how to save source estamates from epoched data set with multiple events

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1

Hi all,
I am trying to extract from a structural roi a time series source estimate for each one of the epoch in each of my conditions

first I read in the saved epoched data fif file:

epochs=mne.read_epochs(fname_epoched)

next I apply the inverse operator that I created using the evoked data and the anatomic label previously created and execute the following:

stcs = apply_inverse_epochs(epochs,inverse_operator, lambda2, method, anat_label1,
                            pick_ori="normal")

what I would like to do next is calculate the mean activation within this roi comprising 480 vertices. so that I have one average value for each of my epochs and conditions and save an output matrix comprising time series for each epoch and including a vector for event id

I tried picking up from the a similar stage in the plot_compute_mne_inverse_epochs_in_label.py substituting my commands above for

# Read epochs
epochs = mne.Epochs(raw, events, event_id, tmin, tmax, picks=picks,
                    baseline=(None, 0), reject=dict(mag=4e-12, grad=4000e-13,
                                                    eog=150e-6))

# Compute inverse solution and stcs for each epoch
stcs = apply_inverse_epochs(epochs, inverse_operator, lambda2, method, label,
                            pick_ori="normal")

mean_stc = sum(stcs) / len(stcs)

but mean_stc is not what I want and stcs does not have attribute save like for example stc.save

any help would be appreciated
thanks dave

2

hi David,

have a look at:

http://martinos.org/mne/stable/auto_examples/inverse/plot_label_source_activations.html

extract_label_time_course will give you a time series per stc, then you can make
an array from all time courses and save it as a numpy binary file with np.save

let me know if you need more help

HTH
Alex

3

thanks I have been using this example as a base but I was curious about the following:
1. can stc.extract_label_time_course work on a epoched data . fif file containing all my event condtions
2. lets say I want to extract as a time course just the vertices with the center of mass or perhaps an roi reflecting this vertices and a small number of neighboring vertices instead of the mean of a whole anatomic roi label. how could I do that?
3 ) with np.save can I also ad a vector that corresponds to the event type that each epoch represents?

thanks //dave

hi David,

have a look at:

http://martinos.org/mne/stable/auto_examples/inverse/plot_label_source_activations.html

extract_label_time_course will give you a time series per stc, then you can make
an array from all time courses and save it as a numpy binary file with np.save

let me know if you need more help

HTH
Alex

Hi all,
I am trying to extract from a structural roi a time series source estimate for each one of the epoch in each of my conditions

first I read in the saved epoched data fif file:

epochs=mne.read_epochs(fname_epoched)

next I apply the inverse operator that I created using the evoked data and the anatomic label previously created and execute the following:

stcs = apply_inverse_epochs(epochs,inverse_operator, lambda2, method, anat_label1,
                           pick_ori="normal")

what I would like to do next is calculate the mean activation within this roi comprising 480 vertices. so that I have one average value for each of my epochs and conditions and save an output matrix comprising time series for each epoch and including a vector for event id

I tried picking up from the a similar stage in the plot_compute_mne_inverse_epochs_in_label.py substituting my commands above for

# Read epochs
epochs = mne.Epochs(raw, events, event_id, tmin, tmax, picks=picks,
                   baseline=(None, 0), reject=dict(mag=4e-12, grad=4000e-13,
                                                   eog=150e-6))

# Compute inverse solution and stcs for each epoch
stcs = apply_inverse_epochs(epochs, inverse_operator, lambda2, method, label,
                           pick_ori="normal")

mean_stc = sum(stcs) / len(stcs)

but mean_stc is not what I want and stcs does not have attribute save like for example stc.save

any help would be appreciated
thanks dave

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