Suggested Pipelines: Difference between revisions

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== Basic Synthetic Aperture Magnetometry Workflow ==
== Basic Synthetic Aperture Magnetometry Workflow ==

{{#mermaid:graph LR

subgraph MRI Preprocessing
MRI["Structural MRI"] --> ortho["Processed MRI"];
end

subgraph MEG Data Statistics
meg[MEG Data] --> Filter[Band-pass<br>filter];
Filter --> Covariance;
end

subgraph MEG Preprocessing
ThresholdDetect --> filter[Basic Filtering];
filter --> marks[Create markers];
end

}}


{{#mermaid:graph LR
{{#mermaid:graph LR
subgraph SAM
subgraph SAM
Covariance --> Beamformer;
Covariance --> Beamformer;
ortho[Processed MRI] --> Beamformer;
Beamformer --> image["3D Images"];
Beamformer --> image["3D Images"];
end
subgraph MRI
MRI["Structural MRI"] --> ortho["Processed MRI<br>ortho+tlrc"];
ortho --> Beamformer;
end
end
}}
}}

Revision as of 08:40, 2 March 2019

{{#mermaid:graph LR

 DoStuff --> DoMoreStuff;
 DoMoreStuff --> DoEvenMoreStuff;
 DoEvenMoreStuff --> PublishNaturePaper;

}}

Basic Synthetic Aperture Magnetometry Workflow

{{#mermaid:graph LR

subgraph MRI Preprocessing

 MRI["Structural MRI"] --> ortho["Processed MRI"];

end

subgraph MEG Data Statistics

 meg[MEG Data] --> Filter[Band-pass
filter]; Filter --> Covariance;

end

subgraph MEG Preprocessing

 ThresholdDetect --> filter[Basic Filtering];
 filter --> marks[Create markers];

end

}}

{{#mermaid:graph LR subgraph SAM

 Covariance --> Beamformer;
 ortho[Processed MRI] --> Beamformer;
 Beamformer --> image["3D Images"];

end }}

{{#mermaid:graph LR subgraph SAM

 sam_cov --> sam_wts;
 sam_wts --> sam_3d;
 sam_3d --> AFNI;
 AFNI --> sam_wts;
 AFNI --> sam_cov;

end }}

  1. Create covariance matrices using sam_cov.
  2. Compute beamformer weights with sam_wts.
  3. sam_3d uses the weights to compute volumetric images of activity estimates.
  4. View them with AFNI.
  5. It didn't work, go back and try again.
  6. Nope, still didn't work, try this instead.