Differences between revisions 16 and 68 (spanning 52 versions)

DBA tutorial: Compute sources in deep cerebral structures

Authors: Jean-Eudes Le Douget, Francois Tadel, Denis Schwartz

This tutorial explains step-by-step how to use the DBA (Deep Brain Activity) functionality, useful to assess subcortical source localization.

Contents

Import database
Select deep structures
Location and orientation constraints
Source estimation [TODO]
Compute statistics
Volume scouts
References

Import database

This tutorial is based on resting-state recordings for 7 subjects with two conditions: eyes open (YO), eyes closed (YF). We have recorded 20 runs of 15 seconds for each subject and each condition.

The goal is to compute the contrast between the two conditions in the alpha band. The data has already been filtered in the alpha frequency band (7-13Hz) and the default anatomy is used for all the subjects.

Start by downloading the tutorial dataset TutorialDba.zip from the Download page.
The file is an exported Brainstorm protocol. To load it in your database, use the menu:
File > Load Protocol > Load from zip file.

Select deep structures

The first step consists in creating the surface file that includes the cortex and the deep structures that we want to include in the model. Here, in the default anatomy:

Right-click on "aseg atlas" > Less vertices > 15000 vertices.
Double-click on "aseg atlas_15000V" (contains the subcortical structures from the FreeSurfer altas).
Select the amygdala, the thalamus and the hippocampus, and create a subatlas.
Merge the cortex with the selected structures. Rename the new surface in "cortex_mixed".
Open the cortex_mixed surface and create a new atlas "Source model options". With Matlab 2015b+, the display looks weird because it limits the number of possible transparent layers to 5. To produce nicer figures, disable the OpenGL renderer (File > Edit preferences). The display will be much slower, but the renderer won't suffer from this limitation.
Set the set modeling options to "Deep brain" for all the structures.

Location and orientation constraints

Two types of constraints can be applied to each anatomical region in the atlas "Source model":

Location constraint: Defines where the sources corresponding to these regions are placed.
- Surface: The sources are located on the surface of the structure (cortex and hippocampus). The surface describing the region is directly used as the source space.
- Volume: The sources are located inside the volume of the region. The source space is a grid of points uniformly distributed inside of the volume delimited by the syrface of the structure.
- Deep brain: Use the preferred configuration defined in the Deep Brain Atlas (surface for the cerebral cortex and hippocampus, volume for all the other structures).
Orientation constraint:
- Constrained: Defines only one dipole per grid point, with a fixed orientation orientation.
  - With option "Surface": Uses the normal orientation to the surface at each point.
  - With option "Deep brain": Uses the preferred orientation defined in the atlas (see below).
- Unconstrained: Uses three orthogonal dipoles per grid point (x,y,z).
- Loose: Intermediate option, uses three orthogonal dipoles per grid point, but favors the preferred orientation used for the contrained case.

Based on the anatomical observations reported for each subcortical region in the reference articles (next section), the preferred combination of constraints is described below. The reference articles also estimate the number of averaged trials needed to detect responses in some regions.

	Location constraint	Preferred orientation	Default	Trials (MEG)	Trials (EEG)
Cortex	Surface	Normal	Constrained	-	-
Hippocampus	Surface	Normal	Constrained	21	45
Cerebellum	Surface	Normal	Unconstrained	-	-
Accumbens	Volume	None	Unconstrained	-	-
Amygdala	Volume	None	Unconstrained	-	-
Brainstem	Volume	None	Unconstrained	400 (LGN)	490 (LGN)
Caudate	Volume	None	Unconstrained	-	-
Putamen	Volume	None	Unconstrained	34	23
Pallidum	Volume	Y axis	Constrained	> 10000	> 10000
Thalamus	Volume	None	Unconstrained	3500	3700

Source estimation [TODO]

Head model

Select all the subjects (except for the empty room recordings) > right-click > Compute head model. Select "Custom source model", and leave the other options to their defaults.
You can explore the source grids that were computed. Right-click on one of the head models > Check source grid (volume) and Check source grid (surface). In the Scout tab, select the atlas "User scouts" to get a clearer view. In panel Surface, increase the transparency of the surface to see the source grids representing the select subcortical regions.

