Tutorial 4: Co-registration MEG-MRI

Authors: Francois Tadel, Elizabeth Bock, Sylvain Baillet

The anatomy of your subject is ready. Before we can start looking at the MEG/EEG recordings, we need to make sure that the sensors (electrodes, magnetometers or gradiometers) are properly aligned with the MRI and the surfaces of the subject.

In this tutorial, we will start with a detailed description of the experiment and the files that were recorded, then we will link the original CTF files to the database in order to get access to the sensors positions, and finally we will explore the various options for aligning these sensors on the head of the subject.

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This dataset (MEG and MRI data) was collected by the MEG Unit Lab, McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Canada. The original purpose was to serve as a tutorial data example for the Brainstorm software project. It is presently released in the Public Domain, and is not subject to copyright in any jurisdiction.

We would appreciate though that you reference this dataset in your publications: please acknowledge its authors (Elizabeth Bock, Peter Donhauser, Francois Tadel and Sylvain Baillet) and cite the Brainstorm project seminal publication.

Presentation of the experiment


  • One subject, two acquisition runs of 6 minutes each.
  • Subject stimulated binaurally with intra-aural earphones (air tubes+transducers), eyes opened and looking at a fixation cross on a screen.
  • Each run contains:
    • 200 regular beeps (440Hz).
    • 40 easy deviant beeps (554.4Hz, 4 semitones higher).
  • Random inter-stimulus interval: between 0.7s and 1.7s seconds, uniformly distributed.
  • The subject presses a button when detecting a deviant with the right index finger.
  • Auditory stimuli generated with the Matlab Psychophysics toolbox.
  • The specifications of this dataset were discussed initially on the FieldTrip bug tracker:

MEG acquisition

  • Acquisition at 2400Hz, with a CTF 275 system, subject in sitting position

  • Recorded at the Montreal Neurological Institute in December 2013
  • Anti-aliasing low-pass filter at 600Hz, files saved with the 3rd order gradient
  • Downsampled at a lower sampling rate: from 2400Hz to 600Hz: The only purpose for this resampling is to make the introduction tutorials easier to follow the on a regular computer.

  • Recorded channels (340):
    • 1 Stim channel indicating the presentation times of the audio stimuli: UPPT001 (#1)
    • 1 Audio signal sent to the subject: UADC001 (#316)
    • 1 Response channel recordings the finger taps in response to the deviants: UDIO001 (#2)
    • 26 MEG reference sensors (#5-#30)
    • 274 MEG axial gradiometers (#31-#304)
    • 2 EEG electrodes: Cz, Pz (#305 and #306)
    • 1 ECG bipolar (#307)
    • 2 EOG bipolar (vertical #308, horizontal #309)
    • 12 Head tracking channels: Nasion XYZ, Left XYZ, Right XYZ, Error N/L/R (#317-#328)
    • 20 Unused channels (#3, #4, #310-#315, #329-340)
  • 3 datasets:
    • S01_AEF_20131218_01_600Hz.ds: Run #1, 360s, 200 standard + 40 deviants

    • S01_AEF_20131218_02_600Hz.ds: Run #2, 360s, 200 standard + 40 deviants

    • S01_Noise_20131218_02_600Hz.ds: Empty room recordings, 30s long

  • Average reaction times for the button press after a deviant tone:
    • Run #1: 515ms +/- 108ms

    • Run #2: 596ms +/- 134ms

Stimulation delays

  • Delay #1: Production of the sound.
    Between the stim markers (channel UDIO001) and the moment when the sound card plays the sound (channel UADC001). This is mostly due to the software running on the computer (stimulation software, operating system, sound card drivers, sound card electronics). The delay can be measured from the recorded files by comparing the triggers in the two channels: Delay between 11.5ms and 12.8ms (std = 0.3ms) This delay is not constant, we will need to correct for it.

  • Delay #2: Transmission of the sound.
    Between when the sound card plays the sound and when the subject receives the sound in the ears. This is the time it takes for the transducer to convert the analog audio signal into a sound, plus the time it takes the sound to travel through the air tubes from the transducer to the subject's ears. This delay cannot be estimated from the recorded signals: before the acquisition, we placed a sound meter at the extremity of the tubes to record when the sound is delivered. Delay between 4.8ms and 5.0ms (std = 0.08ms). At a sampling rate of 2400Hz, this delay can be considered constant, we will not compensate for it.

