[Mne_analysis] need help to plot EEG topomaps with mne
jeanremi.king at gmail.com
Tue Jun 21 01:49:32 EDT 2016
it's generally best to follow up your questions on the mailing list so that
others can checkout the archives.
To make an Evoked object you should be able to do:
from mne import EvokedArray, create_info
sampling_freq = 128
info = create_info(n_channels, sampling_freq, 'eeg')
evoked = EvokedArray(your_data_array, info=info, tmin=0.)
Then you can make a montage and attach it to the evoked object:
from mne.channels import Montage
kind = 2 # means eeg channels
montage = Montage(position_xyz, info, kind=2, range(n_channels))
You can then use the plotting function that I described in the previous
email to plot in 3D. Note that MNE has a wider spectrum of functions for 2D
plottings (have a look at evoked.plot(), plot_topo(), plot_topomap(),
plot_*() methods). Tu use them you'll need to make a 2D layout
Hope that helps,
PS: yes I am ;)
Hi Jean-Rémi (Are you French?)
> Thanks for your help.
> I've some difficulties with the mne.read_evokeds function. At the moment,
> I have a grand average data 19(channels) x 300 (datapoints) numpy array and
> a custom montage instance from the mne.channels.Montage map (see attached).
> How could I proceed to (i) generate a read_evokeds() object, and (ii)
> plot a 3D map in a specific time window...
On 20 June 2016 at 10:13, JR KING <jeanremi.king at gmail.com> wrote:
> Hi Mathieu,
> to complete Jaakko's answer, you can plot 3D EEG projection using mne.viz
> import.evoked_field. For example:
> import os.path as op
> import mne
> from mne.forward import make_field_map
> from mne.viz import plot_evoked_field
> # get data
> data_path = mne.datasets.sample.data_path()
> subjects_dir = data_path + '/subjects'
> trans_fname = op.join(data_path, 'MEG', 'sample',
> fname = op.join(data_path, 'MEG', 'sample', 'sample_audvis-ave.fif')
> evoked = mne.read_evokeds(fname, baseline=(None, 0), proj=True)
> # select eeg channels only
> evoked.pick_types(eeg=True, meg=False)
> # plot field maps
> maps = make_field_map(evoked, trans=trans_fname, subjects_dir=subjects_dir,
> subject='sample', n_jobs=-1, meg_surf='head')
> plot_evoked_field(evoked, maps, time=.1)
> Hope that helps,
> On 20 June 2016 at 09:00, Jaakko Leppäkangas <jaeilepp at student.jyu.fi>
>> Hi Mathieu,
>> currently there is no way to project to 3d.
>> For the second point you could use a montage when reading the data. The
>> readers for EEG data have a montage parameter that you could use to set the
>> channel locations (see for example
>> In your case, since you have some custom locations, one option would be to
>> manually add entries for 'OL' and 'OR' to the standard_1020.elc file, if
>> you know their locations.
>> On 18 June 2016 at 20:56, Servant Mathieu <servant.mathieu at gmail.com>
>>> I'm new to mne, and would like to compute some topographic voltage maps
>>> from my EEG grand-averaged data.
>>> I have two specific questions:
>>> (i) The plot_topomap function plots 2D maps. Is there a way to plot 3D
>>> (ii) My data_ is a 19 (electrodes) x 300 (datapoints) numpy array.
>>> Sampling rate was 250 Hz, and the 300 datapoints correspond to a -200 1000
>>> ms epoch (0 being the stimulus-locking event).
>>> -Is there a simple way to plot topographies at say, 300 ms after
>>> stimulus onset, or topographies over the average of a given time window
>>> (300-500ms after stimulus onset)?
>>> -I need to provide the (x,y) coordinates for each EEG channel. My
>>> channels are:
>>> electrodes =
>>> These electrodes are standard international 10/20 System sites, except
>>> OL (halfway between 01 and T5) and OL (halfway between 02 and T6). Given
>>> these locations, which coordinate array should I provide to the
>>> plot_topomap function ?
>>> Thanks for your help!
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