> Yaroslav Halchenko wrote: > > I you only care about classification performances I bet you might soon > hear from Raj...
Ah, well, I can't resist an invitation like that! :-) Hi John: Definitely check out the hyper-alignment paper by Haxby et al. which Yarik sent along earlier in the thread: http://haxbylab.dartmouth.edu/publications/HGC+11.pdf It's an important paper, and it shows a way of mapping the voxel spaces of different subjects onto each other. Andy Connolly and I recently published a paper addressing a related but slightly different question, namely how to map the neural-similarity space of different subjects onto each other: http://raizadalab.org/papers/RaizadaConnolly_JoCN_2012_uncorrected_proofs.pdf Like you, we also used the Haxby 2001 data. The fact that Jim and the PyMVPA developers put that data online is a great service to the community. Our Matlab and PyMVPA analysis code is here: http://raizadalab.org/papers/RaizadaConnolly_SuppInfo_code.zip and a brief description of how to run it is in this doc: http://raizadalab.org/papers/RaizadaConnolly_JoCN_in_press_SuppInfo.pdf The code has a lot of comments in it, so hopefully it's reasonably clear. Our approach takes as its premise the idea that the commonalities across subjects may emerge from abstracting away from people's voxel-spaces, as people's voxel-space "neural fingerprints" tend to be somewhat subject-specific and idiosyncratic. So, we abstract from voxel-space to similarity-space, and then map people's similarity spaces onto each other using a simple permutation-based approach. The fact that the different subjects' VT-cortex masks do not cover exactly the same voxels is thereby side-stepped, as the analysis doesn't require the same voxels across subjects. In fact, the neural similarity-spaces match up across subjs, even when the sets of voxels that are used in each subj are highly diverse (that's shown in Fig.3 of our paper). I hope this helps. I'd be very interested indeed to hear your thoughts. Maybe try running our code on the Haxby data, and see if it suggests any useful lines of attack. Cheers, Raj _______________________________________________ Pkg-ExpPsy-PyMVPA mailing list [email protected] http://lists.alioth.debian.org/cgi-bin/mailman/listinfo/pkg-exppsy-pymvpa
