= MEG visual tutorial: Single subject =
''Authors: Francois Tadel, Elizabeth Bock. ''

The aim of this tutorial is to reproduce in the Brainstorm environment the analysis described in the SPM tutorial "[[ftp://ftp.mrc-cbu.cam.ac.uk/personal/rik.henson/wakemandg_hensonrn/Publications/SPM12_manual_chapter.pdf|Multimodal, Multisubject data fusion]]". The data processed here consists in simulateneous MEG/EEG recordings of 16 subjects performing simple visual task on a large number of famous, unfamiliar and scrambled faces.

The analysis is split in two tutorial pages: the present tutorial describes the detailed analysis of one single subject and another one that the describes the batch processing and [[Tutorials/VisualGroup|group analysis of the 16 subjects]].

Note that the operations used here are not detailed, the goal of this tutorial is not to teach Brainstorm to a new inexperienced user. For in depth explanations of the interface and the theory, please refer to the introduction tutorials.

<<TableOfContents(3,2)>>

== License ==
These  data are provided freely for research purposes only (as part of their  Award of the BioMag2010 Data Competition). If you wish to publish any of  these data, please acknowledge Daniel Wakeman and Richard Henson. The  best single reference is: Wakeman DG, Henson RN, [[http://www.nature.com/articles/sdata20151|A  multi-subject, multi-modal human neuroimaging dataset]], Scientific Data (2015)

Any questions, please contact: rik.henson@mrc-cbu.cam.ac.uk

== Presentation of the experiment ==
==== Experiment ====
 * 16 subjects
 * 6 runs (sessions) of approximately 10mins for each subject
 * Presentation of series of images: familiar faces, unfamiliar faces, phase-scrambled faces
 * The subject has to judge the left-right symmetry of each stimulus
 * Total of nearly 300 trials in total for each of the 3 conditions

==== MEG acquisition ====
 * Acquisition at 1100Hz with an Elekta-Neuromag VectorView system (simultaneous MEG+EEG).
 * Recorded channels (404):
  * 102 magnetometers
  * 204 planar gradiometers
  * 70 EEG electrodes recorded with a nose reference.
 * MEG data have been "cleaned" using Signal-Space Separation as implemented in MaxFilter 2.1.
 * A  Polhemus digitizer was used to digitise three fiducial points and a  large number of other points across the scalp, which can be used to  coregister the M/EEG data with the structural MRI image.
 * The distribution contains 3 sub-directories of empty-room recordings of 3-5mins acquired  at roughly the same time of year (spring 2009) as the 16 subjects. The  sub-directory names are Year (first 2 digits), Month (second 2 digits)  and Day (third 2 digits). Inside each are 2 raw *.fif files: one for  which basic SSS has been applied by maxfilter in a similar manner to the  subject data above, and one (*-noSSS.fif) for which SSS has not been  applied (though the data have been passed through maxfilter just to  convert to float format).

==== Subject anatomy ====
 * MRI data acquired on a 3T Siemens TIM Trio: 1x1x1mm T1-weighted structural MRI
 * Processed with FreeSurfer 5.3

== Download and installation ==
 * The data is hosted on this FTP site (use an FTP client such as FileZilla, not your web browser): <<BR>>ftp://ftp.mrc-cbu.cam.ac.uk/personal/rik.henson/wakemandg_hensonrn/
 * Download only the following folders (about 75Gb):
  * '''EmptyRoom''': MEG empty room measurements.
  * '''SubXX/MEEG''': MEG and EEG recordings in FIF format and triggers definition files.
  * '''Publications''': Reference publications related with this dataset.
  * '''README.TXT''': License and dataset description.
 * The FreeSurfer segmentations of the T1 images are not part of this package. You can either process them by yourself, or download the result of the segmentation from the Brainstorm website. <<BR>>Go to the [[http://neuroimage.usc.edu/bst/download.php|Download]] page, and download the file: '''sample_group_anat.zip'''<<BR>>Unzip this file in the same folder where you downloaded all the datasets.
 * Reminder: Do not put the downloaded files in the Brainstorm  folders (program or database folders).
 * Start Brainstorm (Matlab scripts or stand-alone version). For help, see the [[Installation]] page.

