How Do EEG Sensors Work? The Science Behind Brainwave Detection

The Role of Neurons and Electrical Activity in EEG Measurements

Electroencephalography (EEG) sensors are the fundamental tools that allow us to measure the brain’s electrical activity non-invasively. To understand how these sensors work, it’s crucial to grasp the role of neurons and their electrical signaling in generating the signals that EEG detects. The brain is a vast network of billions of neurons, specialized cells that communicate with each other through electrochemical signals. This communication is the basis of all brain function, from basic sensory processing to complex thought and emotion.

Neurons: The Building Blocks of the Brain

Neurons have a unique structure that enables them to transmit information. A typical neuron consists of:

• Cell Body (Soma): Contains the nucleus and other essential cellular machinery.
• Dendrites: Branch-like extensions that receive signals from other neurons.
• Axon: A long, slender projection that carries signals away from the cell body to other neurons, muscles, or glands.
• Synapses: Specialized junctions where the axon of one neuron communicates with the dendrites or cell body of another neuron.

Electrochemical Signaling: The Language of Neurons

Neurons communicate using a combination of electrical and chemical signals.

1. Resting Membrane Potential: When a neuron is not actively transmitting signals, it maintains a difference in electrical potential across its cell membrane. This is called the resting membrane potential, and it’s typically around -70 millivolts (mV), meaning the inside of the neuron is negatively charged compared to the outside. This potential difference is maintained by ion pumps and channels that selectively control the flow of ions (charged particles, such as sodium (Na+), potassium (K+), chloride (Cl-), and calcium (Ca2+)) across the membrane.
2. Action Potentials: When a neuron receives sufficient stimulation from other neurons, it can generate an action potential, a rapid and brief change in its membrane potential. This is the primary means of long-distance communication within the brain. The process unfolds as follows:
   • Depolarization: If the incoming signals from other neurons depolarize the neuron’s membrane (make it less negative) to a threshold level, voltage-gated sodium channels open, allowing a rapid influx of Na+ ions into the neuron. This causes a sharp spike in the membrane potential, making it positive.
   • Repolarization: Voltage-gated potassium channels then open, allowing K+ ions to flow out of the neuron. This restores the negative resting membrane potential.
   • Hyperpolarization: The membrane potential may briefly become even more negative than the resting potential (hyperpolarization) before returning to the resting state.
   • Refractory Period After an action potential, there is a brief refractory period during which the neuron is less likely, or completely unable, to fire another action potential.
3. Synaptic Transmission: When an action potential reaches the end of the axon, it triggers the release of neurotransmitters, chemical messengers that diffuse across the synapse and bind to receptors on the postsynaptic neuron (the receiving neuron).
4. Postsynaptic Potentials (PSPs): The binding of neurotransmitters to receptors on the postsynaptic neuron causes ion channels to open or close, leading to a change in the electrical potential across the postsynaptic neuron’s membrane. These changes are called postsynaptic potentials (PSPs). PSPs are the primary source of the EEG signal.
   • Excitatory Postsynaptic Potentials (EPSPs): These depolarize the postsynaptic neuron, making it more likely to fire an action potential. EPSPs are typically caused by the influx of Na+ ions.
   • Inhibitory Postsynaptic Potentials (IPSPs): These hyperpolarize the postsynaptic neuron, making it less likely to fire an action potential. IPSPs are often caused by the influx of Cl- ions or the efflux of K+ ions.

Summation of PSPs: The Key to EEG Signals

EEG does not directly measure action potentials. Action potentials are too brief and localized to generate a measurable signal at the scalp. Instead, EEG primarily reflects the summed activity of postsynaptic potentials (PSPs). There are several reasons for this:

• Duration: PSPs last much longer (tens to hundreds of milliseconds) than action potentials (about 1 millisecond). This longer duration allows PSPs from multiple neurons to summate more effectively over time.
• Spatial Alignment: PSPs occur primarily in the dendrites of neurons. In the cerebral cortex (the outer layer of the brain), many neurons, particularly pyramidal neurons, have their dendrites arranged in parallel. This parallel arrangement allows the electrical fields generated by PSPs in many neurons to summate spatially, creating a stronger signal.
• Dipole Formation: Pyramidal neurons have long, apical dendrites that extend towards the surface of the cortex. When EPSPs occur in these apical dendrites, a current flow is created, forming an electrical dipole (a separation of positive and negative charge). The aligned dipoles of many pyramidal neurons summate to produce a measurable potential difference at the scalp.

