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Introduction
Introduction
EEG is one of the oldest yet most insightful functional brain imaging technique. It measures electrical activity of the brain from electrodes placed on the scalp (usually between 64-256 electrodes), allowing us to study the brain's responses real-time.
EEG is widely used in research to study brain function, offering excellent temporal resolution. By analyzing different wave types, EEG helps us understand attention, perception, memory, and sensory processing. It also plays a key role in studying event-related potentials (ERPs), which represent the brain's responses to specific stimuli, such as those involved in decision-making processes.
The name comes from the Greek words “enkephalo” (brain) and “graphein” (to write). There are two types of recorded EEG signals:
SPONTANEOUS SIGNALS
SPONTANEOUS SIGNALS
These signals occur without any specific stimulus, often linked to an individual's natural brain state. Because of this, spontaneous EEG is widely used to evaluate altered states of consciousness or to monitor brain activity in clinical settings.
EVENT RELATED POTENTIALS (ERPs)
EVENT RELATED POTENTIALS (ERPs)
ERPs are brain responses triggered by specific events or stimuli. To capture these signals, EEG often requires repeated presentations of stimuli to filter out background noise. ERPs help researchers understand how the brain processes different types of information.
ERPs can be analyzed in two ways:
Time-Locked Averaging: This technique synchronizes multiple trials to highlight consistent brain responses to stimuli. It reduces noise, making event-specific signals clearer.
Spectral Analysis: This approach breaks down EEG signals into various frequency bands (e.g., alpha, beta, gamma), providing insights into brain activity tied to specific events.
KEY POINTS
KEY POINTS
WHAT DOES THE EEG REFLECT?
WHAT DOES THE EEG REFLECT?
The EEG Reflects the immediate mass action of neural networks, providing a direct and noninvasive window onto human brain function. As it has a high temporal resolution, it not only measures generations at one specific time moment, but also the possible generators of rhythmic oscillations in different frequency ranges.
WHERE DO THE SIGNALS COME FROM?
WHERE DO THE SIGNALS COME FROM?
The signal of the EEG primarly detects dipoles created by pyramidal neurons in the cortex. These neurons are aligned so that their dendrites (branch like structures) point towards the surface of the cortex. The activation of a pyramidal neuron leads to an excitatory post synaptic potential (EPSPs), which inside the neurons means a ion concentration gradient, which forms a dipole (see Action Potentials part to understand more).
WHEN ARE THE DIPOLES DETECTED?
WHEN ARE THE DIPOLES DETECTED?
When there is a separation of charges between two regions, a dipole is formed. The sink is created by the inflow of Na+ ions, which leaves the area outside the neuron more negative than before. The source is located at the cell body, where a positive charge is formed as K+ ions flow out, making the surrounding area more positive. When enough neurons are synchronised, the dipole can be detected on the surface of the scalp using the EEG. The major signal that the EEG recollects are made by extended patches of grey matter, polarised by synchronous synaptic input either in an oscillatory manner or as transient evoked activity. The patches contain thousands of cortical columns, and perpendicular to these cortical surfaces lie large pyramidal cells. The different layers correspond to different synaptic connections of different structures.
WHY CAN'T THE EEG DETECT SINGLE NEURONS?
WHY CAN'T THE EEG DETECT SINGLE NEURONS?
The EEG can detect the action of neural networks, but not individual neurons. This is because the spike amplitude of a synapse becomes very weak (<60 microV) beyond 0.05mm. As the EEG is more than 2cm away from the brain tissue this makes it impossible to measure individual spikes. Therefore, the EEG measures the voltage change of the post synaptic potentials, which are generated at the dendrites of neurons which are large and perpendicular to the cortical surface and their electrical fields add up and project out of the scalp. [2]
references:
[1] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2849100/
. [2] https://www.cambridge.org/core/books/electrical-neuroimaging/DB6F5991EF51762172A59823E132905E
images: 1,2: AI
3: Advanced forward models for EEG source imaging - Scientific Figure on ResearchGate. Available from: https://www.researchgate.net/figure/Simplified-illustration-of-the-extracellular-currents-represented-by-current-sinks-and_fig8_294430587 [accessed 14 Nov 2024]Page updated
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