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| In this tutorial we will compare the performance of the BEM, FEM forward computation in basic model (realistic head model 3 layer) and also within in a spherical head model with an analytical solution. | == Introduction == In this tutorial, we compare the head models computation using the methods available in brainstorm. At this time, the FEM implementation is available for the EEG and the MEG computation. We will integrate and test soon the FEM for sEEG and ECOG. == EEG within a spherical model == === The volume conductor or the head model: === In this part we used the spherical head model distributed by the duneuro team ([[https://gitlab.dune-project.org/duneuro/duneuro-tests/-/blob/master/src/test_sphere_tet.msh|sphere]]). The following figure shows on the left the surface model and on right the tetrahedral mesh. {{attachment:DuneuroModelMesh.JPG||height="300",width="600"}} The model has three layers, the brain (inner skull), the outer skull and the scalp. === The source space : === For the source space or dipole position, we will use a realistic cortex distributed with the ICBM default subject of brainstorm. {{attachment:DuneuroModelMeshAnCortex.JPG||height="300",width="600"}} === The sensor model === Regarding the electrode's positions, we use the same position defined in this [[https://gitlab.dune-project.org/duneuro/duneuro-tests/-/blob/master/src/test_sphere_electrodes.txt|file]]. The total number of electrodes is 200 regularly distributed on the outer layer. {{attachment:DuneuroModelElectrode.JPG||height="300",width="350"}} === The forward model === Now, we have all the components of the model, we can start the process to compute the head model. For the EEG, brainstorm offers three methods. We perform these three computations on this model. 1. 3-shell sphere: best-fitting sphere based on the scalp, then OK. 1. OpenMeeg BEM: use the conductivity 0.33, 0.004 and 0.33, and keep the default options. 1. DUNEuro FEM: use the default option with the same conductivity value as the previous method. {{attachment:protocolDuneuroSphereEEG.JPG||height="180",width="250"}} === Qualitative comparison of the methods === In this tutorial, we use the display of the lead field vector to compare visually the performances of the three methods. Right-click on the head model, and then select 'View lead field vector'. You can select more than the head model in order to overlay the vectors. {{attachment:rightClickLeadFieldView.JPG||height="250",width="350"}} In this figure, we show all of these methods and zoom to focus on the vectors. For more documentations about these lead field vectors, please refere to these pages ([[https://www.researchgate.net/publication/260603026_Biomagnetism|page1]], [[http://www.bem.fi/book/11/11x/1119x.htm|page2]]) {{attachment:ViewLeadFieldEEGAllMethod.JPG||height="300",width="350"}} {{attachment:leadVectorZoom.JPG||height="300",width="350"}} We can easily see that the three vectors are pointing in the same direction and have the same length. Regarding the computation time: * 3-shell sphere: less than 30 secondes * OpenMeeg BEM: ~ 12 minutes. * DUNEuro FEM: ~ 2 minutes. This example has 15000 dipoles (x3) and 200 electrodes. There are many studies and publications that compare these methods and highlights the advantages and weakness of each method. From the brainstorm side, we recommend to use either openmeeg or duneuro for a realistic head model. If you have the FEM mesh*, Duneuro is faster for the same mesh resolution as the surface (OpenMeeg). Duneuro can be used for a more realistic model (more than 3 layers with the complex shape). *You can generate the FEM if you have the surfaces or the MRI, this process is explained in this '''tutorial'''. == EEG within brainstom template (3 layers) == In this example, we will present the process of FEM mesh generation from surface model and highlight the effect of the mesh resolution. the BEM, FEM forward computation in basic model (realistic head model 3 layer) and also within a spherical head model with an analytical solution. |
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| Compare the performance of the mesh resolution vs the leadfield approximation | Compare the performance of the mesh resolution vs the lead field approximation |
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| difference appears on v10 | the difference appears on v10 |
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| in spherical head model | in the spherical head model |
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| same observation on the lf view {{attachment:lfview_v01andv001.JPG||height="400",width="700"}} |
same observation on the lf view {{attachment:lfview_v01andv001.JPG||height="400",width="700"}} |
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| difference appears on the v1 and worse for v10 | the difference appears on the v1 and worse for v10 |
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| == EEG forward within 3 layers head model: == In this example, we compute the head model for the ICBM head model using the openmeeg method and then we generate the fem mesh for the same subject, then we compute the lead field using the Duneuro method v = 0.1 default value. MNorm {{attachment:sourcelocalisation.JPG||height="400",width="700"}} |
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| == EEG forward within 3 layers head model : == In this example we compute the head model for the ICBM head model using the openmeeg method and then we generate the fem mesh for the same subject, then we compute the the leadfield using the Duneuro method v = 0.1 default value. {{attachment:sourcelocalisation.JPG||height="400",width="700"}} |
sloreta {{attachment:sourcelocalisationloreta.JPG||height="400",width="700"}} {{attachment:sourcelocalisationloreta2.JPG||height="400",width="700"}} |
Introduction
In this tutorial, we compare the head models computation using the methods available in brainstorm.
