10.1 Electroencephalography (EEG) and event-related potentials (ERP)
4 min read•august 16, 2024
EEG and ERPs are powerful tools for studying brain activity. They measure electrical signals from the scalp, giving us a window into neural processes. These techniques offer high temporal resolution, helping researchers track rapid changes in brain function.
EEG records ongoing brain waves, while ERPs capture responses to specific events. Both methods have wide-ranging applications in neuroscience, from understanding cognitive processes to diagnosing neurological disorders. They're key players in unraveling the mysteries of the brain.
EEG Recording and Analysis
Principles of EEG
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- (EEG) measures electrical activity in the brain using placed on the scalp
- EEG recordings capture summation of postsynaptic potentials from large populations of neurons (primarily pyramidal cells in cerebral cortex)
- 10-20 system standardizes electrode placement for reproducibility across subjects and studies
- Voltage differences recorded between active electrodes and reference electrode (linked mastoids, average reference)
Signal Processing Techniques
- Filtering removes unwanted frequency components from raw EEG data
- eliminates non-neural signals (eye blinks, muscle activity)
- (ICA) separates mixed signals into independent sources
- decomposes EEG signals into constituent frequencies
- Fourier Transform converts time-domain signal to frequency domain
- Wavelet analysis provides time-frequency representation of non-stationary signals
Advanced EEG Analysis
- estimates neural generators of scalp-recorded activity
- Examples: LORETA, beamforming
- Connectivity measures quantify functional interactions between brain regions
- Examples: ,
- Machine learning classifies EEG patterns for brain-computer interfaces
EEG Waveforms and Frequency Bands
Characteristics of EEG Waveforms
- reflects strength of neural activity (typically 10-100 μV in adults)
- Frequency indicates oscillatory rate of waveform (measured in Hz)
- Morphology describes shape and pattern of waveform
- Brain state and cognitive processes influence waveform properties
Major EEG Frequency Bands
- (0.5-4 Hz)
- Associated with deep sleep
- Prominent in infants and certain pathological conditions (coma)
- (4-8 Hz)
- Linked to drowsiness, meditation, memory processes
- Prominent in hippocampus and frontal midline regions
- (8-13 Hz)
- Dominant during relaxed wakefulness, especially with eyes closed
- Thought to reflect cortical idling or inhibition
- (13-30 Hz)
- Associated with active, alert mental states
- Prominent during cognitive tasks and motor behavior
- (30-100+ Hz)
- Linked to higher-order cognitive processes (attention, perception, consciousness)
- May reflect binding of distributed neural information
Clinical and Research Applications
- Relative power of frequency bands provides information about brain states
- Spatial distribution of bands indicates regional brain activity
- Abnormal patterns aid diagnosis of neurological disorders (epilepsy, sleep disorders)
- Neurofeedback training modulates specific frequency bands to improve cognitive function
Event-Related Potentials in Neuroscience
Fundamentals of ERPs
- (ERPs) time-locked EEG responses to specific events
- Signal averaging technique extracts ERPs from ongoing EEG
- Improves signal-to-noise ratio by canceling out random background activity
- ERPs reveal temporal dynamics of cognitive processes with millisecond precision
- Characterized by polarity, , and scalp distribution
ERP Components and Processing Stages
- Early components reflect sensory processing
- : auditory stimulus detection (~100 ms)
- : feature detection and selective attention (~200 ms)
- Later components associated with higher-order cognition
- : semantic processing (300-500 ms)
- : context updating, decision-making (300-600 ms)
- (MMN) investigates pre-attentive auditory processing
- Elicited by deviant stimuli in oddball paradigms
- Peaks around 150-250 ms after stimulus onset
Applications in Cognitive Neuroscience
- ERPs widely used to study various cognitive functions:
- Attention: spatial cueing tasks, visual search paradigms
- Language processing: syntactic violations, semantic priming
- Memory: recognition tasks, working memory load manipulations
- Decision-making: gambling tasks, perceptual decision paradigms
- Clinical applications assess cognitive function in neurological disorders
- Examples: Alzheimer's disease, schizophrenia, ADHD
ERP Components and Cognitive Processes
Classic ERP Components
- P300 component
- Positive deflection 300-600 ms post-stimulus
- Associated with context updating, oddball detection
- Amplitude increases with task relevance and stimulus infrequency
- N400 component
- Negative deflection peaking around 400 ms
- Linked to semantic processing and integration
- Larger amplitude for semantically incongruent stimuli
- Error-related negativity (ERN)
- Occurs following error commission (~50-100 ms after response)
- Reflects error detection and conflict monitoring processes
