Current dipole fitting using independent components

Hello everyone,

MNE version: 1.3.0
System: Mac, Ventura 13.1, Apple M1

I am using MNE python to do some connectivity analysis. Meanwhile, I am interested in doing dipole fitting on a selected number of independent components. I have been working with FieldTrip, and I have been using this method a lot. Since I am new in MNE, I am assuming that there should be a way to run dipole fitting analysis on independent components.
So, it would be great if you could give me some hint on this question.

Thank you in advance,

That is not really something we support. You could try and back the ICA component in an EvokedArray object so you can do mne.fit_dipole on it, but please check the results against fieldtrip before trusting them.

Experimental code. Use at your own risk.
import mne

# Grab some example data
root = mne.datasets.sample.data_path()
subjects_dir = root / 'subjects'
meg_dir = root / 'MEG' / 'sample'
raw = / 'sample_audvis_filt-0-40_raw.fif', preload=True)

# Compute covariance
events = mne.find_events(raw)
epochs = mne.Epochs(raw, events, event_id={'aud/l': 1, 'aud/r': 2, 'vis/l': 3, 'vis/r': 4},
                    picks='meg', preload=True)
cov = mne.read_cov(meg_dir / 'sample_audvis-cov.fif')

# Hipass before fitting ICA
raw_high = raw.filter(1.0, None)

# Tuning ICA for speed over accuracy for this example
ica = mne.preprocessing.ICA(0.9, random_state=0).fit(raw_high, decim=5, picks='meg')

# Let's look through the components to see if there's one with a nice dipole pattern...
# Component 4 looks good! It seems to capture the auditory evoked potential.
ica.plot_properties(epochs['aud/l'], picks=4)

# Place the component in an Evoked object
component = mne.EvokedArray(ica.get_components()[:, [4]],

# Load a BEM model and fit a dipole
bem = mne.read_bem_solution(subjects_dir / 'sample' / 'bem' / 'sample-5120-5120-5120-bem-sol.fif')
trans = mne.read_trans(meg_dir / 'sample_audvis_raw-trans.fif')

# Fit the dipole using only the sensors on the left side of the head
picks_lh = [ch['ch_name'] for ch in['chs'] if ch['loc'][0] < 0]
component_lh = component.pick_channels(picks_lh)
dip, _ = mne.fit_dipole(component_lh, cov, bem, trans)

# Plot dipole location
dip.plot_locations(trans, 'sample', subjects_dir)
1 Like

The above code fits a dipole to the ICA weights. I don’t know if that makes any sense. But hopefully with the above to get you started you can make it do the same thing you have been doing in fieldtrip.