Brain Encoder

Brain encoding research focuses on developing computational models that predict brain activity (e.g., fMRI signals) in response to stimuli, primarily visual images. Current efforts concentrate on creating universal brain encoders, capable of generalizing across subjects and datasets, often employing convolutional neural networks (CNNs) and cross-attention mechanisms within voxel-centric architectures. These advancements promise to improve the efficiency and accuracy of brain-computer interfaces, accelerate neuroscience research by enabling large-scale data analysis, and facilitate the development of advanced applications in augmented and virtual reality.