how to deal with Schaefer 2018 fsLR 1000 n missing data points?

[Saiwen Yu]

Dear CBIG group

As mentioned in this issue and this issue, the fsLR 1000-parcel version of the Schaefer 2018 atlas is missing two labels (553 and 903) when  transforming from fsaverage to fsLR.

I am conducting research on large-scale brain networks and aim to construct a functional network using the Schaefer 1000-parcel atlas. My data is in fsLR 32k space, so I have to use that atlas that includes the missing labels.

Do you have any advice on how to address this issue? The missing labels make data analysis challenging, especially when mapping from the atlas to fsLR 32k (e.g., converting 1000-parcel data to 64k space).

I would greatly appreciate any suggestions on how to resolve this.

[Thomas Yeo]

Hi Saiwen,

Can you elaborate a little more? The Schaefer parcellation was generated in fsaverage6 space. Since the Schaefer 1000 regions are a little small and the fsLR and fsaverage6 do not match exactly, so when transforming from fsaverage6 to fsLR, some parcels are inevitably lost. Don’t think the missing parcels can be recovered but if you are computing FC matrices in fsLR space you will end up with 998 x 998 matrices, but analyses can still proceed. What is the issue you face here? 

Regards,

Thomas

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