MEG current phantom (Elekta-Neuromag)

This tutorial dataset remains a property of its authors: Ken Taylor, John Mosher (Epilepsy Center, Cleveland Clinic Neurological Institute, Cleveland, OH USA).

If you reference this dataset in your publications, please acknowledge them and cite Brainstorm as indicated on the website. For questions, please contact us through the forum.

The phantom

A current phantom is provided with the Elekta Neuromag for checking the system performance. It contains 32 artificial dipoles and four fixed head-position indicator coils. The phantom is based on the mathematical fact that an equilateral triangular line current produces equivalent magnetic field distribution to that of a tangential current dipole in a spherical conductor, provided that the vertex of the triangle and the origin of the conducting sphere coincide. For a detailed description of how the phantom works, see here.

The phantom dipoles are energized using an internal signal generator which also feeds the HPI coils. An external multiplexer box is used to connect the signal to the individual dipoles. Only one dipole can be activated at a time. The location of the dipole is recorded relative to the center of the sphere (0,0,0)m, where X is positive toward the nasion, Y is positive toward the left ear and Z is positive toward the top of the head (see the CoordinateSystems tutorial for more details).

Use of the phantom is shown below. Note that the uncovered version is the phantom that came with the Neuromag-122, which explicitly shows the wiring. The covered version uses the same principle but somewhat different dipole locations. Further details are available in Section 7.2 of the User's Manual.

References

• R.J. Ilmoniemi, M.S. Hämäläinen, and J. Knuutila, The Forward and Inverse Problems in the Spherical Model. In: Biomagnetism: Applications and Theory, eds. H. Weinberg, G. Stroink, T. Katil, Pergamon Press, 1985.
• Elekta Neuromag System Hardware User's Manual, Revision G, September 2005.

Description of the experiment

Files distributed as part of the phantom Elekta tutorial:

• kojak_all_2000nAm_pp_no_chpi_no_ms_raw.fif
  Source = 2000 nAm. This corresponds to an unrealistically strong 1,000 nA-m (2,000 nA-m peak to peak) dipole that gives the highest SNR visualization of the experimental source.

• kojak_all_200nAm_pp_no_chpi_no_ms_raw.fif
  Source = 200 nAm. This is a weaker dipole, closer to the range of amplitudes we can expect from inter-ictal spikes due to epilepsy, visible in raw data.

• kojak_all_20nAm_pp_no_chpi_no_ms_raw.fif
  Source = 20 nAm. This represents some of the weakest sources we expect in evoked studies which require averaging to detect and estimate (i.e. generally cannot be seen in single trials).

• All recordings were performed by John Mosher in the MEG lab at the Cleveland Clinic with an Elekta phantom.

Download and installation

• Requirements: You have followed the introduction tutorials and Brainstorm is installed.

• Go to the Download page and download the file: sample_phantom_elekta.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)

• Select the menu File > Create new protocol. Name it TutorialPhantomElekta and select:

  • No, use individual anatomy,

  • No, use one channel file per acquisition run (MEG).

Generate anatomy

• In the Matlab command window: type "generate_phantom_elekta".

• This creates a new subject Kojak (so named after the 70's TV show) and generates the "anatomy" for this device: one volume and a few surfaces representing the geometry of the phantom.
  
  

• 
  
  

• You can display the MRI and surfaces as presented in the introduction tutorials.
  
  

Access the recordings

We can now review one of the raw kojak data sets. These have been generated by sequentially activating each of the 32 phantom dipoles in a single raw file.

• Switch to the functional data view by clicking the second button under the protocol name.

• Right-click on the subject folder > Review raw file.

  • Select the file format: "MEG/EEG: Elekta-Neuromag (*.fif)"

  • Select the 200nA file: sample_phantom_elekta/kojak_all_200nAm...fif

• Click Event channel, select STI201, and hit OK.

• A figure is opened at the end of the import to show the position of the phantom in the MEG:
  
  

Organize the events

• Double click the link to raw file: it opens the recordings and shows the list of the events.
• In the Record tab, rename your groups so that the ordering remains convenient:

  • Double-click on event group "1" (or menu Events > Rename group), rename it to 01.

