Differences between revisions 21 and 43 (spanning 22 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
Compute source activity
Compute statistics
Volume scouts
DBA constraints [TODO]
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: *file.zip*.
The file is an exported Brainstorm protocol. To load 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:

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"

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.

At this stage, it is now possible to compute sources.

You can now visualize activity the same way as for usual headmodels.

If activities of the volume structures (thalamus and amygdala here) do not appear, try moving the Min size cursor to max and then back to 1.

Compute statistics

Now that the source calculations are done, we design a statistical analysis to assess the eyes-open and eyes-closed contrast.

First, the alpha-power is time-averaged for each run
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 volumic scouts. The steps are the following :

First, create the volumic 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 volumic scouts you want to create
Finally, you can display time series of your choice

DBA constraints [TODO]

Describe the constraints applied to each region.

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

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-To follow through the tutorial, the dataset can be downloaded *here*.
+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, .
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-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.
+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.
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-The dataset is already in Brainstorm format and simply needs to be loaded  via File > Load Protocol. {{attachment:LoadProtocol.png}}
+ * Start by downloading the tutorial dataset: *file.zip*.
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-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.
+ * The file is an exported Brainstorm protocol. To load in your database, use the menu:<<BR>> File > Load Protocol > '''Load from zip file'''. <<BR>><<BR>> {{attachment:DBA_LoadProtocol.png||height="209",width="293"}}
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+{{attachment:DBA_SelectStructures.png||height="353",width="444"}}
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+{{attachment:DBA_MergeSurfaces.png||height="295",width="223"}}                                                        {{attachment:DBA_RenameCtx.png||height="198",width="135"}}
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-{{attachment:SelectStructures.png}} {{attachment:MergeSurfaces.png}} {{attachment:RenameCtx.png}} {{attachment:SourceModelOptions.png}} {{attachment:SetModelingOptions.png}}
+{{attachment:DBA_SourceModelOptions.png||height="193",width="437"}}

{{attachment:DBA_SetModelingOptions.png||height="213",width="440"}}
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-{{attachment:HeadModelBatch.png}} {{attachment:HeadModelOptions.png}}
+{{attachment:DBA_HeadModelBatch.png||height="268",width="233"}}        {{attachment:DBA_HeadModelOptions.png||height="267",width="206"}}
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-{{attachment:ComputeSources.png}} {{attachment:SourceOptions.png}} {{attachment:SourceOptions2.png}}
+{{attachment:DBA_ComputeSources.png||height="244",width="171"}}    {{attachment:DBA_SourceOptions.png||height="232",width="156"}}       {{attachment:DBA_SourceOptions2.png||height="289",width="143"}}
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-{{attachment:VisuActivity.png}}
+{{attachment:DBA_VisuActivity.png||height="351",width="478"}}
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-If the activity of the volume structures (thalamus and amygdala here) do not appear, try moving the Min size cursor to max and then back to 1.
+If activities of the volume structures (thalamus and amygdala here) do not appear, try moving the Min size cursor to max and then back to 1.
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- * First, the alpha-power is time-averaged for each run<<BR>> {{attachment:AverageTime.png}} {{attachment:AverageTimeOptions3.png}}
+ * First, the alpha-power is time-averaged for each run<<BR>> {{attachment:DBA_AverageTime.png||height="259",width="303"}}  {{attachment:DBA_AverageTimeOptions.png||height="216",width="236"}}
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- * Run a Student's T-Test to compute a statistical contrast between the conditions<<BR>> {{attachment:Ttest.png}} {{attachment:TtestOptions.png}}
 * The stat file can then be visualized and the values corresponding to subcortical structures are also appearing<<BR>> {{attachment:VisuStat.png}}
 * 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.png}}
+ * Run a Student's T-Test to compute a statistical contrast between the conditions<<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>> {{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>> {{attachment:DBA_DiffOfMeans.png||height="283",width="394"}}
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- * First, create the volumic atlas<<BR>> {{attachment:VolumeScouts.png}}
+ * First, create the volumic atlas<<BR>> {{attachment:DBA_VolumeScouts.png||height="264",width="668"}}
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+Line 66:
-  * Click on the "Create scout" cross, and  click one point of the structure you want to include in the scout<<BR>> {{attachment:VolumeFirstPoint.png}}
  * 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.png}} {{attachment:RightThal.png}}
  * Rename the scout and set the correct region and the desired function<<BR>> {{attachment:RenameScout.png}} {{attachment:SetRegion.png}} {{attachment:SetFunction.png}}
+  * 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="147"}} {{attachment:DBA_Scout_RightThal.png||height="272",width="266"}}
  * Rename the scout and set the correct region and the desired function<<BR>> {{attachment:DBA_RenameScout.png||height="83",width="204"}} {{attachment:DBA_SetRegion2.png||height="277",width="265"}} {{attachment:DBA_SetFunction2.png||height="277",width="251"}}
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- * Finally, you can display time series of your choice<<BR>> {{attachment:DisplayScoutsTS.png}}
+ * Finally, you can display time series of your choice<<BR>> {{attachment:DBA_DispolayScoutsTS.png||height="306",width="280"}}







== DBA constraints [TODO] ==
Describe the constraints applied to each region.

== 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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