Electroencephalography, or EEG, is a noninvasive method for recording the brain’s electrical activity using electrodes placed on the scalp. It primarily measures the summed postsynaptic potentials of large populations of cortical neurons, especially pyramidal cells aligned perpendicular to the cortical surface. These signals are filtered, amplified and digitized for analysis.

EEG is characterized by rhythmic activity across several frequency bands, each associated with different functional states: delta (0.5–4 Hz) in deep sleep, theta (4–8 Hz) in drowsiness and some cognitive processes, alpha (8–13 Hz) in relaxed wakefulness with eyes closed, beta (13–30 Hz) in active thinking and motor activity, and gamma (>30 Hz) in higher-order processing and binding of information. Modern analysis uses time frequency methods, connectivity metrics and source localization to interpret these oscillations and their interactions.

EEG is widely used in clinical practice to diagnose and monitor epilepsy, sleep disorders, encephalopathies, coma and brain death, as well as to guide anesthesia depth. In research, it is crucial for studying perception, attention, memory and language with millisecond temporal resolution, enabling the detection of event related potentials that reflect stimulus processing and decision making.

Although spatial resolution is limited compared with imaging techniques like fMRI, EEG is inexpensive, portable and safe, and can be applied across the lifespan, including in newborns. Recent work integrates EEG with other modalities and advances in machine learning, improving brain computer interfaces and enabling applications such as communication for paralyzed patients, neurofeedback therapies and real time monitoring of brain states in everyday environments.