- Generated in anterior cingulate cortex
Motor and Perceptual ERPs
- Lateralized readiness potential (LRP)
- Observed prior to voluntary movements
- Used to study motor preparation and response selection
- Calculated as difference between contralateral and ipsilateral motor cortex activity
- N170 component
- Face-sensitive ERP peaking around 170 ms post-stimulus
- Larger amplitude for faces compared to other visual stimuli
- Generated in fusiform and inferior temporal regions
Cognitive State ERPs
- (CNV)
- Slow negative potential between warning and imperative stimuli
- Reflects anticipation and motor preparation
- Amplitude modulated by task demands and motivation
- P600 component
- Positive deflection around 600 ms post-stimulus
- Associated with syntactic processing and reanalysis
- Elicited by grammatical violations and complex sentence structures
Key Terms to Review (33)
Alpha waves: Alpha waves are brainwave patterns that oscillate at a frequency of 8 to 12 Hz, typically observed during states of relaxation and calm alertness. These waves are primarily produced in the occipital lobe when the eyes are closed, indicating a state of wakeful rest or light meditation, and play a crucial role in various cognitive functions such as attention and memory.
Amplitude: Amplitude refers to the height of a wave, which is an important measure of its strength or intensity. In the context of brain activity, amplitude reflects the degree of electrical activity in neural oscillations, often measured using techniques like EEG. Higher amplitudes indicate stronger neural responses, while lower amplitudes suggest weaker responses, providing insights into cognitive processes and states of consciousness.
Artifact rejection: Artifact rejection is the process of identifying and removing unwanted signals or noise from data recordings, especially in the context of brain activity measurements like electroencephalography (EEG) and event-related potentials (ERP). This is crucial because artifacts can arise from various sources, such as muscle movement, eye blinks, or external electrical interference, which can distort the actual neural signals being studied. By effectively rejecting these artifacts, researchers can ensure more accurate interpretations of cognitive processes and brain function.
Beta Waves: Beta waves are a type of brainwave pattern characterized by high frequency and low amplitude, typically ranging from 12 to 30 Hz. They are associated with active thinking, alertness, and concentration, playing a crucial role in cognitive processes and active engagement with the environment.
Cognitive Processing: Cognitive processing refers to the mental operations involved in acquiring, storing, retrieving, and using information. It encompasses various functions such as perception, attention, memory, and problem-solving, all of which are essential for understanding how we interact with our environment and make decisions. In the context of brain activity, cognitive processing can be observed through techniques like electroencephalography (EEG) and event-related potentials (ERP), which measure the electrical activity of the brain as it engages in different cognitive tasks.
Coherence: Coherence refers to the degree to which different brain regions synchronize their electrical activity over time, reflecting a unified and organized pattern of neural communication. This synchronization can be crucial for understanding how various cognitive processes are coordinated, as it indicates the functional connectivity between regions during tasks or states of rest. In the context of brain measurements like EEG and ERP, coherence provides insights into how well regions work together, revealing information about brain function and cognitive processing.
Contingent Negative Variation: Contingent negative variation (CNV) is an event-related potential observed in EEG studies that occurs during a waiting period for an anticipated stimulus, typically reflected as a negative shift in electrical activity. This phenomenon is believed to be linked to cognitive processes related to attention, expectation, and preparation for an upcoming event. CNV plays a crucial role in understanding how the brain processes anticipatory information and its implications for cognitive neuroscience.
David Regan: David Regan is a prominent neuroscientist known for his contributions to the understanding of visual perception and the application of electroencephalography (EEG) in studying brain activity. His research has significantly advanced the field by using EEG and event-related potentials (ERPs) to explore how the brain processes visual information, linking neural responses to cognitive functions such as attention and recognition.
Delta Waves: Delta waves are a type of brain wave that are characterized by their high amplitude and low frequency, typically ranging from 0.5 to 4 Hz. These waves are most commonly associated with deep sleep, particularly during the non-REM stages, and play a crucial role in restorative processes within the brain and body.