Inverse model

The noise covariance matrix was estimated from the empty room recordings (Empty_Subject) and copied to all the folders of all the subjects.
Select all the subjects (except the empty room recordings), right-click > Compute sources.
Select Minimum norm (wMNE) and lelave the other options to their default values.
Double-click on the sources for any trial (segment of 15s of rest recordings). Make sure the atlas "User scouts" is selected in the Scout tab, then explore the display options available in the Surface tab. The surface regions (cortex and hippocampus) are represented as surfaces, and the values are directly mapped on the surface. The volume regions (amygdala and thalamus) are represented as grids of dots.
In the Scout tab, you can use the atlas "Source model" to display separately some regions difficult to observe with all the cortex. Typically the activity on the hippocampus surface. Click on the button [SEL] to display only the selected regions, then select the hippocampus entries. [TODO]

Compute statistics

We will now design a statistical analysis to assess the eyes-open and eyes-closed contrast. As a reminder, the recordings available in the database have already been filtered in the alpha frequency band (7-13Hz). As a measure of the global of the activity in this frequency band, we will average all the time samples in each block of 15s. Note that this is not the recommended procedure anymore: it would have been better to simply compute a PSD from the sources estimated for the continuous file link, but this option was not available at the time this tutorial was written.

In Process1, select all the subjects (except for Empty_Subject)and select [Process sources].
Run process Average > Average time > Use absolute value, All file.
Then, the "Process2" tab is used : place the source power files of the eyes-closed condition in the "Files A" space and of the eyes-open condition in the "Files B" space.
To gain time, it is possible to sort the functional data by conditions, place the subjects in "FilesA" and "FilesB" and use the filter to include only files that contain 'avg' (for time-averaged files)
Run a Student's T-Test to compute a statistical contrast between the conditions
The stat file can then be visualized and the values corresponding to subcortical structures are also appearing
It is also interesting to observe the difference of means between conditions. To compute this, instead of runnning a Student's T-Test, select the "Difference of means" option

Volume scouts

Some subcortical structures are modeled as volume source structures (for instance here, the thalamus and the amygdala). It is not possible to display scouts time series for these structures from the "Source model" or "Structures" atlases. It is necessary to create a new atlas, specific to volume scouts. The steps are the following :

First, create the volume atlas
Second, to create a new scout :
- Click on the "Create scout" cross, and click one point of the structure you want to include in the scout
- Click on the "Increase scout size" as many times as necessary to include all the points of the volume, for example in the right thalamus
- Rename the scout and set the correct region and the desired function
- Repeat this operation for all the volume scouts you want to create
Finally, you can display time series of your choice

References

Attal Y, Bhattacharjee M, Yelnik J, Cottereau B, Lefèvre J, Okada Y, Bardinet E, Chupin M, Baillet S (2009)
Modelling and detecting deep brain activity with MEG and EEG
IRBM, 30(3):133-138

Attal Y, Schwartz D (2013)
Assessment of Subcortical Source Localization Using Deep Brain Activity Imaging Model with Minimum Norm Operators: A MEG Study
PLOS ONE, 8(3):e59856

Dumas T, Dubal S, Attal Y, Chupin M, Jouvent R (2013)
MEG Evidence for Dynamic Amygdala Modulations by Gaze and Facial Emotions
PLOS ONE, 8(9): e74145

-  ⇤ ← Revision 16 as of 2015-07-17 12:05:45 → 
  Size: 4550
  Editor: ?DenisSchwartz
  Comment: Minor typos fixed
+   ← Revision 68 as of 2016-08-10 19:46:35 → ⇥
  Size: 11041
  Editor: FrancoisTadel
  Comment:
-Deletions are marked like this.
+Additions are marked like this.
 Line 1:
-= Compute sources in deep cerebral structures : DBA tutorial =
+= DBA tutorial: Compute sources in deep cerebral structures =
''Authors: Jean-Eudes Le Douget, Francois Tadel, Denis Schwartz''
-Line 4:
+Line 6:
-== Import Database ==
To follow through the tutorial, the dataset can be downloaded *here*.
+<<TableOfContents(2,2)>>
-Line 7:
+Line 8:
-It contains MEG resting-state recordings of 7 subjects under 2 conditions, eyes-open (YO) and eyes-closed (YF). For each subject and under each condition, 20 runs of 15 seconds are included in the dataset.
+== Import database ==
This tutorial is based on resting-state recordings for 7 subjects with two conditions: eyes open (YO), eyes closed (YF). We have recorded 20 runs of 15 seconds for each subject and each condition.
-Line 9:
+Line 11:
-The dataset is already in Brainstorm format and simply needs to be loaded  via File > Load Protocol. [[attachment:LoadProtocol]]
+The goal is to compute the contrast between the two conditions in the alpha band. The data has already been filtered in the alpha frequency  band (7-13Hz) and the default anatomy is used for all the  subjects.
-Line 11:
+Line 13:
-The following steps detail a method to compute the Eyes-Open vs Eyes-Closed contrast in the alpha band.