In essence, the EEG signal represents the synchronous activity of large populations of neurons, primarily reflecting the summed postsynaptic potentials in the dendrites of cortical pyramidal neurons. The synchronized activity of thousands, or even millions, of neurons is necessary to generate a signal strong enough to be detected at the scalp.

Signal Transmission: How Electrodes Pick Up Brainwave Data

The process of converting the brain’s electrical activity into a measurable signal that can be analyzed involves several key steps, all facilitated by the EEG electrodes and associated equipment.

1. Volume Conduction: The electrical potentials generated by the synchronous activity of neurons propagate through the brain tissue, cerebrospinal fluid, skull, and scalp. These tissues act as a volume conductor, meaning that the electrical current spreads out in three dimensions. The amplitude of the signal decreases with distance from the source, and the signal is also distorted by the different conductivities of the various tissues.
2. Electrode Placement: EEG electrodes are small, conductive discs (typically made of silver/silver chloride (Ag/AgCl), gold, or tin) that are placed on the scalp at specific locations. The placement is crucial for detecting activity from specific brain regions. The international 10-20 system is a standardized method for electrode placement, ensuring consistency across different recordings and laboratories. This system uses anatomical landmarks on the head (nasion, inion, and preauricular points) to define a coordinate system for electrode placement. Electrode locations are designated by letters (representing the underlying brain lobe: F – Frontal, T – Temporal, C – Central, P – Parietal, O – Occipital) and numbers (odd numbers for the left hemisphere, even numbers for the right hemisphere, and ‘z’ for the midline).
3. Electrode-Electrolyte Interface: To ensure good electrical contact between the electrode and the scalp, a conductive gel or paste is typically used. This gel contains electrolytes (ions) that can carry current. The interface between the metal electrode and the electrolyte is crucial for signal transduction.
4. Electrochemical Transduction: At the electrode-electrolyte interface, electrochemical reactions occur. These reactions involve the transfer of electrons between the metal and the ions in the electrolyte. This process converts the ionic current flowing in the brain tissue into an electronic current that can be measured by the amplifier. The specific reactions depend on the electrode material. For Ag/AgCl electrodes, the key reaction is: AgCl + e- ↔ Ag + Cl- This reversible reaction establishes a stable electrical potential at the electrode-electrolyte interface. Changes in the ionic current in the brain tissue (due to neuronal activity) cause small changes in this potential. These changes are what the EEG system detects.
5. Differential Amplification: EEG recordings typically use differential amplifiers. This means that the amplifier measures the voltage difference between two electrodes. This is crucial for reducing noise.
   • Active Electrode: The electrode placed over the brain region of interest.
   • Reference Electrode: Ideally, an electrode placed at a location with minimal brain activity. Common reference locations include the earlobes, mastoid process (bone behind the ear), or the nose. However, there is no truly “inactive” reference point on the head.
   • Ground Electrode: A third electrode, often placed on the forehead or earlobe, provides a common ground for the system, further reducing noise.
   The differential amplifier subtracts the voltage at the reference electrode from the voltage at the active electrode. This cancels out common-mode noise, which is electrical noise that affects both electrodes equally (e.g., interference from power lines, muscle activity). The remaining signal, representing the difference in electrical activity between the two electrode locations, is then amplified.
6. Analog-to-Digital Conversion: The amplified analog signal is then converted into a digital signal by an analog-to-digital converter (ADC). This involves sampling the signal at regular intervals (the sampling rate, measured in Hertz) and quantizing the amplitude of the signal at each sample point. The sampling rate must be at least twice the highest frequency of interest in the EEG signal (Nyquist-Shannon sampling theorem) to avoid aliasing (distortion of the signal).
7. Signal Processing and Display: The digitized EEG signal is then processed by a computer. This can involve various steps, such as filtering to remove artifacts (unwanted signals, such as eye blinks or muscle movements), frequency analysis (e.g., using the Fourier transform to decompose the signal into its constituent frequencies), and visualization of the data as waveforms or topographic maps.

In summary, EEG electrodes pick up brainwave data by transducing the ionic currents generated by neuronal activity into electronic currents, which are then amplified, digitized, processed, and displayed. The differential amplification technique is crucial for reducing noise and isolating the brain’s electrical activity.

