type of session.
> *One pulse every 2 min starting at the first sample*.
> I then exported the data using
>
> fieldtrip2fiff
>
> making sure the channel's unit and kind were correctly set.
>
> However, after importing the raw, when I tried to find the events to do
> the epoching using this function
>
> events = mne.find_events(raw, stim_channel='STIM')
>
> MNE droped the first event saying
>
> Removing orphaned offset at the beginning of the file.
>
> I looked at the _find_events code and realized that the event pulse
> should have at least one empty sample before it.
> I tried to change the consecutive parameter to no avail.
>
> What would be the best way to keep the first event / session?
>
> I imagine it is rare to have a stimulus already in the first sample of a
> continuous data, but I would like to avoid losing the first session of each
> subject or recoding the stimulus at the EEGLAB/fieldtrip if possible.
>
> Thank you,
> Leonardo
>
>
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