Note that the data have already been filtered in the alpha frequency band (7-13Hz) and that for simplicity, default anatomy is used for all subjects.
+ * Start by downloading the tutorial dataset '''TutorialDba.zip''' from the [[http://neuroimage.usc.edu/bst/download.php|Download]] page.
 * The file is an exported Brainstorm protocol. To load it in your database, use the menu:<<BR>> File > Load Protocol > '''Load from zip file'''. <<BR>><<BR>> {{attachment:loadzip.gif}}
-Line 18:
+Line 19:
- * Double-click on "aseg atlas" (which contains the subcortical structures)
 * Select the amygdala, the thalamus and the hippocampus, and create a subatlas
 * Merge the cortex with the atlas of selected structures ; rename the structure created in CortexDBA
 * Create a new atlas "Source Model Atlas", and set modeling options to "Deep brain"
+ * Right-click on "aseg atlas" > '''Less vertices''' > '''15000''' vertices. <<BR>><<BR>> {{attachment:aseg_downsample.gif||height="213",width="436"}}
 * Double-click on "aseg atlas_15000V" (contains the subcortical structures from the FreeSurfer altas).
-Line 23:
+Line 22:
-[[attachment:SelectStructures]] [[attachment:MergeSurfaces]] [[attachment:RenameCtx]] [[attachment:SourceModelOptions]] [[attachment:SetModelingOptions]]
+ * Select the amygdala, the thalamus and the hippocampus, and create a subatlas. <<BR>><<BR>> {{attachment:aseg_keep.gif||height="385",width="555"}}
-Line 25:
+Line 24:
-== Compute source activity ==
Then, compute a headmodel for each subject as "Custom Source Model" ; it is advised to run it as batch from the pipeline editor.
+ * '''Merge '''the cortex with the selected structures. '''Rename '''the new surface in "cortex_mixed". <<BR>><<BR>> {{attachment:aseg_merge.gif}}  {{attachment:aseg_rename.gif}}
-Line 28:
+Line 26:
-[[attachment:HeadModelBatch]] [[attachment:HeadModelOptions]]
+ * Open the cortex_mixed surface and create a new atlas "'''Source model options'''". With Matlab 2015b+, the display looks weird because it limits the number of possible transparent layers to 5. To produce nicer figures, disable the OpenGL renderer (File > Edit preferences). The display will be much slower, but the renderer won't suffer from this limitation.<<BR>><<BR>> {{attachment:atlas_model.gif||height="214",width="668"}}
-Line 30:
+Line 28:
-At this stage, it is now possible to compute sources.
+ * Set the set modeling options to "'''Deep brain'''" for all the structures.<<BR>><<BR>> {{attachment:atlas_dba.gif||height="246",width="606"}}
-Line 32:
+Line 30:
-[[attachment:ComputeSources]] [[attachment:SourceOptions]] [[attachment:SourceOptions2]]
+== Location and orientation constraints ==
Two types of constraints can be applied to each anatomical region in the atlas "Source model":
-Line 34:
+Line 33:
-You can now visualize activity the same way as for usual headmodels.
+ * '''Location constraint''': Defines where the sources corresponding to these regions are placed.
  * '''Surface''': The sources are located on the surface of the structure (cortex and hippocampus). The surface describing the region is directly used as the source space.
  * '''Volume''': The sources are located inside the volume of the region. The source space is a grid of points uniformly distributed inside of the volume delimited by the syrface of the structure.
  * '''Deep brain''': Use the preferred configuration defined in the Deep Brain Atlas (surface for the cerebral cortex and hippocampus, volume for all the other structures).
 * '''Orientation constraint''':
  * '''Constrained''': Defines only one dipole per grid point, with a fixed orientation orientation.
   * With option "Surface": Uses the normal orientation to the surface at each point.
   * With option "Deep brain": Uses the preferred orientation defined in the atlas (see below).
  * '''Unconstrained''': Uses three orthogonal dipoles per grid point (x,y,z).
  * '''Loose''': Intermediate option, uses three orthogonal dipoles per grid point, but favors the preferred orientation used for the contrained case.
-Line 36:
+Line 44:
-[[attachment:VisuActivity]]
+Based on the anatomical  observations reported for each subcortical region in the reference  articles (next section), the preferred combination of constraints is  described below. The reference articles also estimate the number of averaged trials needed to detect responses in some regions.
-Line 38:
+Line 46:
-If the activity of the volumic structures (thalamus and amygdala here) do not appear, try moving the Min size cursor to max and then back to 1.
+ || ||'''Location<<BR>>constraint''' ||'''Preferred<<BR>>orientation''' ||'''Default''' ||'''Trials (MEG)''' ||'''Trials (EEG)''' ||
 ||'''Cortex''' ||Surface ||Normal ||Constrained || - || - ||
 ||'''Hippocampus''' ||Surface ||Normal ||Constrained || 21 || 45 ||
 ||'''Cerebellum''' ||Surface ||Normal ||Unconstrained || - || - ||
 ||'''Accumbens''' ||Volume ||None ||Unconstrained || - || - ||
 ||'''Amygdala''' ||Volume ||None ||Unconstrained || - || - ||
 ||'''Brainstem''' ||Volume ||None ||Unconstrained || 400 (LGN) || 490 (LGN) ||
 ||'''Caudate''' ||Volume ||None ||Unconstrained || - || - ||
 ||'''Putamen''' ||Volume ||None ||Unconstrained || 34 || 23 ||
 ||'''Pallidum''' ||Volume ||Y axis ||Constrained || > 10000 || > 10000 ||
 ||'''Thalamus''' ||Volume ||None ||Unconstrained || 3500 || 3700 ||





