Electroencephalography, or EEG, is a noninvasive method for recording the brain’s electrical activity from the scalp. It measures voltage fluctuations generated mainly by synchronized postsynaptic potentials in cortical neurons. These signals are typically in the microvolt range and are analyzed across characteristic frequency bands: delta, theta, alpha, beta, and gamma, each associated with different brain states such as sleep, relaxation, attention, and cognitive processing.

Research on EEG spans both technical development and applications in neuroscience, medicine, and technology. On the technical side, work focuses on improving spatial resolution, artifact removal, and signal processing. Advanced methods such as independent component analysis, machine learning, and time frequency decomposition are used to isolate brain activity from noise caused by muscle movement, blinking, or external electrical sources. High density EEG arrays and improved electrode materials aim to capture finer spatial detail while maintaining comfort and long term stability.

In clinical and cognitive research, EEG is used to study epilepsy, sleep disorders, neurodegenerative diseases, and psychiatric conditions. It can detect abnormal rhythms, such as epileptic spikes, and characterize sleep stages through distinct oscillatory patterns. In cognitive neuroscience, EEG helps link temporal dynamics of brain activity to perception, attention, memory, and decision making with millisecond precision.

A growing research area is brain computer interfaces, where EEG signals are translated into control commands for communication or device control. This includes assistive technologies for individuals with severe motor impairments and experimental neurofeedback systems that train users to modulate their own brain rhythms for therapeutic or performance related goals.