  • Delay #3: Recording of the signals.
    The CTF MEG systems have a constant delay of 4 samples between the MEG/EEG channels and the analog channels (such as the audio signal UADC001), because of an anti-aliasing filter that is applied to the first and not the second. This translate here to a constant delay of 1.7ms.

  • Delay #4: Over-compensation of delay #1.
    When correcting of delay #1, the process we use to detect the beginning of the triggers on the audio signal (UADC001) sets the trigger in the middle of the ramp between silence and the beep. We "over-compensate" the delay #1 by 1.7ms. This can be considered as constant delay of about -1.7ms.

  • Uncorrected delays: We will correct for the delay #1, and keep the other delays (#2, #3 and #4). After we compensate for delay #1 our MEG signals will have a constant delay of about 4.9 + 1.7 - 1.7 = 4.9 ms. We decide not to compensate for these delays because they do not introduce any jitter in the responses and they are not going to change anything in the interpretation of the data.


Head shape and fiducial points

  • 3D digitization using a Polhemus Fastrak device driven by Brainstorm (S01_20131218_01.pos)

  • More information: Digitize EEG electrodes and head shape

  • The output file is copied to each .ds folder and contains the following entries:
    • The position of the center of CTF coils.
    • The position of the anatomical references we use in Brainstorm:
      Nasion and connections tragus/helix, as illustrated here.

    • Around 150 head points distributed on the hard parts of the head (no soft tissues).

Subject anatomy

  • Subject with 1.5T MRI
  • Marker on the left cheek
  • Processed with FreeSurfer 5.3

Tutorials using this dataset

  • All the introduction tutorials

Registration method

The registration between the MRI and the MEG (or EEG) is done in two steps. We start with a first approximation based on three reference points, then we refine it with the full head shape of the subject.

Step 1: Fiducials

Step 2: Head shape

Channel file

Brainstorm offers the possibility to visualize continuous MEG/EEG recordings in any of the supported file formats without having to fully "import" them. A link to the native file is created in the database, which can be then manipulated almost like the "imported" recording blocks. Only the description of the file is saved in the database, and when displaying it the values are read directly from the native file.

From auditory

Multiple runs and head position

From CTF

Channel file

Let's explore what you can do with the first file. Right-click on the CTF channels file and try all the menus.


The menus in the Display menu display the same thing, but in a different way. You can add the scalp (or cortex) surface easily with the toolbar in the Surfaces tab, in the main window (Add a surface "+" button).

channelCtf.gif channelHelmet.gif channelMeg.gif

Display a table with all the information about the individual channels. You can use this window to view and edit the channels properties.


The channel file describes each channel separately, with the following information:

For the moment, the registration between anatomy and sensors is based only on three points that are manually positioned (nasion and ears). This rough alignment technique is quite robust but also very imprecise, and depends on the precision with which the people defined the fiducials, both during the data acquisition and on the MRI slices. For this reason, it is sometimes necessary to correct the position of the sensors.

There is nothing to change here, but remember to always check the registration scalp/sensors just after you import MEG or EEG recordings.

Before locking your subject into that dark shielded room, when you acquire the position of some reference points with a magnetic tracking system (eg. Polhemus Isotrak), it is a good practice to acquire also many other points at the surface of the head. It does not take a very long time but provides very valuable information to register properly the MEG sensors with the MRI and surfaces. The more head points the better, with a minimum of 50 or 100, avoiding the softer parts of the head (cheeks, base of the neck, ears, eyes) because they may have different shapes when the patient is sitting on the MEG chair and when he/she is laying down in the MR scanner. Always insist on the nose, it provides a really good indicator of the orientation of the head.

Note: The digitization of the head shape and the head localization coils with a Polhemus device can be done with Brainstorm: see the digitize tutorial.

Some other fields are present in the channel file that cannot be accessed with the Channel editor window. You can explore those other fields with the File menu, selecting View file contents or Export to Matlab. As we saw in previous tutorial.


Some fields you may find there:

Feedback: Comments, bug reports, suggestions, questions
Email address (if you expect an answer):

Tutorials/ChannelFile (last edited 2015-02-06 18:01:09 by FrancoisTadel)