  • Repeat this for events #2-#9.
• Some unnecessary triggers are generated by the neuromag system, we will delete them:

  • Select all the categories with only one event (#256-#7939), press the delete key.

• These steps can also be performed from your MATLAB command window:
  • Close the file viewer.

  • Right-click on the link > File > Export to Matlab > "link"

  • Run the lines of code below:

    for i = 1:32
        STR = str2num(link.F.events(i).label);
        link.F.events(i).label = sprintf('%02.0f',STR);
    end
    link.F.events(33:end) = [];

  • Right-click on the link > File > Import from Matlab > "link".

• There is also a switching transient in the phantom generator which should be removed:

  • Select category 01, click on the first time instant and press the delete key.

• Events should now appear as per the image below on the right:
  
  

• 

• Close the recordings figure to save the modifications.

Import the dipole events

Right click on Link to raw file > Import in database:

• Select all the events #01-#32, Epoch time = [-100,300]ms

• Uncheck Apply SSP/ICA projectors (we will use noise covariance to stabilize the data)

• Check Remove DC offset, time range = [-100,-10]ms

• Resample the recordings to 100Hz (change from 1000Hz)

• Do not create separate folders

• Click Import
  
  

Noise covariance

With the epochs imported, we can now calculate the noise covariance from the prestims:

• Select all the imported epochs (click on the first group, hold the shift key, click on the last).

• Right-click on any epochs group > Noise covariance > Compute from recordings.

• Keep all the default options and hit OK.
  
  

• 

Average trials

• In Process1, select all the 32 trials groups.

• Run process Average > Average files > By trial group (folder average).
  
  

• 

Head modelling

• Right-click on the channel file > Compute head model > MRI volume, Single sphere.
  
  

• A figure opens showing a sphere fit to the phantom, however we can see that the location is not exactly (0,0,0). We can adjust it manually:

  • Click the Edit sphere properties button in the top toolbar.

  • Change the center location to [ 0 0 0 ] and hit OK.

• Click the [OK] button. A window appears allowing adjustment of the volume source grid.

• Select Regular grid (isotropic) with Grid resolution 2.5mm.
  This results in an around 56K grid point, which is sufficient.
  
  

Dipole source estimation

• Right click the Single sphere (volume) and select Compute sources [2016]

• Method: Dipole modeling

• Source model: Dipole orientations Unconstrained

For the sensor selection you can choose to use either the gradiometers or the magnetometers, in this case we select both.

Click Show details if the noise covariance regularization is hidden.

• Select Regularize noise covariance: 0.1

• Ignore the other settings, and click OK
  
  

• 

• 
  

Dipole scanning

Select the set of 32 averages and drop them into the process box again. Switch to process sources and click the cog in the pipeline editor. Select Sources > Dipole Scanning [BETTER]. Set the process options to look at 60ms only by changing the Time window to 60ms - 60ms, and clicking Run.

As an optional step, we can sign flip the dipoles in Matlab so that they are all pointing up for convenience. To do this, right click on Merge: 32 files and export to Matlab as the variable merge_dips. Then in Matlab use the following code:

for i = 1:32,
    merge_dips.Dipole(i).Amplitude = merge_dips.Dipole(i).Amplitude*...
    sign(merge_dips.Dipole(i).Amplitude(3));
end
merge_dips.Comment = [merge_dips.Comment ' | flipped'];

The true dipole locations are now shown in red along with the estimated locations in blue:

Results

  Dipole      Loc (mm)      Amp (nA-m)  Gof     Perf       Chi2     RChi2
--------------------------------------------------------------------------
  01 - [ -0.4 -60.4  21.3]    75.1    98.8%    208.7    513 (201)   2.55
  02 - [  2.1 -47.9  21.3]    83.3    97.9%    117.4    295 (201)   1.47
  03 - [ -0.4 -35.4  23.8]    79.8    94.1%     64.5    263 (201)   1.31
  04 - [ -0.4 -25.4  21.3]    74.6    83.9%     36.2    251 (201)   1.25
  05 - [  2.1 -35.4  48.8]    92.7    98.1%    154.3    466 (201)   2.32
  06 - [  2.1 -25.4  43.8]    91.4    96.8%     87.9    256 (201)   1.27
  07 - [  2.1 -15.4  38.8]    90.7    91.9%     53.2    251 (201)   1.25
  08 - [  2.1  -5.4  33.8]    77.7    80.9%     30.6    222 (201)   1.10
  09 - [-60.4   2.1  21.3]    77.3    98.6%    204.2    584 (201)   2.91
  10 - [-47.9   2.1  23.8]    82.2    98.0%    120.0    290 (201)   1.44
  11 - [-35.4  -0.4  23.8]    83.9    94.8%     69.1    262 (201)   1.30
  12 - [-25.4   2.1  21.3]    80.4    88.9%     42.3    224 (201)   1.12
  13 - [-35.4   2.1  51.3]    84.4    98.4%    178.3    507 (201)   2.52
  14 - [-27.9   2.1  43.8]    86.0    96.9%    101.7    326 (201)   1.62
  15 - [-15.4   2.1  38.8]    89.3    93.5%     60.9    258 (201)   1.28
  16 - [ -7.9   2.1  31.3]    80.4    83.1%     35.2    251 (201)   1.25
  17 - [ -0.4  47.1  41.3]    85.8    98.7%    176.4    423 (201)   2.10
  18 - [ -0.4  44.6  31.3]    77.1    98.0%    106.0    229 (201)   1.14
  19 - [ -0.4  42.1  18.8]    72.7    94.5%     68.7    273 (201)   1.36
  20 - [ -0.4  34.6   8.8]    74.4    88.8%     42.3    224 (201)   1.12
  21 - [ -0.4  14.6  61.3]    79.5    98.3%    131.7    306 (201)   1.52
  22 - [  2.1  17.1  48.8]    87.9    96.1%     82.1    274 (201)   1.36
  23 - [  2.1  22.1  36.3]    86.4    92.5%     55.9    253 (201)   1.26
  24 - [  2.1  19.6  23.8]    91.6    84.0%     36.7    258 (201)   1.28
  25 - [ 47.1   2.1  41.3]    88.1    97.1%     94.2    264 (201)   1.31
  26 - [ 42.1  -0.4  31.3]    83.7    93.9%     61.7    247 (201)   1.23
  27 - [ 37.1  -0.4  18.8]    87.5    88.9%     45.6    260 (201)   1.29
  28 - [ 29.6   2.1  11.3]    85.3    87.7%     32.7    151 (201)   0.75
  29 - [ 14.6   2.1  58.8]    92.1    97.6%    129.1    402 (201)   2.00
  30 - [ 17.1   2.1  48.8]    86.8    95.8%     76.7    257 (201)   1.28
  31 - [ 19.6   2.1  38.8]    80.1    91.3%     48.3    223 (201)   1.11
  32 - [ 22.1   2.1  23.8]    87.2    84.6%     34.3    213 (201)   1.06