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

== Import the anatomy ==
 * Switch to the "anatomy" view.
 * Right-click on the TutorialAuditory folder > New subject > '''Sub01'''
  * Leave the default options you set for the protocol
 * Right-click on the subject node > Import anatomy folder:
  * Set the file format: "FreeSurfer folder"
  * Select the folder: '''Anatomy/Sub01'''  (from sample_group_anat.zip)
  * Number of vertices of the cortex surface: 15000 (default value)
 * The two sets of fiducials we usually have to define interactively are here set automatically.
  * '''NAS/LPA/RPA''': The file Anatomy/Sub01/fiducials.m contains the definition of the nasion, left and right ears. The anatomical points used by the authors are the same as the ones we recommend in the Brainstorm [[CoordinateSystems|coordinates systems page]].
  * '''AC/PC/IH''': Identified automatically using the SPM affine registration with an MNI template.
  * If you want to double-check that all these points were correctly marked after importing the anatomy, right-click on the MRI > Edit MRI.

 * At   the end of the process, make sure that the file "cortex_15000V" is   selected (downsampled pial surface, that will be used for the source   estimation). If it is not, double-click on it to select it as the   default cortex surface. Do not worry about the big holes in the head surface, parts of MRI have been remove voluntarily for anonymization purposes.<<BR>><<BR>> {{attachment:anatomy_import.gif||height="384",width="613"}}

 * All the anatomical atlases [[Tutorials/LabelFreeSurfer|generated by FreeSurfer]] were imported automatically: the surface-based cortical atlases and the atlas of sub-cortical regions (ASEG). <<BR>><<BR>> {{attachment:anatomy_atlas.gif||height="211",width="550"}}

== Access the recordings ==
=== Link the recordings ===
 * Switch to the "functional data" view.
 * Right-click on the subject folder > '''Review raw file'''.
  * Select the file format: "'''MEG/EEG: Neuromag FIFF (*.fif)'''"
  * Select the '''first''' FIF files in: '''Sub01/MEEG''' <<BR>><<BR>> {{attachment:review_raw.gif||height="181",width="446"}}
 * Events:''' Ignore'''<<BR>>We will load the trial definition separately.<<BR>><<BR>> {{attachment:review_ignore.gif||height="186",width="330"}}
 * Refine registration now? '''NO''' <<BR>>The head points that are available in the FIF files contain all the points that were digitized during the MEG acquisition, including the ones corresponding to the parts of the face that have been removed from the MRI. If we run the fitting algorithm, all the points around the nose will not match any close points on the head surface, leading to a wrong result. We will first remove the face points and then run the registration manually.
 * Right-click on the channel file > '''Digitized head points > Remove points below nasion'''.<<BR>><<BR>> {{attachment:channel_remove.gif||height="194",width="329"}}
 * Right-click on the channel file > '''MRI registration > Remove points below nasion'''.<<BR>><<BR>> {{attachment:channel_refine.gif||height="173",width="294"}}
 * MEG/MRI registration, before (left) and after (right) this automatic registration procedure:  <<BR>><<BR>> {{attachment:registration.gif||height="209",width="236"}} {{attachment:registration_final.gif||height="208",width="237"}}
 * Right-click on the  "Link to raw file" > '''MEG (all) > Display time series'''. <<BR>><<BR>> {{attachment:events_add.gif||height="183",width="537"}}
 * In the Record tab, menu '''File > Add events from file''':
  * Select the file format: "'''FieldTrip trial definition ('''*.txt;'''*.mat)'''"
  * Select the '''first''' text file: '''Sub01/MEEG/Trials/run_01_trldef.txt''' <<BR>><<BR>> {{attachment:events_file.gif||height="170",width="596"}}

== Epoching and averaging ==
<<EmbedContent(http://neuroimage.usc.edu/bst/get_feedback.php?Tutorials/VisualSingle)>>