[Mne_analysis] functional network from raw resting state MEG

[Abolfazl Ziaeemehr]

        External Email - Use Caution        

Hello everyone,

I am almost new to MNE, Please be patient with me.
I am trying to calculate the functional network from raw resting state MEG
data from here
<http://How_to_Build_a_Functional_Connectomic_Biomarker_for_Mild_Cognitive_Impairment_from_Source_Reconstructed_MEG_Resting-State_Activity_-_Raw_data_I_Controls_/6210158>
.
I am following this example:
Compute source space connectivity and visualize it using a circular graph
<https://mne.tools/stable/auto_examples/connectivity/plot_mne_inverse_label_connectivity.html>

The problem is there is no *meg-inv.fif* file in the dataset.
an I am stuck in these lines:

inverse_operator
<https://mne.tools/stable/generated/mne.minimum_norm.InverseOperator.html#mne.minimum_norm.InverseOperator>
= read_inverse_operator
<https://mne.tools/stable/generated/mne.minimum_norm.read_inverse_operator.html#mne.minimum_norm.read_inverse_operator>(fname_inv
<https://docs.python.org/3/library/stdtypes.html#str>)

stcs = apply_inverse_epochs
<https://mne.tools/stable/generated/mne.minimum_norm.apply_inverse_epochs.html#mne.minimum_norm.apply_inverse_epochs>(epochs
<https://mne.tools/stable/generated/mne.Epochs.html#mne.Epochs>,
inverse_operator
<https://mne.tools/stable/generated/mne.minimum_norm.InverseOperator.html#mne.minimum_norm.InverseOperator>,
lambda2 <https://docs.python.org/3/library/functions.html#float>,
method <https://docs.python.org/3/library/stdtypes.html#str>,
                            pick_ori="normal", return_generator=True)

Gramfort, 2013. MEG and EEG data analysis with MNE-Python. *Frontiers in
neuroscience*, *7*, p.267.
This article clearly explain why we need a SourceEstimate object

Is it still possible to calculate the functional network from this dataset
or I should look for something else?

here is the output of *raw.info <http://raw.info>*:
*MADCN0001_tsss_mc.fif*
<Info | 23 non-empty values
 acq_pars: ACQch001 110113 ACQch002 110112 ACQch003 110111 ACQch004 110122
...
 bads: []
 ch_names: MEG0113, MEG0112, MEG0111, MEG0122, MEG0123, MEG0121, MEG0132,
...
 chs: 204 GRAD, 102 MAG, 1 EEG, 3 STIM, 9 CHPI
 custom_ref_applied: False
 description: Vectorview system
 dev_head_t: MEG device -> head transform
 dig: 322 items (3 Cardinal, 4 HPI, 315 Extra)
 events: 1 item (list)
 experimenter: Common account for MEG work (meg)
 file_id: 4 items (dict)
 highpass: 0.1 Hz
 hpi_meas: 1 item (list)
 hpi_results: 1 item (list)
 hpi_subsystem: 2 items (dict)
 line_freq: 50.0
 lowpass: 330.0 Hz
 meas_date: 2013-11-05 12:09:28 UTC
 meas_id: 4 items (dict)
 nchan: 319
 proc_history: 1 item (list)
 proj_id: 1 item (ndarray)
 proj_name: qsm
 projs: []
 sfreq: 1000.0 Hz
 subject_info: 7 items (dict)
>

-- 

Abolfazl Ziaeemehr
Department of Physics,
PhD student in Computational Physics
Institute for Advanced Studies in Basic Sciences (IASBS)
Tel: 0919 607 4296
Page: iasbs.ac.ir/~a.ziaeemehr
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