Suggested Pipelines: Difference between revisions

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{{#mermaid:graph LR
{{#mermaid:graph LR


MEG Data --> Filtering
MEG Data --> Filtering;
Filtering --> Art["Artifact Removal"]
Filtering --> Art["Artifact Removal"];
subgraph Power
subgraph Power
Filtering --> sam_3d
Filtering --> sam["sam_3d/sam_3dc"];
Filtering --> sam_3dc
end
end
subgraph Connectivity
subgraph Connectivity
Filtering --> sam_power
Filtering --> sam_power;
end
end
}}
}}

Revision as of 10:19, 20 March 2019

Master Pipeline

Basic MRI Pre-Processing Workflow

For any experiment where you wish to localize data to the brain, the first step is MRI pre-processing. First, MEG data must be co-registered to the space of the MRI, either by manually placing fiducial points on the MRI, or through a semi-automated method where a digital head shape is aligned with a head surface. (Other algorithmic techniques are possible, these will be discussed later). For the purpose of source space reconstruction, the head can be modeled either as a collection of spheres, one per channel, (MultiSphere) or in a realistic fashion using the Nolte model.

Basic Resting State MEG processing

When examining resting state data, the end goals is usually to examine either static measures of

  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.