Understanding EEG Waveforms: Frequency, Amplitude, and Signal Strength

The raw EEG signal is typically displayed as a waveform, a graph of voltage (on the vertical axis) versus time (on the horizontal axis). This waveform is not a simple, regular wave; it’s a complex, fluctuating signal that reflects the summed activity of many neurons. To interpret EEG waveforms, we need to understand the concepts of frequency, amplitude, and signal strength.

Frequency:

Frequency refers to the number of times a wave completes a full cycle (from peak to trough to peak) per second. It is measured in Hertz (Hz). EEG activity is categorized into different frequency bands, each associated with different brain states and cognitive functions:

• Delta (δ) (0.5 – 4 Hz): The slowest brainwaves, dominant during deep, dreamless sleep (stages 3 and 4 of non-rapid eye movement (NREM) sleep). High-amplitude delta waves are normal in infants and young children. In adults, high delta activity during wakefulness can indicate brain injury or disease.
• Theta (θ) (4 – 8 Hz): Associated with drowsiness, light sleep (stage 1 NREM sleep), and the transition between sleep and wakefulness. Also involved in memory processing, particularly in the hippocampus. Theta activity is also observed during meditative states. Excessive theta during wakefulness can be linked to attention deficits.
• Alpha (α) (8 – 12 Hz): Prominent when awake but relaxed with eyes closed. Most easily observed over the occipital cortex (visual processing area). Alpha waves represent a state of relaxed alertness, or “idling.” Alpha waves are often used in biofeedback.
• Beta (β) (12 – 30 Hz): Associated with active thinking, problem-solving, concentration, and alertness. The dominant frequency during wakefulness when engaged in cognitive tasks or experiencing sensory stimulation. High-frequency beta can be associated with anxiety and stress.
• Gamma (γ) (30 – 100+ Hz): The fastest brainwaves, associated with higher-order cognitive functions, such as perception, attention, and consciousness. Thought to reflect synchronized activity of neuronal networks and are believed to play a crucial role in binding different sensory inputs into a coherent perception.

Amplitude:

Amplitude refers to the height of the wave, representing the strength or intensity of the electrical activity. It is measured in microvolts (µV). Amplitude reflects the degree of synchronous firing of neurons.

• High Amplitude: Indicates that a large number of neurons are firing together in a coordinated manner. This is often seen in slower frequency bands, such as delta during deep sleep, or alpha during relaxed wakefulness.
• Low Amplitude: Suggests less synchronized activity, with neurons firing more independently. This is typical of faster frequency bands, such as beta during active thinking.

Signal Strength:

Signal strength is closely related to amplitude. It represents the overall power of the EEG signal. Signal strength is affected by several factors:

• Number of Synchronized Neurons: The more neurons that fire synchronously, the stronger the signal.
• Distance from Source: The closer the electrodes are to the source of the electrical activity, the stronger the signal.
• Conductivity of Tissues: The skull and scalp attenuate the EEG signal, reducing its strength. Thicker skulls or poor electrode contact can reduce signal strength.
• Artifacts: Contamination.

Interpreting EEG Waveforms:

Analyzing EEG waveforms involves examining the frequency, amplitude, and spatial distribution of the brainwave activity. Clinicians and researchers look for:

• Dominant Frequency: The frequency band with the highest amplitude. This can indicate the overall brain state (e.g., awake and alert, drowsy, asleep).
• Changes in Frequency and Amplitude: Shifts in frequency or amplitude over time can indicate changes in brain state or cognitive processing.
• Asymmetry: Differences in activity between the two hemispheres of the brain can be indicative of neurological problems.
• Abnormal Patterns: Specific EEG patterns, such as spikes, sharp waves, or spike-and-wave complexes, are characteristic of seizures.
• Topographic Distribution: The spatial distribution of brainwave activity across the scalp can provide information about the location of the underlying neural sources.

EEG waveform analysis is a complex skill that requires extensive training and experience. It’s not simply a matter of identifying individual waves; it’s about understanding the overall pattern of brain activity and how it relates to the individual’s state and behavior. Modern EEG analysis often involves computer-assisted techniques, such as spectral analysis (using the Fourier transform to decompose the signal into its constituent frequencies) and time-frequency analysis (examining how the frequency content of the signal changes over time).