Hello,

Thank you so much for publishing these amazing data/toolbox/results.

I tried to get the data from both the Generic_Object_Decoding project (Kamitani2017) and the Deep Image Reconstruction project (Shen2019) with the following download link:
Kamitani2017: https://figshare.com/articles/dataset/Generic_Object_Decoding/7387130
Shen2019: https://figshare.com/articles/dataset/Deep_Image_Reconstruction/7033577

However, when I try to extract the voxels from visual cortex (i.e., 'ROI_VC'), I found these two datasets differ a lot in size.
The number of VC voxels in the Kamitani2017 dataset is 3444, 4979, 5355, 4656, 6237 for each subject respectivel;
however, the number of VC voxels in Shen2019 dataset is 11726 for all the participants.

I used bdpy toolbox to extract the voxels. And I used this function to get the VC ROIs - bdata.select('ROI_VC')

Could you please kindly have a look and see if this is normal?

Thanks!