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== 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.
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Revision as of 10:12, 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.
- Create covariance matrices using sam_cov.
- Compute beamformer weights with sam_wts.
- sam_3d uses the weights to compute volumetric images of activity estimates.
- View them with AFNI.
- It didn't work, go back and try again.
- Nope, still didn't work, try this instead.