Electroencephalography (EEG) and Magnetoencephalography (MEG) are both non-invasive tools used in neuroscience to map and measure brain function in real-time. They share the goal of understanding how nerve cells communicate during thought, perception, and action. Both techniques detect electromagnetic signals resulting from neural activity. Specifically, EEG and MEG measure the collective effect of postsynaptic potentials—small electrical currents generated when neurons communicate at their synapses. The primary difference lies in the physical phenomenon each technology is designed to detect.
Electroencephalography (EEG): Measuring Electrical Signals
Electroencephalography works by placing small metal sensors, known as electrodes, directly onto the scalp. These electrodes are sensitive to the tiny voltage fluctuations that occur as groups of neurons fire synchronously. The electrodes capture the electrical potential difference, which is then amplified and recorded as brain waves. This method is primarily sensitive to electrical currents that flow radially, or perpendicular to the brain’s surface, meaning it best detects activity originating from the crests of the cortical folds, known as gyri.
EEG offers exceptional temporal resolution, tracking changes in brain activity with millisecond precision. However, the electrical signals must pass through several layers, including brain tissue, cerebrospinal fluid, the skull, and the scalp. These tissues distort and smear the electrical signals as they travel toward the surface. This distortion significantly limits the precision with which EEG can pinpoint the location of the activity, particularly for sources deeper within the brain.
Magnetoencephalography (MEG): Tracking Magnetic Fields
Magnetoencephalography measures the minute magnetic fields produced as a byproduct of the same electrical currents detected by EEG. MEG is most sensitive to magnetic fields generated by currents flowing tangentially, or parallel to the brain’s surface, meaning it primarily captures activity originating in the deep grooves of the cortex, known as sulci.
Detecting these magnetic fields is a major technical challenge because the signals are incredibly small, measuring in the femto-tesla range—billions of times weaker than the Earth’s magnetic field. To capture such faint signals, MEG systems rely on sensors called Superconducting Quantum Interference Devices (SQUIDs). These sensors must be kept at extremely low temperatures using liquid helium and are housed within a magnetically shielded room to block out environmental magnetic noise. Magnetic fields pass through the skull and scalp without being distorted, allowing MEG to achieve significantly better spatial localization of the neural source than EEG.
Comparing EEG and MEG: Resolution, Cost, and Mobility
Both EEG and MEG offer outstanding temporal resolution, capable of capturing brain events in the millisecond range, providing a fast, dynamic view of neural activity. The most significant difference is in spatial resolution, where MEG excels due to the magnetic transparency of the skull. While EEG can localize activity with an accuracy of several centimeters, MEG can pinpoint the source of activity to within a few millimeters.
MEG’s superior localization precision requires substantial technical overhead. The need for SQUID sensors, liquid helium cooling, and a dedicated magnetically shielded room makes the MEG system expensive, large, and immobile. In contrast, EEG equipment is low-cost, portable, and widely available in clinical settings, often consisting of a cap of electrodes and a small amplifier.
Because each technique is sensitive to different orientations of electrical current in the brain, they provide complementary information. Researchers often use them in combination to leverage the high temporal resolution and portability of EEG with the high spatial resolution of MEG, allowing for a more complete picture of brain function.
Clinical and Research Applications
Both EEG and MEG are used in clinical neurology and cognitive neuroscience research. In a medical context, a primary application is the diagnosis and monitoring of epilepsy. They locate the area in the brain where abnormal electrical discharges originate, which helps determine treatment plans, especially for patients considering surgery.
MEG is frequently used for pre-surgical functional mapping, helping neurosurgeons identify eloquent cortex, which includes areas responsible for functions like language and motor control. This mapping ensures these areas are avoided during the surgical removal of tumors or epileptic tissue. In research, these tools map cognitive processes such as memory, auditory processing, and language comprehension, and contribute to studying the progression of neurological conditions like Alzheimer’s.