Electroencephalography (EEG) is a non-invasive technique used to record the electrical activity generated by the brain. This activity is visualized as oscillating wave patterns, commonly called “brainwaves.” Sensors placed on the scalp detect these tiny electrical signals, providing a real-time window into brain function. EEG helps researchers and clinicians understand the underlying dynamics of the central nervous system and is used to explore cognitive states and diagnose neurological conditions.
The Origin of Brainwaves
The electrical signals recorded by the EEG do not originate from the rapid electrical spikes known as action potentials. Instead, the signals are generated by the much slower electrical changes called postsynaptic potentials (PSPs). PSPs occur when neurotransmitters cross the synapse, changing the electrical charge of the receiving neuron. These potentials are the cumulative result of thousands of simultaneous excitatory and inhibitory inputs on the dendrites of neurons.
The most significant contributors to the EEG signal are the large pyramidal cells, which are numerous and oriented perpendicular to the cortical surface. Due to this parallel orientation, the electrical fields generated by the PSPs of millions of these cells sum together. This synchronized activity creates a measurable electrical field that extends through the brain tissue, skull, and scalp.
The Measurement Process
Capturing these minute electrical signals requires placing multiple electrodes directly onto the scalp. A conductive gel or paste is used before application to ensure a low-resistance connection between the sensor and the skin. These electrodes measure the voltage difference between two points, reflecting the electrical activity beneath the scalp.
The brain’s electrical signals measured at the scalp are very small, generally only a few microvolts (a millionth of a volt). Because of this low amplitude, the raw signal must be fed into high-gain differential amplifiers to increase the voltage for recording and analysis. A computer then digitizes this amplified signal, converting the analog electrical information into data points.
A significant challenge is the presence of artifacts, which are unwanted electrical signals that contaminate the data. These artifacts often originate from non-brain sources, such as muscle movement, eye blinks, or movement of the recording cables. Sophisticated signal processing techniques are used to identify and filter out these contaminating signals, ensuring the analyzed data accurately reflects genuine brain activity.
Classification of Brain Rhythms
The recorded EEG signal is analyzed by separating it into distinct frequency bands, categorized by cycles per second (Hertz or Hz). Each band correlates to a specific state of mental function or consciousness. The slowest rhythms are Delta waves (0.5 to 4 Hz), characteristic of deep, dreamless sleep. They are also the dominant rhythm observed in infants and in states of unconsciousness.
Theta waves (4 to 8 Hz) are associated with drowsiness, the onset of sleep, and deep meditative states. This frequency range is also linked to emotional processing and creative inspiration. Excessive Theta activity during conscious wakefulness in adults can sometimes indicate issues with attention or focus.
The Alpha band (8 to 12 Hz) is observed when an individual is in a relaxed, non-aroused state with their eyes closed. This rhythm represents calm wakefulness. When a person opens their eyes or begins to concentrate, the Alpha rhythm quickly decreases in amplitude, known as Alpha desynchronization.
Beta waves (13 to 30 Hz) dominate when the brain is actively engaged in focused attention, problem-solving, or decision-making. This fast rhythm indicates an alert, active mind processing information. When an individual is highly anxious or hyper-alert, the amplitude of Beta waves can increase significantly.
The Gamma band encompasses the fastest frequencies, typically above 30 Hz, sometimes extending up to 100 Hz or more. Gamma waves are involved in the binding of information from different brain regions to form a coherent perception, such as integrating sight and sound. They are associated with higher-level cognitive processing, intense concentration, and peak mental performance.
Practical Uses of EEG
Monitoring and interpreting brain rhythms makes EEG essential across clinical and research settings. Clinically, it is a primary diagnostic instrument for conditions like epilepsy, detecting and localizing the abnormal electrical discharges that characterize a seizure. EEG is also used extensively in sleep medicine to monitor frequency changes that delineate different sleep stages.
EEG assesses brain function in patients in a coma or those suspected of brain death. Analyzing the patterns helps clinicians determine the presence or absence of residual electrical activity, guiding medical decisions. Beyond diagnosis, EEG is used in cognitive neuroscience research to study how the brain processes information.
Researchers use EEG to track changes in brain activity associated with perception, memory encoding, and attentional shifts in real time. The technology’s high temporal resolution allows scientists to pinpoint the exact moment a cognitive event occurs. A rapidly expanding application is in the development of Brain-Computer Interfaces (BCIs), which allow individuals to control external devices directly with their thoughts, holding promise for restoring communication and mobility in people with severe paralysis.