Diagnosis of Epilepsy: The diagnosis of epilepsy involves identifying a neurological disorder characterized by recurrent, unprovoked seizures caused by abnormal electrical activity in the brain. Accurate diagnosis is crucial for effective treatment and management, often relying on various assessments, including EEG readings and clinical evaluations to distinguish epilepsy from other conditions that may cause seizures.
Electrodes: Electrodes are conductive materials that are used to detect and transmit electrical signals in biological systems, particularly in neuroscience. They play a crucial role in techniques like electroencephalography (EEG) and event-related potentials (ERP), as they interface with the scalp or brain tissue to capture the electrical activity produced by neurons. Understanding electrodes is key to interpreting brain activity measurements and their implications for cognitive processes.
Electroencephalography: Electroencephalography (EEG) is a non-invasive method used to record electrical activity in the brain through electrodes placed on the scalp. This technique measures voltage fluctuations resulting from ionic current flows within the neurons, allowing researchers and clinicians to analyze brain activity over time. EEG is often used in conjunction with event-related potentials (ERPs), which are time-locked brain responses to specific sensory, cognitive, or motor events, providing insights into neural processing related to these events.
Event-related desynchronization: Event-related desynchronization (ERD) refers to a decrease in the power of specific frequency bands of the electroencephalographic (EEG) signal, which occurs in response to a stimulus or event. This phenomenon is important as it highlights brain activity changes related to cognitive processing, motor preparation, and attention. ERD is commonly observed in the alpha and beta frequency ranges and can be utilized to assess neural engagement during various tasks.
Event-related potentials: Event-related potentials (ERPs) are electrical activities in the brain that are time-locked to specific sensory, cognitive, or motor events, measured using electroencephalography (EEG). These potentials reflect the brain's immediate response to stimuli, allowing researchers to investigate cognitive processes and neural mechanisms underlying perception, attention, and memory in real-time.
Event-related synchronization: Event-related synchronization (ERS) refers to the increase in power of specific frequency bands in the brain's electrical activity, observed during the processing of stimuli or events. This phenomenon is significant in understanding how the brain organizes its resources and synchronizes its activity in response to specific cognitive demands, particularly in relation to electroencephalography (EEG) and event-related potentials (ERP). By examining ERS, researchers can gain insights into attention, perception, and other cognitive processes as they unfold over time.
Gamma waves: Gamma waves are brainwave patterns with a frequency ranging from 30 Hz to over 100 Hz, often associated with higher mental activity, cognitive processing, and states of heightened perception. These waves play a crucial role in information processing, memory formation, and maintaining consciousness, making them essential for understanding brain function during complex tasks.
Hans Berger: Hans Berger was a German psychiatrist and neurologist known for his pioneering work in the development of electroencephalography (EEG), a technique used to measure electrical activity in the brain. His groundbreaking invention in the early 20th century allowed for non-invasive monitoring of brain function, leading to significant advancements in both neuroscience and clinical medicine.
Independent Component Analysis: Independent Component Analysis (ICA) is a computational method used to separate a multivariate signal into additive, independent components. This technique is particularly important in neuroimaging and signal processing, as it helps isolate brain activity patterns from noise and overlapping signals, making it crucial for analyzing data from brain imaging techniques.
Information Processing Theory: Information processing theory is a cognitive framework that compares the human mind to a computer, emphasizing how information is received, processed, stored, and retrieved. This theory highlights the sequential stages involved in understanding stimuli from the environment and how these processes relate to cognitive functions such as perception, memory, and decision-making. It helps to explain how the brain interprets data from various sources, making it fundamental for understanding cognitive processes and behaviors.
Latency: Latency refers to the time delay between a stimulus and the brain's response to that stimulus, often measured in milliseconds. This concept is crucial for understanding how quickly the brain processes information and responds to events, impacting our perception and reaction times in various cognitive tasks.
Mismatch Negativity: Mismatch negativity (MMN) is an event-related potential (ERP) component that reflects the brain's response to changes in auditory stimuli, specifically when an unexpected or deviant sound occurs within a sequence of standard sounds. This neural marker indicates the brain's automatic detection of discrepancies, playing a crucial role in understanding auditory processing and cognitive functions such as attention and memory.
