Latent neural integral operator models are evaluated on two fMRI datasets for encoding and decoding, with larger temporal windows and broader spatial context yielding improved performance and more structured latent representations.
Visual image reconstruction from human brain activity using a combination of multiscale local image decoders
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Nonlocal operator learning for fMRI encoding and decoding tasks
Latent neural integral operator models are evaluated on two fMRI datasets for encoding and decoding, with larger temporal windows and broader spatial context yielding improved performance and more structured latent representations.