= Resting state recordings from the OMEGA database =
'''[WARNING: Tutorial under construction, not ready for public use]'''

''Authors: Francois Tadel, Guiomar Niso, Elizabeth Bock, Sylvain Baillet ''

This tutorial introduces how to download resting state recordings from the OMEGA database and process them into Brainstorm. The goal is evaluate where in the brain is distributed the power in specific frequency bands at rest. This example includes only 5 healthy subjects, but the same pipeline can be applied over larger populations.

<<TableOfContents(3,2)>>

== OMEGA database ==
The Open MEG Archive (OMEGA) is the fruit  of a collaborative effort by the McConnell Brain Imaging Centre and the  Université de Montréal to build a centralised repository in which to  regroup MEG data for open dissemination. This continuously expanding  repository also contains anatomical MRI volumes, demographic and  questionnaire information, and eventually will feature other forms of  electrophysiological data (e.g. EEG, field, and cell recordings). OMEGA  features the technological framework for multi-centric data aggregation,  and is amongst the largest freely available resting-state MEG datasets  presently available.

''' '''You are free to use all data in OMEGA for research purposes; however, we  ask that you '''please cite the following reference''' in your publications  if you have used data from OMEGA:

Niso G, Rogers C, Moreau JT, Chen LY, Madjar C, Das S, Bock E, Tadel F, Evans A, Jolicoeur P, Baillet S<<BR>>[[http://dx.doi.org/10.1016/j.neuroimage.2015.04.028|OMEGA: The Open MEG Archive]], Neuroimage, 2015.

== Presentation of the experiment ==
==== Experiment ====
 * 5 subjects x 5 minute resting sessions, eyes open

==== MEG acquisition ====
 * Acquisition at '''2400Hz''', with a '''CTF 275''' MEG system,
 * Recorded at the Montreal Neurological Institute in 2015-2016.
 * Anti-aliasing low-pass filter at  600Hz, files saved with the CTF 3rd order gradient compensation.
 * Recorded channels (at least 297):
  * 26 MEG reference sensors (#2-#27)
  * 270 MEG axial gradiometers (#28-#297)
  * 1 ECG bipolar (EEG057/#298) - Not available in the empty room recordings
  * 1 vertical EOG bipolar (EEG058/#299) - Not available in the empty room recordings
  * 1 horizontal EOG bipolar (EEG059/#300) - Not available in the empty room recordings
 * The data in this dataset has been formatted along the BIDS specifications (Brain Imaging Data Structure, http://bids.neuroimaging.io)

==== Head shape and fiducial points ====
3D digitization using a Polhemus Fastrak device driven by Brainstorm. The .pos files contain:

 * The center of the CTF coils,
 * The anatomical references we use in Brainstorm: nasion and ears as illustrated [[http://neuroimage.usc.edu/brainstorm/CoordinateSystems#Pre-auricular_points_.28LPA.2C_RPA.29|here]],
 * Around 150 head points distributed on the hard parts of the head (no soft tissues).

==== Subject anatomy ====
 * Structural T1 image recorded with a 1.5T MRI (defaced for anonymization purposes)
 * Processed with FreeSurfer 5.3
 * The anatomical fiducials (NAS, LPA, RPA) have already been marked and saved in the files fiducials.m

== Download and installation ==
 * First, make sure you have at least '''40Gb''' of free space on your hard drive (raw files: 12Gb).
 * The OMEGA database is not in it its final release stage, so we temporarily distribute the 5 subjects used in this tutorial from the Brainstorm website.
 * Go to the [[http://neuroimage.usc.edu/bst/download.php|Download]] page, and download the file: '''sample_omega.zip '''

 * Unzip     it in a folder that is not in any of the Brainstorm folders (program     folder or database folder).

 * Start Brainstorm (Matlab scripts or stand-alone version). For help, see the [[http://neuroimage.usc.edu/brainstorm/Installation|Installation]] page.

