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Found 5 papers, 3 papers with code
Modality-Agnostic fMRI Decoding of Vision and Language
Previous studies have shown that it is possible to map brain activation data of subjects viewing images onto the feature representation space of not only vision models (modality-specific decoding) but also language models (cross-modal decoding).
Reconstruction of Perceived Images from fMRI Patterns and Semantic Brain Exploration using Instance-Conditioned GANs
Reconstructing perceived natural images from fMRI signals is one of the most engaging topics of neural decoding research.
Multimodal neural networks better explain multivoxel patterns in the hippocampus
The human hippocampus possesses "concept cells", neurons that fire when presented with stimuli belonging to a specific concept, regardless of the modality.
Reconstructing Natural Scenes from fMRI Patterns using BigBiGAN
Then, we applied this mapping to the fMRI activity patterns obtained from 50 new test images from 50 unseen categories in order to retrieve their latent vectors, and reconstruct the corresponding images.
Reconstructing Faces from fMRI Patterns using Deep Generative Neural Networks
While objects from different categories can be reliably decoded from fMRI brain response patterns, it has proved more difficult to distinguish visually similar inputs, such as different instances of the same category.
Human-Computer Interaction Neurons and Cognition
