What is EEG (Electroencephalography)?
Electroencephalography (EEG) is a non-invasive neuroimaging technique that measures electrical activity in the brain through electrodes placed on the scalp. It records the electrical signals generated by the brain’s neurons, which can be analyzed to provide insights into various cognitive processes, emotional states, and neurological disorders. Due to its high temporal resolution, EEG is particularly useful for studying the dynamics and timing of brain activity, although it has limited spatial resolution compared to other neuroimaging techniques.
Key Features of EEG
EEG is a non-invasive method of measuring brain activity, requiring only the placement of electrodes on the scalp. This makes it a relatively safe and accessible option for researchers and clinicians to study the brain’s electrical activity.
High Temporal Resolution
One of the main advantages of EEG is its high temporal resolution, which allows researchers to capture changes in brain activity on the order of milliseconds. This makes EEG particularly suitable for studying the timing and dynamics of cognitive processes, such as attention, perception, and decision-making.
Limited Spatial Resolution
Although EEG provides excellent temporal resolution, it has limited spatial resolution. This means that it can be challenging to determine the exact location of the neural sources generating the recorded electrical signals. Other neuroimaging techniques, such as fMRI or MEG, may be better suited for spatial localization.
Applications and Research Areas
EEG is widely used in the diagnosis and monitoring of neurological disorders, such as epilepsy, sleep disorders, and encephalopathies. It can help identify abnormal patterns of brain activity associated with these conditions and guide treatment decisions.
In cognitive neuroscience, researchers use EEG to study the neural mechanisms underlying various cognitive processes, such as attention, perception, memory, and decision-making. By analyzing specific features of the EEG signal, such as event-related potentials (ERPs), researchers can gain insights into the timing and dynamics of these processes.
EEG has been used to develop brain-computer interfaces (BCIs), which allow users to control devices or software through their brain activity. By analyzing the EEG signals associated with specific thoughts or mental states, BCIs can be designed to respond to user commands, offering potential applications in assistive technology, gaming, and communication.