 * Select the menu File > Create new protocol. Name it "'''TutorialOmega'''" and select the options:
  * "'''No, use individual anatomy'''",
  * "'''No, use one channel file per condition'''".

== BIDS specifications [TODO] ==
The B

Description of the initiative and its current stage of development.

The files that have been imported with this process are the following:

 * sample_omega/derivatives/freesurfer/sub-000*_ses-0001: MRIs processed with FreeSurfer.
 * sample_omega/sub-000*/ses-0001/meg/*_task-rest_run-01_meg.ds: Resting MEG recordings
 * sample_omega/sub-000*/ses-0001/meg/*_task-noise_run-01_meg: Empty room recordings

== Import the dataset ==
 * The datasets following the [[http://bids.neuroimaging.io|BIDS specifications]] can be imported automatically in Brainstorm.

 * Select the menu File > Load protocol > '''Import BIDS dataset''' > Select the folder '''sample_omega'''.
 * Keep the default values for all the questions that may be asked during the import process (eg. number of vertices in the cortex surfaces). Once finished, you should be able to access the data for the 5 subjects in your database explorer: anatomy, and subject and noise recordings. <<BR>><<BR>> {{attachment:load_bids.gif||width="594",height="322"}}

== Pre-processing ==
 * Switch to the functional view of the protocol (second button above the database explorer).
 * Drag and drop all the subjects into the Process1 box, and click on [Run].
 * Select process: '''Import recordings >''' '''Convert to continuous''': Continuous
 * Add process: '''Frequency >''' '''Power spectrum density (Welch)''': All file, 4s, 50% overlap, Individual <<BR>><<BR>> {{attachment:psd_process.gif||width="573",height="325"}}
 * Run, then check the quality of the PSD for all the files, as documented in [[http://neuroimage.usc.edu/brainstorm/Tutorials/ArtifactsFilter#Interpretation_of_the_PSD|this tutorial]]. <<BR>><<BR>> {{attachment:psd_before.gif||width="343",height="152"}}

 * In Process1, keep the same files selected and click on [Run].

 * Select process: '''Pre-process >''' '''Notch filter''': 60 120 180 240 300 Hz, Process the entire file at once

 * Add process: '''Pre-process >''' '''Band-pass filter''': High-pass filter at 0.3Hz, 60dB, Process entire file.

 * Add process: '''Frequency >''' '''Power spectrum density (Welch)''': Same options <<BR>><<BR>> {{attachment:filter_process.gif||width="597",height="342"}}

 * Run, then check the PSD after filtering. <<BR>><<BR>> {{attachment:psd_after.gif}}

 * Delete all the folders corresponding to the original recordings (_meg) and the notch filtered data (_meg_notch). Only keep the fully processed files (_meg_notch_high). <<BR>><<BR>>{{attachment:delete_original.gif}} {{attachment:delete_after.gif}}

== Artifact cleaning ==
We will remove the contamination from the most types of artifacts (heartbeats and blinks) with the procedure described in the introduction tutorials ([[Tutorials/ArtifactsDetect|detection]], [[Tutorials/ArtifactsSsp|SSP]], [[Tutorials/BadSegments|bad segments]]).

 * In Process1, select all the subject recordings ('''task-rest''').
 * Select process: '''Events > Detect heartbeats''': ECG, All file, cardiac
 * Add process: '''Events > Detect eye blinks''': VEOG, All file, blink
 * Add process: '''Artifacts > SSP: Heartbeats''': cardiac, MEG, Use existing SSP
 * Add process: '''Artifacts > SSP: Eye blinks''': blink, MEG, Use existing SSP
 * Add process: '''File > Snapshot''': Sensor/MRI registration
 * Add process: '''File > Snapshot''': SSP projectors<<BR>><<BR>> {{attachment:ssp_process.gif}}
 * Run, then review the registration and the SSP topographies for all the subjects. <<BR>><<BR>> {{attachment:ssp_report.gif}}

== Resting state metrics [TODO] ==
Discuss what measures can be used in resting state MEG...

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