Hello, I have a question about MSMall, as I am trying to better understand how it is performing the alignment in the HCP Pipelines. My understanding is that MSMall uses areal features that include myelin maps and resting state network maps for alignment. MSM uses a discrete optimization approach and optimizes across the surface until features on the moving surface best match the target surface and it does this over a series of iterations. In the HCP Pipelines, how is this being done for the different modalities? Is it doing it for each modality on its own or is it creating a single, multivariate CostFunctionweighted mask and using it as the –refweight option? If it’s the latter, what are the actual weights that are used as default in the pipeline for the different modalities?
Any help with my understanding is appreciated! Thanks! Mark _______________________________________________ HCP-Users mailing list HCP-Users@humanconnectome.org http://lists.humanconnectome.org/mailman/listinfo/hcp-users
