Question

What are some of the most common artifacts that occur during EEG data collection? How can these be prevented in the first place?

How does eye-blink reduction work, what does it accomplish, and what is a side-effect of this process?

What is the purpose of separating data into epochs? At what later processing stage is having epochs important? Why is this?

What sorts of ‘noise’ is filtering best at removing? To answer this, provide at least one example for both the higher and lower frequencies.

Why are larger epochs than are needed initially selected (i.e. why are they cropped after filtering)?

In one to two sentences, describe what a baseline correction accomplishes, in very simple terms.

What is the point of averaging ERP data?

For each number, name the preprocessing step used, and describe the changes that occurred before and after that gave it away. Use the images below and the numbering assignment to answer the question.

Answer 1

• Common artifacts that occur during EEG data collection are generated are due to physiological movements such as eye movements, tongue movements, talking/chewing,electrode artifacts, sweat artifacts.
• These can be prevented by artifactual segment reduction,Filtering, Weiner filtering, adaptive filtering,adaptive noise cancellation etc.
• Eye-blink reduction work: To minimize the ocular artifacts,linear regression algorithms are commonly used to remove such artifacts.
• It is accomplished by using additional electrodes near the ocular and facial muscles to note down the additional movements in the concerned area.The side effects can be the occurrence of false negative, else it was true positive.
  Good luck!