Brain Activity

Brain activity research focuses on understanding and decoding neural signals to gain insights into cognitive processes and neurological disorders. Current research heavily utilizes machine learning, employing diverse architectures like deep learning models (including Transformers, GANs, and diffusion models), graph neural networks, and other AI techniques to analyze data from various neuroimaging modalities (EEG, fMRI). This work aims to improve the accuracy of brain activity classification for disease diagnosis, reconstruct sensory experiences from neural data (images, videos, sounds), and ultimately enhance brain-computer interfaces and personalized therapeutic interventions.