W3 - EEG Flashcards

1
Q

What is EEG in one sentence. What do they pick up?

A
  • Detect neural activity using electrodes on scalp
    • Pick up small fluctuations of electrical signals from activity of (mostly cortical) neurons
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

Is EEG extra or intra-cranial?

A
  • Extra-cranial/Scalp
    • Non-Invasive
  • Intra-Cranial
    • Measure directly at exposed cortex
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

Who invented EEG? When and how?

A

Hans Berger.

Detected first EEG with wife’s scalp in 1924.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

What is the Alpha Rhythm

A
  • Inconsistent electrical signal varying between 8 - 13 Hz.
  • Resting signal when someone closed their eyes.
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

What is the pros of EEG

A
  • Cheap
  • Good Temporal Resolution
    • ms accuracy
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

What is the cons of EEG

A

1.) EEG signal biased to Gyri

  • Sulci harder to detect
    • Masked by gyri signals
  1. ) Meninges, CSF and skull “smear” EEG signal, makes localisation dificult
    * Inverse Problem
  2. ) Poor Spatial Resolution
    * 1-10cm (10-100mm)
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

What is the inverse problem.

A
  • If the diple solutions are known, the resulting scalp configuration of signals can be reconstructed
  • However, one given scalp configuration of signal = Multiple dipole solutions
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

What is EEG signal measured in relation to

A

In relation to a reference electrode, which is either

  • a neutral point like nose
  • average of all scalp electrodes
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

How is EEG Recorded: What are the 4 tools

A

(1) Electrode Cap > (2) Amplifier > (4) EEG Recording
(3) Experimental Stimulation > (4) EEG Recording

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

What are the channels in EEG

A

10 – 32 – 64 – 128 – 256 channels

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

How are numbers on the scalp displayed in EEG

A

Split cortex odd and even

F = frontal P = parietal C = central O = occipital T = temporal

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

What is the neurophysiology of the EEG Signal.

What is it NOT

A
  • EEG activity orginates from post-synaptic potential
    • Voltage when NT binds to post-synaptic membrane’s receptor
    • Causes ion channels to open/close, leading to graded changes in potential across membrane

Note: EEG does not record action potential

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

What can the post-synaptic potential be considered as. Can we record one post-synaptic potental?

A
  • A small dipole
  • Signals from single cells are not strong enough to be recorded outside of the head
  • If many neurons spatially align, then their summed potentials add up and create the signals we can record
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

Many neurons spatially align > summed potentials add up and create the signals we can record: What is this called? Where is the origin?

A

Pooled activity

  • From large number of similarly oriented neurons from large cortical pyramid cells
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

What is the functional unit of EEG? i.e. How many Neurons must be spatially aligned to record?

A

The functional unit is >10,000 simultaneously activated neurons

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

What determines the sign of the recorded potentials. Can all of them be recorded?

A
  • Orientation of the neurons determines the sign of the recorded potentials.
  • Some orientations lead to signals which cannot be recorded.
17
Q

Typical amplitude of EEG and Steps to make it clear

A
  1. ) 10μV to 100μV (Tiny)
  2. ) Amplified by factor of 1,000 to 100,000x
  3. ) Signal is typically digitalized. Typical sample frequency is 256-1024Hz, but can be >4000Hz
  4. ) Signal is band-pass filtered to remove the low (<0.5-1Hz) and high frequencies (typically >35-70Hz) because they cannot reflect brain activity.
18
Q

What is the most relevant step in EEG signal analysis. What are some examples?

A

Artefacts Removal, removing stuff that are not brain signals

  • Sweating
  • Electrical noise (“notch filter”)
  • Eye movements and blinks
19
Q

How does eye movement affect EEG. How do we prevent it?

A
  • Eye = Dipole
    • Signals from eye contimates EEG signal to large degree
  • Record eye signal by placing electrodes next to and under the eye to capture horizontal and vertical eye movements
  • Remove by excluding contaminated trials, or mathematical algorithms, such as ICA
20
Q

Despite EEG signals being very noisy, the dominant frequency in the signal can be determined due to

A

The raw signal shows systematic variations, and more of a specific frequency

(Delta, Theta, Alpha, Beta, Gamma) inconsistent characteristic frequency

21
Q

What is wrong with single EEG-trial studies. What should we do then?

A

Noisy: Too much variance (Fluctuations)

(1) Between sessions from same participants
(2) Between participants
* Averaging over lots of trials will reduce noise.

22
Q

How does an ERP look like? What is P and N

A

Positivity is downwards.

Negativity is upwards.

23
Q

What are ways of reading ERP

A
  • Peak-amplitude
    • 70% of studies
  • Area-under-the-curve
    • 20% of studies
  • Peak-to-peak
    • 10% of studies
  • Onset of component
    • Ambiguous

No clear rule. Results will differ across methods

24
Q

Woodman and Luck (1999): What is the signal they used and what did it index.

A
  • N2pc as an index of attention.
  • Attending left = Stronger N2pc right hemsphiere
    • N2pc = 2nd Negative Posterior Contralateral
25
Q

Woodman and Luck (1999): Study Aims, Overview and Hypothesis

A

Aims

Parallel / Serial

Visual Search Task

Search a coloured square

Hypothesis

Serial: Attention switch (N2pc) from one hemifield to the other, until the target is found .

Parallel: No N2pc Switch

26
Q

Woodman and Luck (1999): Study Methods. How did they get the participant to attend to one hemifield first?

A
  • Manipulated probability specific colour was target (C75 and C25) to get people to attend to one hemifield
    • Particiapnts attend to C75 and can monitor attention while particiapants visually scanned
27
Q

Woodman and Luck (1999): Study Results and Conclusion

A

Target Absent

a) When C75 and C25 (same field), no shift in N2pc
b) When C75 and C25 (contralteral), shift in N2pc

Target Present

a) When C75 target and C25 (contralateral), no shift inN2pc
b) When C75 and C25 target (contralteral), shift in N2pc

Conclusion: People search in serial

note looking at crossover of N2pc

28
Q

Gehring et al., 1993: Study Aims

A

Whether there is mechanism for the detection and compensation for errors.

29
Q

Gehring et al., 1993: What is the signal of interest

A

ERN

  • Negative deflection of up to 10μV in amplitude observed at central electrodes ~80-100ms after an erroneous response
30
Q

Gehring et al. (1993): Study Methods. What was manipulated? And what is the hypothesis?

A

Method Flanker-task (Middle Letter)

3 Conditions

  • Emphaise Accuracy
  • Emphaise Speed
  • Control

H1.) Incongruent displays should lead to more errors

H2.) Error detection should only matter in the accuracy condition

31
Q

Gehring et al. (1993): First Hypothesis supported?

A

Yes. ERN on incorrect trial in comparison to correct trials

32
Q

Gehring et al., 1993: Second Hypothesis supported? What else were they interested in finding out?

A

Yes. The ERN was strongest when people emphasised accuracy, and weakest for speed

But is the ERN indicative for compensating for errors?

  • If this were true, one would expect that the ERN should also reflect the attempt to break the error
33
Q

Gehring et al., 1993: Further study of ERN compensation for errors (reflective of breaking the error): Method

A

Investigated how ERNs of different sizes were related to response parameters (might be involved in error correction)

  • Divided into quartiles from small to XL
34
Q

Gehring et al., 1993: Further study of ERN compensation results

A

As ERN increases,

  • Lowe Response Force
    • Error correction
  • Higher Probability of right the next trial
    • Learning
  • Slower response on next trial
    • Post-error slowing
    • Learning