== Source estimation [TODO] ==
==== Head model ====
 * Select all the subjects (except for the empty room recordings) > right-click > '''Compute head model'''. Select "'''Custom source model'''", and leave the other options to their defaults. <<BR>><<BR>> {{attachment:dba_headmodel.gif||height="244",width="443"}}
 * You can explore the source grids that were computed. Right-click on one of the head models > '''Check source grid (volume)''' and '''Check source grid (surface)'''. In the Scout tab, select the atlas "User scouts" to get a clearer view. In panel Surface, increase the transparency of the surface to see the source grids representing the select subcortical regions. <<BR>><<BR>> {{attachment:headmodel_grid.gif||height="198",width="665"}}

==== Inverse model ====
 * The noise covariance matrix was estimated from the empty room recordings (Empty_Subject) and copied to all the folders of all the subjects.
 * Select all the subjects (except the empty room recordings), right-click > '''Compute sources'''.  <<BR>>Select '''Minimum norm (wMNE)''' and lelave the other options to their default values. <<BR>><<BR>> {{attachment:dba_inverse.gif||height="235",width="446"}}
 * Double-click on the sources for any trial (segment of 15s of rest recordings). Make sure the atlas "'''User scouts'''" is selected in the Scout tab, then explore the display options available in the Surface tab. The surface regions (cortex and hippocampus) are represented as surfaces, and the values are directly mapped on the surface. The volume regions (amygdala and thalamus) are represented as grids of dots. <<BR>><<BR>> {{attachment:dba_display.gif||height="244",width="647"}}
 * In the Scout tab, you can use the atlas "'''Source model'''" to display separately some regions difficult to observe with all the cortex. Typically the activity on the hippocampus surface. Click on the button [SEL] to display only the selected regions, then select the hippocampus entries. [TODO]
-Line 41:
+Line 74:
-Now that the source calculations are done, we design a statistical analysis to assess the eyes-open and eyes-closed contrast.
+We will now design a statistical analysis to assess the eyes-open and eyes-closed contrast. As a reminder, the recordings available in the database have already been filtered in the alpha frequency  band (7-13Hz). As a measure of the global of the activity in this frequency band, we will average all the time samples in each block of 15s. Note that this is not the recommended procedure anymore: it would have been better to simply compute a PSD from the sources estimated for the continuous file link, but this option was not available at the time this tutorial was written.
-Line 43:
+Line 76:
- * First, the alpha-power is time-averaged for each run<<BR>>[[attachment:AverageTime]] [[attachment:AverageTimeOptions]]
+ * In Process1, select all the subjects (except for Empty_Subject)and select '''[Process sources]'''.
 * Run process Average > '''Average time''' > Use absolute value, All file. <<BR>><<BR>> {{attachment:dba_avgtime.gif}}
 *
-Line 46:
+Line 81:
- * Run a Student's T-Test to compute a statistical contrast between the conditions<<BR>>[[attachment:Ttest]] [[attachment:TtestOptions]]
 * The stat file can then be visualized and the values corresponding to subcortical structures are also appearing<<BR>>[[attachment:VisuStat]]
 * It is also interesting to observe the difference of means between conditions. To compute this, instead of runnning a Student's T-Test, select the "Difference of means" option<<BR>>[[attachment:DiffOfMeans]]
+ * Run a Student's T-Test to compute a statistical contrast between the conditions<<BR>><<BR>> {{attachment:DBA_Ttest.png||height="422",width="383"}}     {{attachment:DBA_TtestOptions.png||height="283",width="226"}}
