EEG and ERP Techniques Quiz

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Questions and Answers

What is the frequency range for beta waves in EEG analysis?

0.1 - 3.5 Hz

14.0 - 30.0 Hz (correct)

4.0 - 7.5 Hz

8.0 - 13 Hz

Which of the following statements about the N400 ERP is accurate?

It reflects the relatedness of words rather than sentence understanding. (correct)

It requires invasive procedures for accurate measurement.

It is exclusively linked to sentence comprehension.

It occurs primarily in the delta frequency range.

What is a key advantage of using EEG over behavioral paradigms?

Invasiveness

Better spatial resolution than MEG

Excellent temporal resolution (correct)

Higher signal-to-noise ratio

Which of the following is a limitation of EEG?

High setup time Signup and view all the answers

What technology is utilized in magnetoencephalography (MEG) to detect magnetic fields generated by neuronal activity?

Super-conducting quantum interference devices (SQUIDs) Signup and view all the answers

What does electroencephalography (EEG) primarily measure?

Large populations of active neurons Signup and view all the answers

Which of the following is NOT a technique for artifact rejection in EEG pre-processing?

Event-related averaging Signup and view all the answers

What is the primary purpose of the Event-Related Potential (ERP) technique?

To understand how brain activity is modulated by a cognitive task Signup and view all the answers

How does EEG primarily differ from MEG in terms of measurement focus?

EEG measures electrical activity; MEG measures magnetic fields. Signup and view all the answers

In EEG data analysis, what does PCA/ICA stand for?

Principal Component Analysis/Independent Component Analysis Signup and view all the answers

What is a common artifact that may affect EEG readings?

Eye movements Signup and view all the answers

Which aspect of EEG makes it useful for assessing conditions such as epilepsy?

It provides a continuous measure of brain activity. Signup and view all the answers

What is indicated by a paroxysmal spike and wave pattern in an EEG recording?

Possible epileptic seizure Signup and view all the answers

What is a primary limitation of fMRI in measuring neuronal activity?

It measures blood flow rather than neuronal firing. Signup and view all the answers

What is an important aspect of Prediction Error (PE) in behavioral learning?

It is derived from comparing expected rewards with received rewards. Signup and view all the answers

What do ERP studies in EEG focus on?

Temporal aspects but not the accuracy of spatial localization. Signup and view all the answers

Which of the following does NOT improve fMRI research quality?

Using low-quality analysis methods. Signup and view all the answers

Which statement best describes the relationship between EEG and spatial resolution?

EEG has poor spatial resolution but good temporal resolution. Signup and view all the answers

What does the activation pattern from passive face viewing tasks illustrate about neuroimaging?

It provides insight into the statistical and practical significance. Signup and view all the answers

What is the main advantage of combining methods in neuroscience research?

It enhances insights beyond what a single method can offer. Signup and view all the answers

Which method is best suited for understanding when a neural response occurs?

EEG because of its high temporal resolution. Signup and view all the answers

Study Notes

Neuroscience Methods & Issues

This lecture covers neuroscience methods for studying cognition, including EEG, MEG, fMRI (and PET)
Methods are focused on measuring brain activity related to cognitive function
Four main areas of focus include neural function measurements (EEG, MEG), combined function/structure measurements (fMRI, PET), general issues with neuro methods, and the future of combined methods

Functional Neuroimaging Methods: Temporal and Spatial Resolution

Graph shows temporal and spatial resolution differences between MEG/EEG, fMRI, and PET
MEG/EEG have excellent temporal resolution, measuring millisecond-level activity changes. However, their spatial resolution is limited
fMRI has good spatial resolution, allowing accurate location of activity, though its temporal resolution is lower than EEG/MEG (seconds)
PET also has good spatial resolution, but has the poorest temporal resolution compared to the other methods (days).

Neural Function (EEG, MEG)

EEG measures large populations of electrical neuronal activity.
EEG data is continuous and varies by behavioural states, which can suggest cognitive function
EEG is used for diagnosing issues like epilepsy
MEG detects magnetic fields produced by neuronal activity.
MEG signals are more localised than EEG information which helps pinpoint brain regions related to activity
MEG analysis involves positioning SQUIDs around the head, detecting auditory responses to a stimulus, generating contour maps and localising the stimulus-response in the brain

EEG Pre-processing

Essential steps include filtering, epoch segmentation, artifact rejection (blinks or movements) and baseline correction
Data cleaning is crucial to prevent data distortion and accurately reflect the response to a cognitive task

Using data from many trials (e.g. responses to stimuli), researchers can average out noise to identify neural responses to stimuli that may be unique
Data is time-locked to events of interest, often stimuli and behaviours in a task to isolate event-related signals
ERPs are important neuro signals that can be used to understand cognitive events in the brain

Frequency Analysis of EEG Data

EEG activity is characterized by frequency, or oscillations
The different oscillations include various states such as theta, alpha, beta, and gamma rhythms, which can be tracked over time
Time-frequency analysis is used to measure changes in the amplitude of the wave across time

Example: The N400 ERP

The N400 is an ERP component related to semantic processing
An example sentence (like 'He spread his toast with…socks') can be used to illustrate this
The amplitude of the N400 component in the brain shows how relatable words are in a sentence

However Interpretation Can Be More Difficult

The N400 component may not be unique to sentence processing but also due to semantic priming from other context words
Priming describes how previous information can change following responses to a stimulus (related words).

