Electroencephalography

Electroencephalography measures brain activity through electrodes on the scalp or, in intracranial recordings, within the brain, enabling study of cognition and applications such as seizure monitoring, sleep staging, and brain-computer interfaces. Methods range from spectral and Riemannian features to convolutional and recurrent networks, graph models, Transformers, and state-space models; self-supervised learning and generative methods aim to use large amounts of unlabeled data. Foundation models are being tested across clinical classification, motor imagery, and event detection, but their advantages over task-specific models are not consistent. A central challenge is reliable generalization across people, hospitals, and electrode montages, alongside evaluation that prevents data leakage and measures clinical usefulness rather than accuracy alone.