= FEM/Median nerve tutorial =
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== Dataset description ==
=== License [TODO] ===
This  tutorial dataset (MEG/EEG and MRI data) remains proprietary of xxxxyyyy.  Its use and transfer outside the Brainstorm tutorial, e.g. for research  purposes, is xxxx yyy. (allowed /prohibited /request)

=== Experiment ===
The  experiment consists of an unilateral median nerve  stimulation  conducted in a MEG laboratory with an Elekta Triux (Megin,  Finland)  scanner. The subject is a right-handed 46 years old male.

 * The stimulation signal was a square-wave pulse with 2Hz frequency and duration of 0.2ms.
 * An   ISI (inter-stimulus interval) of 500ms with a variation of ±20ms in   order to be able to average out time-locked noise to the stimulation,   while remaining unnoticeable by the subject.
 * The stimulation   was performed on the left hand/wrist, for two minutes, with a Digitimer   DS7A stimulator. An electrode was placed on each current value were   tuned to match the motor threshold of the subject on the stimulated   hand, with a result of 10~12mA approximately.
 * Recordings were   performed with a 1kHz sampling rate. Continuous HPI was disabled during   these recordings. High-pass filters were set to DC for MEG channels and   0.03Hz for EEG channels.
 * All files underwent a MaxFilter (version 2.3.13) tsss post-processing.

=== Files ===
The dataset we distribute with this tutorial follows the [[http://bids.neuroimaging.io|Brain Imaging Data Structure (BIDS)]] standard for neuroimaging data organization. The files that will be imported in this tutorial are the  following:

'''sample_fem'''/'''sub-fem01'''/: Raw data for subject fem01

 * '''ses-meg'''/: Simultaneous recordings of MEG and EEG.
  * '''sub-fem01_ses-meg_task-mediannerve_run-01_proc-tsss_meg.fif'''
 * '''ses-mri'''/: Imaging exams.
  * '''anat'''/'''sub-fem01_ses-mri_T1w.nii.gz''': T1-weighted MRI
  * '''anat'''/'''sub-fem01_ses-mri_T2w.nii.gz''': T2-weighted MRI
  * '''dwi'''/'''sub-fem01_ses-mri_dwi.*''': Diffusion-Weighted Imaging (DWI)

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== Tutorials using this dataset ==
 * [[Tutorials/FemMedianNerve|FEM median nerve]]