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
Copy Number Variation Informs fMRI-based Prediction of Autism Spectrum Disorder
Nicha C. Dvornek, Catherine Sullivan, James S. Duncan, Abha R. Gupta
MindDiffuser: Controlled Image Reconstruction from Human Brain Activity with Semantic and Structural Diffusion
Yizhuo Lu, Changde Du, Qiongyi zhou, Dianpeng Wang, Huiguang He