fMRI Reconstruction

fMRI reconstruction aims to improve the quality and interpretability of functional magnetic resonance imaging data, addressing limitations like low signal-to-noise ratio and inter-subject variability. Current research focuses on developing advanced reconstruction models, including masked autoencoders, diffusion models, and novel neural networks, to enhance spatial and temporal resolution, enable cross-subject analysis, and facilitate the decoding of cognitive states from brain activity patterns. These advancements are significant for neuroscience, offering improved tools for understanding brain function and potentially leading to more accurate and efficient diagnostic and therapeutic applications.