ICA is fit to MEG raw data. We assume that the non-stationary EOG artifacts have already been removed. The sources matching the ECG are automatically found and displayed.
Note that this example does quite a bit of processing, so even on a fast machine it can take about a minute to complete.
Read and preprocess the data. Preprocessing consists of:
data_path = sample.data_path() raw_fname = data_path + '/MEG/sample/sample_audvis_filt-0-40_raw.fif' raw = mne.io.read_raw_fif(raw_fname, preload=True) raw.pick_types(meg=True, eeg=False, exclude='bads', stim=True) raw.filter(1, 30) # longer + more epochs for more artifact exposure events = mne.find_events(raw, stim_channel='STI 014') epochs = mne.Epochs(raw, events, event_id=None, tmin=-0.2, tmax=0.5)
Opening raw data file /home/ubuntu/mne_data/MNE-sample-data/MEG/sample/sample_audvis_filt-0-40_raw.fif... Read a total of 4 projection items: PCA-v1 (1 x 102) idle PCA-v2 (1 x 102) idle PCA-v3 (1 x 102) idle Average EEG reference (1 x 60) idle Range : 6450 ... 48149 = 42.956 ... 320.665 secs Ready. Current compensation grade : 0 Reading 0 ... 41699 = 0.000 ... 277.709 secs... Setting up band-pass filter from 1 - 30 Hz l_trans_bandwidth chosen to be 1.0 Hz h_trans_bandwidth chosen to be 7.5 Hz Filter length of 991 samples (6.600 sec) selected 319 events found Events id: [ 1 2 3 4 5 32] 319 matching events found Created an SSP operator (subspace dimension = 3) 4 projection items activated
Fit ICA model using the FastICA algorithm, detect and plot components explaining ECG artifacts.
Fitting ICA to data using 305 channels. Please be patient, this may take some time Inferring max_pca_components from picks. Loading data for 319 events and 106 original time points ... 0 bad epochs dropped Selection by explained variance: 125 components Loading data for 319 events and 106 original time points ... Reconstructing ECG signal from Magnetometers Setting up band-pass filter from 8 - 16 Hz Number of ECG events detected : 284 (average pulse 61 / min.) Creating RawArray with float64 data, n_channels=1, n_times=41700 Range : 0 ... 41699 = 0.000 ... 277.709 secs Ready. 284 matching events found Created an SSP operator (subspace dimension = 3) Loading data for 284 events and 151 original time points ... 0 bad epochs dropped
Plot properties of ECG components:
Loading data for 319 events and 106 original time points ...
Total running time of the script: ( 1 minutes 29.701 seconds)