Monitoring of sleep disorders: Monitoring of sleep disorders involves the use of various techniques to assess and diagnose sleep-related issues, enabling healthcare professionals to develop appropriate treatment plans. This monitoring often relies on methods such as electroencephalography (EEG) to analyze brain wave patterns and event-related potentials (ERP) to understand brain responses to stimuli during sleep. Through these methods, clinicians can gain insights into the nature of sleep disturbances, contributing to better understanding and management of conditions like insomnia, sleep apnea, and narcolepsy.
N100: The n100 is an event-related potential (ERP) component that typically appears around 100 milliseconds after a stimulus is presented. This negative voltage deflection is mainly observed in the EEG when participants are engaged in tasks requiring attention or cognitive processing, particularly in response to visual and auditory stimuli. The n100 reflects early sensory processing and is crucial for understanding how the brain reacts to external events.
N200: The n200 is a specific event-related potential (ERP) component that appears approximately 200 milliseconds after a stimulus is presented, typically observed in electroencephalography (EEG) recordings. It is associated with cognitive processes such as stimulus evaluation and attentional allocation, often reflecting the brain's response to relevant or unexpected stimuli. The n200 can provide insight into neural mechanisms related to attention and conflict monitoring.
N400: The N400 is an event-related potential (ERP) component that is observed in EEG recordings, typically peaking around 400 milliseconds after the presentation of a meaningful stimulus. It is primarily associated with semantic processing, particularly in response to words or sentences that violate expectations or contain incongruent information. The N400 provides valuable insights into how the brain processes language and meaning, and its amplitude is often modulated by contextual factors and the predictability of upcoming words.
P200: p200 refers to a specific event-related potential (ERP) component that typically emerges around 200 milliseconds after a stimulus is presented, often associated with cognitive processes like attention and memory. This component reflects the brain's early response to stimuli, particularly in visual and auditory processing tasks, playing a crucial role in understanding how we process information in real time.
P300: p300 is an event-related potential (ERP) component that occurs approximately 300 milliseconds after the presentation of a stimulus, particularly in tasks requiring attention and memory processing. This positive voltage shift is often associated with the cognitive processes of decision-making and the allocation of attentional resources during stimulus evaluation.
Phase-Locking Value: The phase-locking value (PLV) is a measure used to quantify the degree to which the phase of a neural oscillation is synchronized with a specific event or stimulus. It helps in understanding how reliably neurons fire in relation to external cues, providing insights into neural communication and coherence in brain activity. By analyzing the PLV, researchers can assess the timing precision of neuronal firing, which is crucial for understanding processes like attention and perception.
Signal Amplification: Signal amplification refers to the process of increasing the strength of a signal, making it more detectable and easier to analyze. In the context of electrophysiological techniques, this is crucial as it enhances the ability to observe electrical activity in the brain, allowing researchers and clinicians to discern patterns related to cognitive processes and responses. The amplification of signals ensures that even subtle neural events can be captured, providing insights into brain function and disorders.
Source Localization: Source localization refers to the process of determining the origin of electrical activity in the brain, typically using techniques like electroencephalography (EEG). This technique allows researchers and clinicians to identify where in the brain certain signals or events originate, which is essential for understanding brain function and diagnosing neurological conditions. It bridges the gap between brain activity and cognitive processes by linking neural responses to specific locations within the brain.
Spatial Filtering: Spatial filtering is a technique used to enhance or suppress certain features of a signal based on their spatial characteristics. This method is crucial in processing data collected from the brain, where it helps to isolate specific brain activity patterns while reducing noise and interference from other sources. By applying spatial filtering, researchers can better understand the localization and dynamics of neural activities using various neuroimaging modalities.
Theta Waves: Theta waves are brainwave patterns that oscillate between 4 to 8 Hz, typically associated with light sleep, relaxation, and meditative states. These waves play an important role in memory formation, creativity, and emotional processing, and are prominently observed during certain stages of sleep and various meditative practices.
Time-Frequency Analysis: Time-frequency analysis is a method used to analyze signals that vary over time, allowing for the examination of how the frequency content of a signal changes at different moments. This technique is particularly important for studying brain activity, as it helps to capture both the temporal and spectral information of EEG signals and event-related potentials, revealing insights into cognitive processes and neural dynamics.