 Location errors from true

 Dipole      Loc (mm)            True (mm)         Diff [x y z]     Norm (mm)
------------------------------------------------------------------------------
  01 - [ -0.4 -60.4  21.3] [  0.0 -59.7  22.9] [ -0.4  -0.7  -1.6]   (  1.8)
  02 - [  2.1 -47.9  21.3] [  0.0 -48.6  23.5] [  2.1   0.7  -2.2]   (  3.2)
  03 - [ -0.4 -35.4  23.8] [  0.0 -35.8  25.5] [ -0.4   0.4  -1.7]   (  1.8)
  04 - [ -0.4 -25.4  21.3] [  0.0 -24.8  23.1] [ -0.4  -0.6  -1.8]   (  2.0)
  05 - [  2.1 -35.4  48.8] [  0.0 -37.2  52.0] [  2.1   1.8  -3.2]   (  4.3)
  06 - [  2.1 -25.4  43.8] [  0.0 -27.5  46.4] [  2.1   2.1  -2.6]   (  4.0)
  07 - [  2.1 -15.4  38.8] [  0.0 -15.8  41.0] [  2.1   0.4  -2.2]   (  3.1)
  08 - [  2.1  -5.4  33.8] [  0.0  -7.9  33.0] [  2.1   2.5   0.8]   (  3.4)
  09 - [-60.4   2.1  21.3] [-59.7  -0.0  22.9] [ -0.7   2.1  -1.6]   (  2.7)
  10 - [-47.9   2.1  23.8] [-48.6  -0.0  23.5] [  0.7   2.1   0.3]   (  2.2)
  11 - [-35.4  -0.4  23.8] [-35.8  -0.0  25.5] [  0.4  -0.4  -1.7]   (  1.8)
  12 - [-25.4   2.1  21.3] [-24.8  -0.0  23.1] [ -0.6   2.1  -1.8]   (  2.8)
  13 - [-35.4   2.1  51.3] [-37.2  -0.0  52.0] [  1.8   2.1  -0.7]   (  2.9)
  14 - [-27.9   2.1  43.8] [-27.5  -0.0  46.4] [ -0.4   2.1  -2.6]   (  3.4)
  15 - [-15.4   2.1  38.8] [-15.8  -0.0  41.0] [  0.4   2.1  -2.2]   (  3.1)
  16 - [ -7.9   2.1  31.3] [ -7.9  -0.0  33.0] [  0.0   2.1  -1.7]   (  2.7)
  17 - [ -0.4  47.1  41.3] [  0.0  46.1  44.4] [ -0.4   1.0  -3.1]   (  3.3)
  18 - [ -0.4  44.6  31.3] [  0.0  41.9  34.0] [ -0.4   2.7  -2.7]   (  3.8)
  19 - [ -0.4  42.1  18.8] [  0.0  38.3  21.6] [ -0.4   3.8  -2.8]   (  4.7)
  20 - [ -0.4  34.6   8.8] [  0.0  31.5  12.7] [ -0.4   3.1  -3.9]   (  5.0)
  21 - [ -0.4  14.6  61.3] [  0.0  13.9  62.4] [ -0.4   0.7  -1.1]   (  1.4)
  22 - [  2.1  17.1  48.8] [  0.0  16.2  51.5] [  2.1   0.9  -2.7]   (  3.6)
  23 - [  2.1  22.1  36.3] [  0.0  20.0  39.1] [  2.1   2.1  -2.8]   (  4.1)
  24 - [  2.1  19.6  23.8] [  0.0  19.3  27.9] [  2.1   0.3  -4.1]   (  4.7)
  25 - [ 47.1   2.1  41.3] [ 46.1  -0.0  44.4] [  1.0   2.1  -3.1]   (  3.9)
  26 - [ 42.1  -0.4  31.3] [ 41.9  -0.0  34.0] [  0.2  -0.4  -2.7]   (  2.8)
  27 - [ 37.1  -0.4  18.8] [ 38.3  -0.0  21.6] [ -1.2  -0.4  -2.8]   (  3.1)
  28 - [ 29.6   2.1  11.3] [ 31.5  -0.0  12.7] [ -1.9   2.1  -1.4]   (  3.1)
  29 - [ 14.6   2.1  58.8] [ 13.9  -0.0  62.4] [  0.7   2.1  -3.6]   (  4.2)
  30 - [ 17.1   2.1  48.8] [ 16.2  -0.0  51.5] [  0.9   2.1  -2.7]   (  3.6)
  31 - [ 19.6   2.1  38.8] [ 20.0  -0.0  39.1] [ -0.4   2.1  -0.3]   (  2.1)
  32 - [ 22.1   2.1  23.8] [ 19.3  -0.0  27.9] [  2.8   2.1  -4.1]   (  5.4)


