The MEGSIM consists of experimental and simulated MEG data which can be useful for reproducing research results.
The MEGSIM files will be dowloaded automatically.
The datasets are documented in: Aine CJ, Sanfratello L, Ranken D, Best E, MacArthur JA, Wallace T, Gilliam K, Donahue CH, Montano R, Bryant JE, Scott A, Stephen JM (2012) MEG-SIM: A Web Portal for Testing MEG Analysis Methods using Realistic Simulated and Empirical Data. Neuroinformatics 10:141-158
Out:
Opening raw data file /home/ubuntu/mne_data/MEGSIM/megsim/empdata/neuromag/visual/subject1_day1_vis_raw.fif...
Read a total of 3 projection items:
PCA-v1 (1 x 102) idle
PCA-v2 (1 x 102) idle
PCA-v3 (1 x 102) idle
Range : 434320 ... 2381639 = 242.246 ... 1328.383 secs
Ready.
Current compensation grade : 0
851 events found
Events id: [ 2 3 5 9 17]
218 matching events found
Created an SSP operator (subspace dimension = 3)
3 projection items activated
Rejecting epoch based on EOG : [u'EOG 062']
Rejecting epoch based on EOG : [u'EOG 062']
Rejecting epoch based on EOG : [u'EOG 062']
Rejecting epoch based on EOG : [u'EOG 062']
Rejecting epoch based on EOG : [u'EOG 062']
Rejecting epoch based on EOG : [u'EOG 062']
Rejecting epoch based on EOG : [u'EOG 062']
Rejecting epoch based on EOG : [u'EOG 062']
Rejecting epoch based on EOG : [u'EOG 062']
Rejecting epoch based on EOG : [u'EOG 062']
Rejecting epoch based on EOG : [u'EOG 062']
Rejecting epoch based on EOG : [u'EOG 062']
Rejecting epoch based on EOG : [u'EOG 062']
Rejecting epoch based on EOG : [u'EOG 062']
Rejecting epoch based on EOG : [u'EOG 062']
Rejecting epoch based on EOG : [u'EOG 062']
Rejecting epoch based on EOG : [u'EOG 062']
Rejecting epoch based on MAG : [u'MEG 2311', u'MEG 2441']
Rejecting epoch based on EOG : [u'EOG 062']
Rejecting epoch based on EOG : [u'EOG 062']
Rejecting epoch based on EOG : [u'EOG 062']
Rejecting epoch based on EOG : [u'EOG 062']
Rejecting epoch based on EOG : [u'EOG 062']
Rejecting epoch based on EOG : [u'EOG 062']
Rejecting epoch based on EOG : [u'EOG 062']
Rejecting epoch based on EOG : [u'EOG 062']
Rejecting epoch based on EOG : [u'EOG 061', u'EOG 062']
Rejecting epoch based on EOG : [u'EOG 062']
Rejecting epoch based on EOG : [u'EOG 061']
Rejecting epoch based on EOG : [u'EOG 062']
Rejecting epoch based on EOG : [u'EOG 062']
Rejecting epoch based on EOG : [u'EOG 062']
Rejecting epoch based on EOG : [u'EOG 062']
Rejecting epoch based on EOG : [u'EOG 062']
Rejecting epoch based on EOG : [u'EOG 062']
Rejecting epoch based on EOG : [u'EOG 062']
Rejecting epoch based on EOG : [u'EOG 062']
Rejecting epoch based on EOG : [u'EOG 062']
Rejecting epoch based on EOG : [u'EOG 062']
Rejecting epoch based on EOG : [u'EOG 062']
Rejecting epoch based on EOG : [u'EOG 062']
Rejecting epoch based on EOG : [u'EOG 062']
Rejecting epoch based on EOG : [u'EOG 062']
Rejecting epoch based on EOG : [u'EOG 062']
This filename (/home/ubuntu/mne_data/MEGSIM/megsim/simdata/neuromag/visual/M87174545_vis_sim1A_4mm_30na_neuro_rn.fif) does not conform to MNE naming conventions. All evoked files should end with -ave.fif or -ave.fif.gz
Reading /home/ubuntu/mne_data/MEGSIM/megsim/simdata/neuromag/visual/M87174545_vis_sim1A_4mm_30na_neuro_rn.fif ...
Read a total of 3 projection items:
PCA-v1 (1 x 102) active
PCA-v2 (1 x 102) active
PCA-v3 (1 x 102) active
Found the data of interest:
t = -199.68 ... 499.75 ms (Average to trigger # 25)
0 CTF compensation matrices available
nave = 100 - aspect type = 100
Projections have already been applied. Setting proj attribute to True.
No baseline correction applied
import mne
from mne import find_events, Epochs, pick_types, read_evokeds
from mne.datasets.megsim import load_data
print(__doc__)
condition = 'visual' # or 'auditory' or 'somatosensory'
# Load experimental RAW files for the visual condition
raw_fnames = load_data(condition=condition, data_format='raw',
data_type='experimental', verbose=True)
# Load simulation evoked files for the visual condition
evoked_fnames = load_data(condition=condition, data_format='evoked',
data_type='simulation', verbose=True)
raw = mne.io.read_raw_fif(raw_fnames[0])
events = find_events(raw, stim_channel="STI 014", shortest_event=1)
# Visualize raw file
raw.plot()
# Make an evoked file from the experimental data
picks = pick_types(raw.info, meg=True, eog=True, exclude='bads')
# Read epochs
event_id, tmin, tmax = 9, -0.2, 0.5
epochs = Epochs(raw, events, event_id, tmin, tmax, baseline=(None, 0),
picks=picks, reject=dict(grad=4000e-13, mag=4e-12, eog=150e-6))
evoked = epochs.average() # average epochs and get an Evoked dataset.
evoked.plot()
# Compare to the simulated data
evoked_sim = read_evokeds(evoked_fnames[0], condition=0)
evoked_sim.plot()
Total running time of the script: ( 0 minutes 24.141 seconds)