ERPs: L6

Question 1

what are event-related potentials (ERPs) used for?

-> why cant we use EEG?

Answer 1

find brain activity that is reliably related to cognitive processes of interest
-> too noisy, spatial configuration = difficult

Question 2

what variance is there in ERPs

what is therefore needed?

Answer 2

• between different sessions from the same participants and between participants
• many trials & participants to calculate good averages

Question 3

Negativity and positivity on a chart

Answer 3

negativity = goes up
positivity = goes down

Question 4

what are the different aspects of ERPs that can be analysed? (4)

Answer 4

1. peak amplitudes (70% studies) A>B
2. area-under curve (20%) B>A
3. peak-to-peak (10%) A=B
4. determine onset of component e.g. motor activity (but this can be tricky)

Question 5

study: Woodman & Luck

1. test

Answer 5

1. visual search experiment - participants to search for a single target
   - colour C75 = 75% probability. C25 - 25%

Question 6

study: Woodman & Luck
1. results: no target
2. results: no targets, stimuli same hemisphere

Answer 6

1. 2 colours were in opposite hemifields
   - > serial search
2. 2 colours in same hemifield
   - > serial search

Question 7

study: Woodman & Luck
1. results: C75 = more likely stimulus the target
2. results: C25 = less likely stimulus the target

= Hypothesis supported overall?

Answer 7

1. stimuli in opposite hemifields
   - > no cross over of N2pc, no shift in attention between hemifields
   - > serial search
2. stimuli in opposite hemifields
   - > cross over of N2pc
   - > serial search

=YES, serial search

Question 8

Gehring study

1. investigated what?
2. negative deflection up to & observed at?

Answer 8

1. error-related negativity
   - > whether there is a cognitive mechanism for the detection of and compensation for errors
2. 10μV in amplitude observed at central electrodes 80-100ms after an erroneous response

Question 9

Gehring study

1. asked participants to?
2. Hyp

Answer 9

1. emphasise accuracy & speed -> respond to central letter on the screen:
   congruent: HHHHH
   incongruent: HHSHH
2. incongruent = more errors & error detection should only matter in the accuracy condition

Question 10

overall what was found?

-> ERN on graph

Answer 10

clear ERN on incorrect trial in comparison to correct trial

-> ERN went up after EMG onset on incorrect trial

Question 11

what was measured to determine response onsets?

Answer 11

muscle activity, measured using the EMG (electromyogram)

Question 12

the ERN was strongest when?

Answer 12

people emphasised accuracy & weakness for speed

Question 13

But is the ERN indicative for compensating for errors?

Answer 13

-> if this were true one would expect that the ERN should also reflect the attempt to break the error

Question 14

The ERNs from the entire experiment can be?

- what does this investigate?

Answer 14

divided into quartiles from small to X-large
- how ERNs of different sizes were related to response parameters which might be related to correcting or avoiding errors

Question 15

What did they do with the quartiles?

Answer 15

divided into 4 categories: (x-small-x-large)

Question 16

Error force

- the greater the ERN the…

Answer 16

the lower the response force

-> trying to correct for the error

Question 17

probability of error-correction

- the greater the ERN the…

Answer 17

the higher the probability to get it right on the next trial
-> successful learning from errors

Question 18

correct RT on next trial

- the greater the ERN the…

Answer 18

the slower the response on the next trial

-> successful learning from errors