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pro vyhledávání: '"Beliy, Roman"'
Image-to-fMRI encoding is important for both neuroscience research and practical applications. However, such "Brain-Encoders" have been typically trained per-subject and per fMRI-dataset, thus restricted to very limited training data. In this paper w
Externí odkaz:
http://arxiv.org/abs/2406.12179
Combining Functional MRI (fMRI) data across different subjects and datasets is crucial for many neuroscience tasks. Relying solely on shared anatomy for brain-to-brain mapping is inadequate. Existing functional transformation methods thus depend on s
Externí odkaz:
http://arxiv.org/abs/2404.11143
Reconstructing natural videos from fMRI brain recordings is very challenging, for two main reasons: (i) As fMRI data acquisition is difficult, we only have a limited amount of supervised samples, which is not enough to cover the huge space of natural
Externí odkaz:
http://arxiv.org/abs/2206.03544
Reconstructing observed images from fMRI brain recordings is challenging. Unfortunately, acquiring sufficient "labeled" pairs of {Image, fMRI} (i.e., images with their corresponding fMRI responses) to span the huge space of natural images is prohibit
Externí odkaz:
http://arxiv.org/abs/1907.02431
Autor:
Gaziv, Guy, Beliy, Roman, Granot, Niv, Hoogi, Assaf, Strappini, Francesca, Golan, Tal, Irani, Michal
Publikováno v:
In NeuroImage 1 July 2022 254