 * The stat file can then be visualized and the values corresponding to subcortical structures are also appearing<<BR>><<BR>> {{attachment:DBA_VisuStat.png||height="286",width="523"}}
 * It is also interesting to observe the difference of means between conditions. To compute this, instead of runnning a Student's T-Test, select the "Difference of means" option<<BR>><<BR>> {{attachment:DBA_DiffOfMeans.png||height="283",width="394"}}
-Line 50:
+Line 85:
-== Bonus : volumic scouts ==
Some subcortical structures are modeled as volumic source structures (for instance here, the thalamus and the amygdala). It is not possible to display scouts time series for these structures from the "Source model" or "Structures" atlases. It is necessary to create a new atlas, specific to volumic scouts. The steps are the following :
+== Volume scouts ==
Some subcortical structures are modeled as volume source structures (for instance here, the thalamus and the amygdala). It is not possible to display scouts time series for these structures from the "Source model" or "Structures" atlases. It is necessary to create a new atlas, specific to volume scouts. The steps are the following :
-Line 53:
+Line 88:
- * First, create the volumic atlas<<BR>>[[attachment:VolumeScouts]]
+ * First, create the volume atlas<<BR>><<BR>> {{attachment:DBA_VolumeScouts.png||height="264",width="668"}}
-Line 55:
+Line 91:
-  * Click on the "Create scout" cross, and  click one point of the structure you want to include in the scout<<BR>>[[attachment:VolumeFirstPoint]]
  * Click on the "Increase scout size" as many times as necessary to include all the points of the volume, for example in the right thalamus<<BR>>[[attachment:IncreaseScoutSize]] [[attachment:RightThal]]
  * Rename the scout and set the correct region and the desired function<<BR>>[[attachment:RenameScout]] [[attachment:SetRegion]] [[attachment:SetFunction]]
  * Repeat this operation for all the volumic scouts you want to create
 * Finally, you can display time series of your choice<<BR>>[[attachment:DisplayScoutsTS]]
+  * Click on the "Create scout" cross, and  click one point of the structure you want to include in the scout<<BR>>
 {{attachment:DBA_VolumeScout_FirstPoint.png||height="291",width="659"}}
  * Click on the "Increase scout size" as many times as necessary to include all the points of the volume, for example in the right thalamus<<BR>>
 {{attachment:DBA_IncreaseScoutSize2.png||height="239",width="148"}}                 {{attachment:DBA_Scout_RightThal.png||height="272",width="266"}}
  * Rename the scout and set the correct region and the desired function<<BR>><<BR>> {{attachment:DBA_RenameScout.png||height="78",width="192"}}
 {{attachment:DBA_SetRegion2.png||height="271",width="260"}}        {{attachment:DBA_SetFunction2.png||height="270",width="244"}}
  * Repeat this operation for all the volume scouts you want to create
 * Finally, you can display time series of your choice<<BR>><<BR>> {{attachment:DBA_DispolayScoutsTS.png||height="306",width="280"}}

== References ==
Attal Y, Bhattacharjee M, Yelnik J, Cottereau B, Lefèvre J, Okada Y, Bardinet E, Chupin M, Baillet S (2009)<<BR>>[[http://www.ncbi.nlm.nih.gov/pubmed/18003114|Modelling and detecting deep brain activity with MEG and EEG]]<<BR>>'''IRBM''', 30(3):133-138

Attal Y, Schwartz D (2013)<<BR>>[[http://www.plosone.org/article/info:doi/10.1371/journal.pone.0059856|Assessment of Subcortical Source Localization Using Deep Brain Activity Imaging Model with Minimum Norm Operators: A MEG Study]]<<BR>>'''PLOS ONE''', 8(3):e59856

Dumas T, Dubal S, Attal Y, Chupin M, Jouvent R (2013)<<BR>>[[http://www.plosone.org/article/info:doi/10.1371/journal.pone.0074145|MEG Evidence for Dynamic Amygdala Modulations by Gaze and Facial Emotions]]<<BR>>'''PLOS ONE''', 8(9): e74145

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