def task_connectivity_stats():
"""Step 12: Compute statistics on connectivity."""
con_fnames = []
for subject in subjects:
for cond in conditions:
con_fnames.append(fname.con(subject=subject, condition=cond))
con_filenames = [
fname.ga_con(condition=cond) for cond in conditions + ['contrast']
]
return dict(file_dep=['12_connectivity_stats.py'] + con_fnames,
targets=con_filenames,
actions=['python 12_connectivity_stats.py'])
def task_connectivity_stats():
"""Step 12: Compute statistics on connectivity."""
con_fnames = []
for subject in subjects:
for cond in conditions:
con_fnames.append(fname.con(subject=subject, condition=cond))
ga_con_fnames = [fname.ga_con(condition=cond) for cond in conditions + ['contrast', 'parcelled']]
return dict(
task_dep=['grand_average_power'],
file_dep=['12_connectivity_stats.py'] + con_fnames,
targets=ga_con_fnames + [fname.stats],
actions=['python 12_connectivity_stats.py']
)
def task_connectivity():
"""Step 10: Compute DICS connectivity."""
for subject in subjects:
fwd_r_fname = fname.fwd_r(subject=subject)
csd_fnames = []
con_fnames = []
for cond in conditions:
csd_fnames.append(fname.csd(subject=subject, condition=cond))
con_fnames.append(fname.con(subject=subject, condition=cond))
yield dict(
name=subject,
task_dep=['power'],
file_dep=[fwd_r_fname, fname.pairs, '10_connectivity.py'] + csd_fnames,
targets=con_fnames,
actions=['python 10_connectivity.py %s' % subject],
)
# Handle command line arguments (only --help)
parser = argparse.ArgumentParser(description=__doc__)
args = parser.parse_args()
# Connectivity will be morphed back to the fsaverage brain
fsaverage = mne.read_source_spaces(fname.fsaverage_src)
cons = dict()
for condition in conditions:
print('Reading connectivity for condition:', condition)
cons[condition] = list()
for subject in subjects:
con_subject = conpy.read_connectivity(
fname.con(condition=condition, subject=subject))
# Morph the Connectivity to the fsaverage brain. This is possible,
# since the original source space was fsaverage morphed to the current
# subject.
con_fsaverage = con_subject.to_original_src(
fsaverage, subjects_dir=fname.subjects_dir)
# By now, the connection objects should define the same connection
# pairs between the same vertices.
cons[condition].append(con_fsaverage)
# Average the connection objects. To save memory, we add the data in-place.
print('Averaging connectivity objects...')
ga_con = dict()
for cond in conditions: