EEG and Event- Related Potential (ERP) Method

Question 1

Average amplitude data overview

Answer 1

• the analysis of event-related potentials (ERPs) is a method that allows us to investigate fast neural processes related to specific events of interest
• usually, we want to study what happens in the brain when participants engage in cognitive process, such as perceived, deciding and responding.
• ERPs can be obtained by time-locking the signal of the events we want to study, so we can analyze the signal amplitude at specific channels.

Question 2

key assumptions for averaging amplitude data

Answer 2

• the event of interest is defined in time
• the event consistently evokes the signal
• the timing of the signal is consistent
• the signal and the noise are uncorrelated
• the noise is random with a mean of zero

Question 3

the importance of averaging amplitude data

Answer 3

• we want to know whether there is brain activity reliably related to the cognitive process of interest
• however, usually the signal-trial EEG trace is far too noisy to do this

Question 4

the process of averaging amplitude data

Answer 4

• if our assumptions are met then we can align the trial segments from the event and average the respective trials
• all noise will average out, and we are left with a better estimate of the true neutral response to the event of interest.

Question 5

ERP’s categorized

Answer 5

• ERP’s are described by their polarity and their order
• specific ERP component are measured at specific channels, or groups of channels.

Question 6

reverse inference (major issue of ERP’s)

Answer 6

• ## concluding what a component ‘reflects’ in a specific experiment required knowing what the component ‘usually’ reflects, which again requires experiments

Question 7

different options to derive a measure of amplitude

Answer 7

• peak amplitude (ie. baseline to peak)
• peak-to-peak
• area under the curve
• latency (the onset of the amplitude)
• 70% of studies are interested on a baseline-to-peak measure; but then researchers have to decide what the best way to estimate is.
• the max peak (ie. the most extreme point)
• the mean amplitude (by defining a range around where the peak should be considering the mean)

Question 8

latency

Answer 8

• the latency refers to the onset of the ERP component
• there are math equations that help with estimating the latencies
• the tail end of component= usually negated

Question 9

studying cognition using ERP’s

Answer 9

• ## a good way to use ERPs for studying cognitive process is to subtract the waves from one condition from the waves from a control condition

Question 10

Gehring and collegues (1993) overview

Answer 10

• investigated whether there is a cognitive mechanism for the detection of the compensation of errors
• for this they measured the error related negativity (ERN), a negative deflection of up to 10 uV in amplitude observed at central electrodes ( 80-100 ms) after an erroneous response
• the ERN comes so fast after we have committed an error (because we can’t take it back anymore).

Question 11

Gehring and collegues (1993) actual experiment

Answer 11

• Gehring and colleagues asked their participants to emphasize accuracy or speed in a simple flanker-task in which participants had to respond to the central letter on the screen
• overall, they found a clear ERN on incorrect trial in comparison to the correct trials.

Question 12

Gehring and collegues (1993) results

Answer 12

• the ERN was indeed strongest when people emphasized accuracy, and weakest for speed.
• this confirmed their hypothesis that participants brains only cared about error deduction when this was also important
• however, this result does not show whether the ERN is also related to compensating for errors.
• if the ERN was not only indicating error detection, but also compensating for making an error, one would except that the ERN additionally reflected the attempt to break the error.
• to investigate the question, G+ H divided the erns from the entire experiment into qualities from ‘small’ to ‘extra large’
• they then investigated whether the ERN’s of different sizes were related to specific parameters, which may be related to correcting or avoiding errors.

Question 13

ERN’s meaning

Answer 13

• the greater the ERN, the lower the response force. participants might be trying to correct for the error
• the greater the ERN, the higher the probability to get it right on next trial. participants might be successful learning from errors.
• the greater the ERN, the slower the response on next trial. participants might be slowing down to avoid a subsequent error

Answer 14

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