At this time, the FEM implementation is available for the EEG and the MEG computation. We will integrate and test soon the FEM for sEEG and ECOG.
EEG within a spherical model
The volume conductor or the head model:
In this part we used the spherical head model distributed by the duneuro team (sphere). The following figure shows on the left the surface model and on right the tetrahedral mesh. 
The model has three layers, the brain (inner skull), the outer skull and the scalp.
The source space :
For the source space or dipole position, we will use a realistic cortex distributed with the ICBM default subject of brainstorm.
The sensor model
Regarding the electrode's positions, we use the same position defined in this file. The total number of electrodes is 200 regularly distributed on the outer layer.
The forward model
Now, we have all the components of the model, we can start the process to compute the head model. For the EEG, brainstorm offers three methods. We perform these three computations on this model.
- 3-shell sphere: best-fitting sphere based on the scalp, then OK.
OpenMeeg BEM: use the conductivity 0.33, 0.004 and 0.33, and keep the default options.
- DUNEuro FEM: use the default option with the same conductivity value as the previous method.
Qualitative comparison of the methods
In this tutorial, we use the display of the lead field vector to compare visually the performances of the three methods.
Right-click on the head model, and then select 'View lead field vector'. You can select more than the head model in order to overlay the vectors.
In this figure, we show all of these methods and zoom to focus on the vectors. For more documentations about these lead field vectors, please refere to these pages (page1, page2)
We can easily see that the three vectors are pointing in the same direction and have the same length.
Regarding the computation time:
- 3-shell sphere: less than 30 secondes
OpenMeeg BEM: ~ 12 minutes.
- DUNEuro FEM: ~ 2 minutes.
This example has 15000 dipoles (x3) and 200 electrodes.
There are many studies and publications that compare these methods and highlights the advantages and weakness of each method.
From the brainstorm side, we recommend to use either openmeeg or duneuro for a realistic head model. If you have the FEM mesh*, Duneuro is faster for the same mesh resolution as the surface (OpenMeeg).
Duneuro can be used for a more realistic model (more than 3 layers with the complex shape).
*You can generate the FEM if you have the surfaces or the MRI, this process is explained in this tutorial.
EEG within brainstom template (3 layers)
In this example, we will present the process of FEM mesh generation from surface model and highlight the effect of the mesh resolution.
the BEM, FEM forward computation in basic model (realistic head model 3 layer) and also within a spherical head model with an analytical solution.
Describe femVSbem here.
Compare the performance of the mesh resolution vs the lead field approximation
v10, v1, v0.1 and v0.01 
v0.1 and V0.01 are almost the same ....
the difference appears on v10
in the spherical head model
same observation on the lf view 
the difference appears on the v1 and worse for v10
EEG forward within 3 layers head model:
In this example, we compute the head model for the ICBM head model using the openmeeg method and then we generate the fem mesh for the same subject, then we compute the lead field using the Duneuro method v = 0.1 default value. MNorm 
sloreta 