EEG Issues and Considerations

Advantages are excellent temporal resolution, non-invasiveness, and low cost
Disadvantages include limited spatial resolution, long setup time, and low signal-to-noise ratio (SNR)

Magnetoencephalography (MEG)

MEG records magnetic fields produced by neuronal activity, offering better spatial localization than EEG
Detecting these signals needs super-conducting sensors and amplifiers (SQUIDs) which collect and interpret the signals
The data is then overlaid onto images of the brain from another imaging technique (e.g. MRI) to provide a visual localisation of the signals

MEG Analysis

Data processing often consists of positioning SQUIDs around the head, introducing a stimulus that generates a behaviour (like a tone that elicits an auditory response), creating contour maps showing areas of activity, and identifying the dipole signal related to the response in the brain

MEG Issues and Considerations

Advantages include good temporal resolution and an ability to identify the activity of neuronal sources in the brain
Disadvantages include small signals and the inverse problem which determines the exact location of electrical activity within the brain

Structural Analysis: Magnetic Resonance Imaging (MRI)

MRI uses magnetic field properties within the brain tissue using hydrogen atoms to record an image of the brain
These signals can be used to generate images of brain structures
fMRI uses this magnetic property to understand brain activity related to cognitive tasks through oxygenated measurements.

Functional Magnetic Resonance Imaging (fMRI)

fMRI monitors the ratio of oxygenated and deoxygenated haemoglobin in the blood in the brain, inferring which areas of the brain are active
Active regions of the brain will take up more oxygen to supply brain cells
It's an indirect measure of brain activity but has great spatial resolution

fMRI Data

fMRI data is composed of voxels (3D cubes) that identify brain activity
Each voxel can contain a great number of neurons, and so the signal reflects the population activity within the voxel

fMRI Sources of Noise

fMRI data has several sources of noise, in addition to physical movement issues like the subject moving, external sounds and changes in brain activity over time

fMRI Preprocessing

Steps in preprocessing can include motion compensation (prevent inaccurate data due to movement), slice timing correction (adjust for differing times during image acquisition), spatial filtering (improving the quality of the signal), and temporal filtering (removing high-frequency fluctuations of the data)

Co-Registration and Normalisation

Co-registration refers to aligning fMRI data with individual and structural anatomical images, like MRI
Normalisation refers to adjusting multiple subjects' fMRI data, making it comparable, by aligning their data to a standard brain model via warping their images

fMRI Example Experiment (Smoking)

A study examined attentional bias and neuro-activity in smokers with exposure to smoking and/or neutral images

Conclusion and Future Directions

EEG and MEG results should be considered to understand when neural events happen, and how to combine results from these techniques across different cognitive tasks
Combining multiple methods helps understanding neurological processes better than each single technique
There is a potential to identify future treatment options especially when these results are considered from a meta-analysis.

Meta-Analysis of Prediction Error (PE) Literature

PE literature studies have been categorized into valence (positive/negative value), magnitude (size of the event), and signed PE groups (combination of valence and magnitude)
Studies have shown separate networks within the brain are correlated with individual PE categories.
The striatum is one area of the brain that appears to correlate across different PE classifications.

Prediction Error (PE)

Prediction Error (PE) is the difference between the expected reward and the outcome of a cognitive task. PE data can be used to update future expectations and behaviours
Dopamine neurons, among others, are used to identify this Prediction Error
The striatum is an important brain region involved in this prediction error pathway

Concurrent fMRI and EEG

EEG studies have revealed different temporal networks to valence, magnitude and PE in studies combining fMRI and EEG
Researchers used EEG informed analysis to highlight distinct brain regions that fMRI alone could not find

Sample Sizes

50 participants is considered a large sample size
It is crucial that researchers consider relevant factors of sample size because effects might be smaller even if the sample size is large, and that bigger studies will not always be meaningful

Bringing It All Together

Formulating a clear research question based on literature is critical to ensure the research is based on a good foundation
Developing a proper research question needs careful consideration of all the relevant background research to help build on existing results

Reversal Learning Task

A behavioural paradigm or task used to study decision-making in the brain which demonstrates the transition in decision-making processes.
Stimuli and feedback are displayed and responses analysed in different conditions to measure how brain regions change in responses
This helps understand learning related to cognitive processes.

Combining Methods

Combining different methods can offer insights beyond what a single method can provide
Combining different methods might enhance understanding of the human brain more fundamentally but it could also introduce issues that need to be carefully considered

PET Issues and Considerations

PET is exposed to radiation, making short-term tasks the only use case for these scans
PET is an expensive technique, making it limited to research purposes rather than clinical and routine applications
PET can measure blood flow and metabolic rates in the brain, which are crucial measures for understanding cognitive processes.

General Limitations of fMRI

fMRI data reflects blood flow in a brain region and not neural activity directly, so results have limitations in interpreting specific neural activity
A large number of neurons might be represented by each voxel, making it difficult to isolate the specific neural activity in that region, and the data is only measured coarsely via time measurements
fMRI responds very slowly compared to neural signalling time, so it cannot accurately measure changes in neural activity

EEG and fMRI Issues and Considerations

The different considerations regarding EEG and fMRI can be summarised as their respective strengths (e.g., EEG has good temporal but poor spatial resolution) and weaknesses (spatial or temporal limitations)

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Description

Test your knowledge on the concepts of EEG and Event-Related Potentials (ERP) with this engaging quiz. You'll explore topics such as frequency ranges, advantages, limitations, and analysis techniques in neuroscience. Perfect for students and professionals in psychology and neuroscience fields.