[Mne_analysis] Applying Inverse to Evoked vs Applying Inverse to Epochs and Averaging

[Rockhill, Alexander P.]

Hi Chris,

    Of course, here is the relevant code:

snr=1.0
method='dSPM'
set_log_level("critical")

set_config("SUBJECTS_DIR",fs_dir,set_env=True)

bem = read_bem_solution(os.path.join(fs_dir, data.name, 'bem',
                        '%s-5120-5120-5120-bem-sol.fif' % data.name))
source = read_source_spaces(os.path.join(fs_dir, data.name, 'bem',
                                         '%s-oct-6p-src.fif' % data.name))
coord_trans = read_trans(os.path.join(fs_dir, data.name, 'mri', 'T1-neuromag',
                                      'sets', 'COR-%s-%s.fif' %(data.name,data.task)))

# Source localization parameters.
lambda2 = 1.0 / snr ** 2
pick_ori = 'normal'

value_indices = data._get_indices(event,condition,values,bins)

epochs = data.epochs_current[event]
epochs.set_eeg_reference(None)
info = epochs.info

print('Making forward model...')
fwd = make_forward_solution(epochs.info,coord_trans,source,bem,
                            meg=False,eeg=True,mindist=1.0)

print('Making noise covariance matrices...')
data.epochs_current['baseline'].info['bads'] = epochs.info['bads']
data.epochs_current['baseline'].set_eeg_reference(None)
_,tmin,tmax = data.events['baseline']
noise_cov = compute_covariance(data.epochs_current['baseline'],
                                    tmin=tmin,tmax=tmax,
                                    method="shrunk")

print('Making inverse...')
inv = make_inverse_operator(epochs.info, fwd, noise_cov)
data.invs[event] = (inv,lambda2,method)

bl_epochs = data.epochs_current['baseline'].crop(tmin=tmin,tmax=tmax)
data.stcs['baseline'] = apply_inverse_epochs(bl_epochs,inv,lambda2=lambda2,method=method)
A = sum([ss.data for ss in data.stcs['baseline']])/len(data.stcs['baseline'])

bl_evoked = data.epochs_current['baseline'].crop(tmin=tmin,tmax=tmax).average()
B = apply_inverse(bl_evoked,inv,lambda2=lambda2,method=method).data

np.array_equal(A,B) # False

Hope that helps.

Alex

________________________________
From: mne_analysis-bounces at nmr.mgh.harvard.edu [mne_analysis-bounces at nmr.mgh.harvard.edu] on behalf of Christopher Bailey [cjb at cfin.au.dk]
Sent: Friday, November 03, 2017 11:20 AM
To: Discussion and support forum for the users of MNE Software
Subject: Re: [Mne_analysis] Applying Inverse to Evoked vs Applying Inverse to Epochs and Averaging

Hi Alex,

Would you mind sharing the code you used for this experiment? I have a feeling the answer might be of general relevance, and it might help to be concrete.

/Chris
/Aarhus, DK

On 3 Nov 2017, at 16.11, Rockhill, Alexander P. <AROCKHILL at mgh.harvard.edu<mailto:AROCKHILL at mgh.harvard.edu>> wrote:

Hi all,

    I tried applying an inverse model to the evoked data and also applying inverse epochs directly to the same epochs that were averaged to make the evoked data and then averaging the data from the list of source space time courses, and these matrices weren't the same. Does anyone have any insight as to why this would be?

Thanks,

Alex
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