Functional Magnetic Resonance Imaging
Functional Magnetic Resonance Imaging (fMRI) studies brain activity by measuring blood oxygenation levels, aiming to understand brain function and its relation to cognition and behavior. Current research heavily utilizes deep learning, including transformer networks, autoencoders, and diffusion models, to analyze high-dimensional fMRI data, improve spatial and temporal resolution, and decode cognitive states or even reconstruct visual imagery from brain activity. These advancements are improving diagnostic accuracy for neurological disorders like autism and Alzheimer's disease, and enabling novel applications such as personalized brain-computer interfaces and the development of more brain-like artificial intelligence models.
Papers
Cinematic Mindscapes: High-quality Video Reconstruction from Brain Activity
Zijiao Chen, Jiaxin Qing, Juan Helen Zhou
Brain Captioning: Decoding human brain activity into images and text
Matteo Ferrante, Furkan Ozcelik, Tommaso Boccato, Rufin VanRullen, Nicola Toschi
A Survey on the Role of Artificial Intelligence in the Prediction and Diagnosis of Schizophrenia
Narges Ramesh, Yasmin Ghodsi, Hamidreza Bolhasani