Functional Magnetic Resonance Imaging (fMRI), Electroencephalography (EEG), and Magnetoencephalography (MEG) are three pivotal neuroimaging techniques used to measure brain activity, each with its unique strengths and applications. Which method we use depends on what we hope to learn from the brain and the context of our research.

fMRI
fMRI is a non-invasive technique that measures brain activity by detecting changes in blood flow. When a particular area of the brain is more active, it consumes more oxygen. The local blood flow to these regions increases to meet the oxygen demand. fMRI detects these changes through a mechanism known as Blood Oxygen Level Dependent (BOLD) contrast. By taking advantage of the different magnetic properties of oxygenated and deoxygenated blood, fMRI produces high-resolution images that reflect which parts of the brain are involved in specific mental processes. One significant advantage of fMRI is its excellent spatial resolution, which allows for the detailed mapping of brain activity to specific anatomical structures. However, fMRI has a relatively poor temporal resolution, meaning it cannot capture rapid changes in brain activity as quickly as other methods.

EEG
EEG measures electrical activity generated by neurons in the brain. Electrodes placed on the scalp detect the tiny electrical charges resulting from the collective activity of thousands or millions of neurons. EEG is particularly valuable for its excellent temporal resolution, providing real-time measurements of brain activity on the order of milliseconds. This makes EEG ideal for studying the brain’s fast dynamics, such as those involved in sensory processing, attention, and cognitive functions. However, the spatial resolution of EEG is relatively low compared to fMRI. It can be challenging to pinpoint the exact locations of the neural activity, as the signals detected by the scalp electrodes are a sum of the underlying electrical activity, which can spread and blur as it passes through the skull and scalp.

MEG
MEG measures the magnetic fields produced by neuronal electrical activity. Neurons generate small magnetic fields as electrical currents flow through them, and MEG sensors can detect these fields with high temporal precision. Similar to EEG, MEG offers excellent temporal resolution, capturing brain activity in real-time. One of MEG’s advantages over EEG is its better spatial resolution. While EEG signals are distorted by the skull and scalp, magnetic fields are less affected by these tissues, allowing for more accurate localization of brain activity. MEG is especially useful for studying neural dynamics and connectivity, as well as for localizing functional areas of the brain in surgical planning.