BrainSpace
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- What are you trying to do? I"m running gradient analysis onto phase-locking networks obtained from source-space MEG data. I have a 52-parcel resolution but am not particularly interested in identifying fine-grained functional boundaries anyway, I'm just looking for a way to embed each connectivity matrix into a one-dimensional array for later statistical analysis. Relatedly, I couldn't find definitive recommendations on how the choice of kernels and dimensionality reduction algorithm may affect the output? What would you recommend in my case?