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# -*- coding: utf-8 -*-
"""
.. _ex-brain:
===============================
Plotting with ``mne.viz.Brain``
===============================
In this example, we'll show how to use :class:`mne.viz.Brain`.
"""
# Author: Alex Rockhill <aprockhill@mailbox.org>
#
# License: BSD-3-Clause
# %%
# Load data
# ---------
#
# In this example we use the ``sample`` data which is data from a subject
# being presented auditory and visual stimuli to display the functionality
# of :class:`mne.viz.Brain` for plotting data on a brain.
import matplotlib.pyplot as plt
from matplotlib.cm import ScalarMappable
from matplotlib.colors import Normalize
import mne
from mne.datasets import sample
print(__doc__)
data_path = sample.data_path()
subjects_dir = data_path / 'subjects'
sample_dir = data_path / 'MEG' / 'sample'
# %%
# Add source information
# ----------------------
#
# Plot source information.
brain_kwargs = dict(alpha=0.1, background='white', cortex='low_contrast')
brain = mne.viz.Brain('sample', subjects_dir=subjects_dir, **brain_kwargs)
stc = mne.read_source_estimate(sample_dir / 'sample_audvis-meg')
stc.crop(0.09, 0.1)
kwargs = dict(fmin=stc.data.min(), fmax=stc.data.max(), alpha=0.25,
smoothing_steps='nearest', time=stc.times)
brain.add_data(stc.lh_data, hemi='lh', vertices=stc.lh_vertno, **kwargs)
brain.add_data(stc.rh_data, hemi='rh', vertices=stc.rh_vertno, **kwargs)
# %%
# Modify the view of the brain
# ----------------------------
#
# You can adjust the view of the brain using ``show_view`` method.
brain = mne.viz.Brain('sample', subjects_dir=subjects_dir, **brain_kwargs)
brain.show_view(azimuth=190, elevation=70, distance=350, focalpoint=(0, 0, 20))
# %%
# Highlight a region on the brain
# -------------------------------
#
# It can be useful to highlight a region of the brain for analyses.
# To highlight a region on the brain you can use the ``add_label`` method.
# Labels are stored in the Freesurfer label directory from the ``recon-all``
# for that subject. Labels can also be made following the
# `Freesurfer instructions
# <https://surfer.nmr.mgh.harvard.edu/fswiki/mri_vol2label>`_
# Here we will show Brodmann Area 44.
#
# .. note:: The MNE sample dataset contains only a subselection of the
# Freesurfer labels created during the ``recon-all``.
brain = mne.viz.Brain('sample', subjects_dir=subjects_dir, **brain_kwargs)
brain.add_label('BA44', hemi='lh', color='green', borders=True)
brain.show_view(azimuth=190, elevation=70, distance=350, focalpoint=(0, 0, 20))
# %%
# Include the head in the image
# -----------------------------
#
# Add a head image using the ``add_head`` method.
brain = mne.viz.Brain('sample', subjects_dir=subjects_dir, **brain_kwargs)
brain.add_head(alpha=0.5)
# %%
# Add sensors positions
# ---------------------
#
# To put into context the data that generated the source time course,
# the sensor positions can be displayed as well.
brain = mne.viz.Brain('sample', subjects_dir=subjects_dir, **brain_kwargs)
evoked = mne.read_evokeds(sample_dir / 'sample_audvis-ave.fif')[0]
trans = mne.read_trans(sample_dir / 'sample_audvis_raw-trans.fif')
brain.add_sensors(evoked.info, trans)
brain.show_view(distance=500) # move back to show sensors
# %%
# Add current dipoles
# -------------------
#
# Dipole modeling as in :ref:`tut-dipole-orientations` can be plotted on the
# brain as well.
brain = mne.viz.Brain('sample', subjects_dir=subjects_dir, **brain_kwargs)
dip = mne.read_dipole(sample_dir / 'sample_audvis_set1.dip')
cmap = plt.colormaps['YlOrRd']
colors = [cmap(gof / dip.gof.max()) for gof in dip.gof]
brain.add_dipole(dip, trans, colors=colors, scales=list(dip.amplitude * 1e8))
brain.show_view(azimuth=-20, elevation=60, distance=300)
img = brain.screenshot() # for next section
# %%
# Create a screenshot for exporting the brain image
# -------------------------------------------------
# Also, we can a static image of the brain using ``screenshot`` (above),
# which will allow us to add a colorbar. This is useful for figures in
# publications.
fig, ax = plt.subplots()
ax.imshow(img)
ax.axis('off')
cax = fig.add_axes([0.9, 0.1, 0.05, 0.8])
norm = Normalize(vmin=0, vmax=dip.gof.max())
fig.colorbar(ScalarMappable(norm=norm, cmap=cmap), cax=cax)
fig.suptitle('Dipole Fits Scaled by Amplitude and Colored by GOF')
|
