[Mne_analysis] mne.save_stc_as_volume('lcmv_inverse.nii.gz', stc, fwd['src'], mri_resolution=False)

[parham hashemzadeh]

Dear
  I simply ran the tutorial below, which uses the file name
fname_fwd = data_path + '/MEG/sample/sample_audvis-meg-vol-7-fwd.fif'
So, it is a volume. I simply set Meg=False. It appears to me that it is 
volume. At least it says that it is volume "vol-7-fwd.fif". I wanted to 
only do the beamformer with EEG.
best regards parham hashemzadeh



On 2016-04-14 04:33, dgw wrote:
> Hi Parham,
> Where are you getting src from? It doesn't seem to be a volume source 
> space.
> 
> hth
> d
> Sent from my Phone
> 
>> On Apr 13, 2016, at 18:01, parham hashemzadeh <ph442 at cam.ac.uk> wrote:
>> 
>> Dear
>>  Thank you for your email. But actually no I am not using that 
>> tutorial.
>> I am using this tutorial which is focused on the Volume Source Space.
>> 
>> http://martinos.org/mne/dev/auto_examples/inverse/plot_lcmv_beamformer_volume.html#sphx-glr-auto-examples-inverse-plot-lcmv-beamformer-volume-py
>> 
>> All I am doing is that I am turning off the MEG and just want to use 
>> the
>> EEG.
>> 
>> In theory it should work even with this reduced leadfield matrix. 
>> Before
>> it was 366 rows but now only 60 rows (Just EEG).
>> 
>> So my volume (source space) does not change. It is exactly the same
>> thing. My number of sensors are reduced.
>> 
>> The error happens at the line below:
>> mne.save_stc_as_volume('lcmv_inverse.nii.gz', stc, fwd['src'],
>> mri_resolution=False)
>> 
>> ""Only volume source estimates can be saved as volumes"" can be saved
>> 
>> Any help will be appreciated.
>> besst regards parham
>> 
>> 
>> 
>> 
>> 
>> 
>> 
>> 
>> 
>> 
>> 
>> 
>>> On 2016-04-13 21:41, dgw wrote:
>>> Hi Parham,
>>> 
>>> It sounds like you are using this tutorial:
>>> 
>>> http://martinos.org/mne/dev/auto_examples/inverse/plot_lcmv_beamformer.html?highlight=beamformer
>>> 
>>> If that is the case, it uses the cortical surface as the source space
>>> and not a volume, so it doesn't really make sense to save as a nifti.
>>> 
>>> hth
>>> d
>>> 
>>> On Wed, Apr 13, 2016 at 3:48 PM, parham hashemzadeh <ph442 at cam.ac.uk>
>>> wrote:
>>>> Dear all
>>>> 
>>>> I got an error when running a beamforming tutorial script. I 
>>>> modified
>>>> the beamformer such that only the EEG leadfield is used and I just
>>>> wanted to do EEG analysis.
>>>> So I made the following changes:
>>>> (a) meg=False in fwd
>>>> (b) in epochs reject=dict(eog=150e-6)
>>>> When it gets to the function lcm_inverse, it throws an error:
>>>> 
>>>> ""Only volume source estimates can be saved as volumes"" can be 
>>>> saved
>>>> 
>>>> 
>>>> 
>>>>  I was wondering, if you would be able to point me in the right
>>>> direction.
>>>> Many thanks
>>>> best regards parham hashemzadeh
>>>> 
>>>> 
>>>> 
>>>> fwd = mne.make_forward_solution(raw_fname, trans, src, bem,
>>>>                                 fname=None, meg=False, eeg=True,
>>>> mindist=5.0,
>>>>                                 n_jobs=2, overwrite=True)
>>>> epochs = mne.Epochs(raw, events, event_id, tmin, tmax, proj=True,
>>>>                     picks=picks, baseline=(None, 0), preload=True,
>>>>                     reject=dict(eog=150e-6))
>>>> 
>>>> evoked = epochs.average()
>>>> leadfield = fwd['sol']['data']
>>>> ## Read regularized noise covariance and compute regularized data
>>>> covariance
>>>> noise_cov = mne.read_cov(fname_cov)
>>>> data_cov = mne.compute_covariance(epochs, tmin=0.04,
>>>> tmax=0.15,method='shrunk')
>>>> #
>>>> ## Run free orientation (vector) beamformer. Source orientation can 
>>>> be
>>>> ## restricted by setting pick_ori to 'max-power' (or 'normal' but 
>>>> only
>>>> when
>>>> ## using a surface-based source space)
>>>> stc = lcmv(evoked, fwd, noise_cov, data_cov, reg=0.01, 
>>>> pick_ori=None)
>>>> #
>>>> ## Save result in stc files
>>>> stc.save('lcmv-vol')
>>>> stc.crop(0.0, 0.2)
>>>> ## Save result in a 4D nifti file
>>>> img = mne.save_stc_as_volume('lcmv_inverse.nii.gz',
>>>> stc,fwd['src'],mri_resolution=False)
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>> 
>> --
>> best regards
>> Parham Hashemzadeh
>> Research Associate
>> Department of Applied Mathematics and Theoretical Physics
>> University of Cambridge, UK.
>> email: hashemzadeh at damtp.cam.ac.uk
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-- 
best regards
Parham Hashemzadeh
Research Associate
Department of Applied Mathematics and Theoretical Physics
University of Cambridge, UK.
email: hashemzadeh at damtp.cam.ac.uk