## page was renamed from Tutorials/DuneuroMunsterData '''[TUTORIAL UNDER CONSTRUCTION]''' Will be completed soon In this tutorial we describe the full FEM process as described in the SPIE paper We may keep the previous tutorial as a basic and this tutorial is an advanced and complete version. = FEM tutorial: MEG/EEG Median nerve stimulation = ''Authors: Takfarinas Medani, Juan Garcia-Prieto, Wayne Mead.'' This tutorial introduces the FEM modeling in the Brainstorm environment. Note that the operations used here are not detailed, the goal of this tutorial is not to introduce Brainstorm to new users. For in-depth explanations of the interface and theoretical foundations, please refer to the [[http://neuroimage.usc.edu/brainstorm/Tutorials#Get_started|introduction tutorials]]. <> == License == 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. == Description of the experiment == The experiment consists of two stimulation protocols being conducted during a single scanning session in a MEG laboratory with an Elekta Triux (Megin, Finland) scanner. The subject is a a right-handed 46 years old male. The two stimulation protocols consist of a unilateral median nerve stimulation and an eyes-close resting-state recording. Median nerve stimulation: * The stimulation signal was a square-wave pulse with 2Hz frequency and a 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 both hands/wrists, independently, with a Digitimer DS7A stimulator. An electrode was placed on each current values were tuned to match the motor threshold of the subject on the stimulated hand, with a result of 10~12mA aproximately. * Initially, the left wrist was stimulated for aproximately 2 minutes (this corresponds with the file containing L1 in its name). After a 2-minute rest, while sitting in the MSR and with his head in the helmet, the stimulation was repeated (L2 file). After this stimulation the subject was asked to have a 10 minutes rest, during which he was allowed to sit calmly with his head out of the helmet, although remaining hooked to the scanner at all times. Finally, two subsequents runs of right wrist stimulation (R1 and R2 files) with an intermediate 2-minute rest were performed. * Recordings were performed with a 1kHz sampling rate. Continuous HPI was disabled during these recordings. And 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. Resting-State protocol: * The subject was recorded for aproximately 80 minutes. Due to a 2GB maximum-size limitation for FIFF files, this translates into the recording being saved in files 'epi1' to 'epi4'. * The subject had his eyes closed. * Recordings were performed with a 1kHz sampling rate. Continuos HPI was enabled. High-pass filterse 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, with motion compensation active. == Download and installation == * Requirements: You have already followed all the introduction tutorials and you have a working copy of Brainstorm installed on your computer. * Go to the [[http://neuroimage.usc.edu/bst/download.php|Download]] page of this website, and download the file: '''sample_tutoFEMadvance.zip''' * Unzip it in a folder that is not in any of the Brainstorm folders (program or database folder) * Start Brainstorm (Matlab scripts or stand-alone version) * Select the menu File > Create new protocol. Name it "'''TutorialFEM'''" and select the options: * "'''No, use individual anatomy'''", * "'''No, use one channel file per condition'''". == Import the anatomy == * Right-click on the TutorialFEM folder > New subject > '''Subject01''' * Leave the default options you set for the protocol * Right-click on the subject node > Import anatomy folder: * Set the file format: "FreeSurfer folder" * Number of vertices of the cortex surface: 15000 (default value) * Click on the link "'''Click here to compute MNI transformation'''". * Set the 6 required fiducial points (indicated in MRI coordinates). This dataset is a good example of a real-world fiducials setting. Fiducials points not always have to be located where we recommend in our [[https://neuroimage.usc.edu/brainstorm/Tutorials/ImportAnatomy#Fiducial_points|introductory]] and our [[https://neuroimage.usc.edu/brainstorm/CoordinateSystems?highlight=(auricular)|coordinate systems]] tutorials. Every subject is different and sometimes things get on the way, and it is not possible to follow canonical recommendations. That is fine! As long as there is a correct correspondence between fiducial points in the fif file and in the MRI, everything works fine. In order to guide in this process, the dataset includes images of the locations with the preauricular fiducials. * At the end of the process, make sure that the file "cortex_15000V" is selected (downsampled pial surface, which will be used for the source estimation). If it is not, double-click on it to select it as the default cortex surface.<
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> == Access the recordings == === Link the recordings === * Switch to the "functional data" view, the middle button in the toolbar above the database explorer. * Right-click on the subject folder > '''Review raw file''': * === Prepare the channel file === * === Refine the MRI registration === * * === Read the stimulation information === * == Pre-processing == === Evaluate the recordings === * === Frequency filters === * == Review the recordings == === MEG: Default montages === === MEG: Bad channels === * === EEG: Average reference === * == Artifacts cleaning with ICA == === Detect heartbeats and blinks === * === EEG: Heartbeats and eye movements === * * === MEG: Heartbeats and eye movements === * == Epoching and averaging == === Import the recordings === === Averaging === * == Source estimation == === Head model === * === Noise covariance matrix === * === Inverse model === * * * === Regions of interest === * Create two scouts S1 and S2 to represent the primary and secondary somatosensory cortex of the left hemisphere. * == Scripting ==