 Orientation errors from true

 Dipole  Amp (nA-m)      [X Y Z]              TRUE [X Y Z]     Degrees
------------------------------------------------------------------------
  01 -    ( 75.1)  [-0.01  0.31  0.95] vs [ 0.00  0.36  0.93] (  3.0 )
  02 -    ( 83.3)  [-0.02  0.38  0.93] vs [ 0.00  0.44  0.90] (  3.7 )
  03 -    ( 79.8)  [-0.09  0.52  0.85] vs [ 0.00  0.58  0.81] (  6.5 )
  04 -    ( 74.6)  [-0.10  0.60  0.79] vs [ 0.00  0.68  0.73] (  8.2 )
  05 -    ( 92.7)  [-0.03  0.79  0.61] vs [ 0.00  0.81  0.58] (  2.7 )
  06 -    ( 91.4)  [-0.02  0.85  0.53] vs [ 0.00  0.86  0.51] (  2.0 )
  07 -    ( 90.7)  [-0.02  0.91  0.41] vs [ 0.00  0.93  0.36] (  3.2 )
  08 -    ( 77.7)  [ 0.10  0.98  0.19] vs [ 0.00  0.97  0.23] (  6.0 )
  09 -    ( 77.3)  [ 0.32  0.03  0.95] vs [ 0.36  0.00  0.93] (  3.0 )
  10 -    ( 82.2)  [ 0.43  0.08  0.90] vs [ 0.44  0.00  0.90] (  4.7 )
  11 -    ( 83.9)  [ 0.53  0.10  0.84] vs [ 0.58  0.00  0.81] (  6.7 )
  12 -    ( 80.4)  [ 0.61  0.20  0.76] vs [ 0.68  0.00  0.73] ( 12.1 )
  13 -    ( 84.4)  [ 0.82  0.02  0.58] vs [ 0.81  0.00  0.58] (  1.5 )
  14 -    ( 86.0)  [ 0.84  0.02  0.55] vs [ 0.86  0.00  0.51] (  2.8 )
  15 -    ( 89.3)  [ 0.92  0.10  0.37] vs [ 0.93  0.00  0.36] (  6.0 )
  16 -    ( 80.4)  [ 0.96  0.13  0.25] vs [ 0.97  0.00  0.23] (  7.3 )
  17 -    ( 85.8)  [ 0.00 -0.66  0.75] vs [ 0.00 -0.69  0.72] (  2.7 )
  18 -    ( 77.1)  [-0.05 -0.57  0.82] vs [ 0.00 -0.63  0.78] (  5.2 )
  19 -    ( 72.7)  [-0.13 -0.39  0.91] vs [ 0.00 -0.49  0.87] (  9.5 )
  20 -    ( 74.4)  [-0.15 -0.22  0.96] vs [ 0.00 -0.37  0.93] ( 12.3 )
  21 -    ( 79.5)  [-0.10 -0.97  0.22] vs [ 0.00 -0.98  0.22] (  5.6 )
  22 -    ( 87.9)  [-0.08 -0.95  0.32] vs [ 0.00 -0.95  0.30] (  4.5 )
  23 -    ( 86.4)  [-0.11 -0.85  0.51] vs [ 0.00 -0.89  0.46] (  7.3 )
  24 -    ( 91.6)  [-0.18 -0.75  0.63] vs [ 0.00 -0.82  0.57] ( 11.8 )
  25 -    ( 88.1)  [-0.65  0.03  0.76] vs [-0.69  0.00  0.72] (  3.8 )
  26 -    ( 83.7)  [-0.58 -0.01  0.81] vs [-0.63  0.00  0.78] (  3.6 )
  27 -    ( 87.5)  [-0.43 -0.03  0.90] vs [-0.49  0.00  0.87] (  4.3 )
  28 -    ( 85.3)  [-0.32 -0.04  0.95] vs [-0.37  0.00  0.93] (  4.1 )
  29 -    ( 92.1)  [-0.97 -0.02  0.25] vs [-0.98  0.00  0.22] (  2.0 )
  30 -    ( 86.8)  [-0.94 -0.02  0.34] vs [-0.95  0.00  0.30] (  2.5 )
  31 -    ( 80.1)  [-0.89 -0.00  0.46] vs [-0.89  0.00  0.46] (  0.5 )
  32 -    ( 87.2)  [-0.71 -0.00  0.70] vs [-0.82  0.00  0.57] (  9.7 )

Scripting

Generate Matlab script

Available in the Brainstorm distribution: brainstorm3/toolbox/script/tutorial_phantom_elekta.m