EEG Flashcards

1
Q

Why is it important to shield n form electrical noise in the environment?

A

• The signal we get with EEG is already tiny
• Noise from the environment is much bigger and would
significantly distort the signal
• shields n from this noise

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2
Q

How does oscillatory activity outside of n affect the signal picked up by the electrode

A
  • Any oscillatory activity produces a magnetic field
  • This magnetic field is picked up by the electrode
  • Signal electrode picks up form this > than signal we are interested in
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3
Q

Can you describe the layout of the cage?

A

Cage – describe the layout?

  • two screens one is inside the shield (digitization) and one is outside (computer sending stimuli)
  • The outside screen sends stimuli into the inside screen
  • Key = both screens are linked, stimulus screen sends pulse to digitization screen saying NOW! And links data to the sitimuli
  • There is also the electrodes and amplifier in the cage and perhaps a response button pad for n
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4
Q

Why do we need multiple electrodes?

A
  • EEG picks up on voltage, voltage is the electrical potential of current moving from A to B.
  • Can’t be measured from one place
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5
Q

How many electrodes are needed in EEG? What are they

A

• EEG systems are differential amplifiers
• Need a minimum of 3 electrodes to work
> Active electrode – placed at a region of interest
> Ground electrode – placed somewhere convenient, it is linked to the ground circuitry of the amplifier
> Reference electrode – anywhere on the scalp, not region of interest

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6
Q

I though we just need to measure current moving from A to B? Why are 2 electrodes not enough?

A
  • The ground electrode is linked to the ground circuitry of the amplifier
  • Every electrical device has a ground circuitry – very noisy!
  • We could look at the voltage between A and G and yes this would tell us something about how the current moves from A to B
  • But it would be infiltrated by the noise of the ground circuit – we don’t want that
  • Adding a third electrode allows us to subtract the noise
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7
Q

I though we just need to measure current moving from A to B? Why are 2 electrodes not enough?

A
  • The ground electrode is linked to the ground circuitry of the amplifier
  • Every electrical device has a ground circuitry – very noisy!
  • We could look at the voltage between A and G and yes this would tell us something about how the current moves from A to B
  • But it would be infiltrated by the noise of the ground circuit – we don’t want that
  • Adding a third electrode allows us to subtract the noise
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8
Q

How does adding a reference electrode subtract the noise?

A
  • Amplifier calculates the difference between: A-G and R-G
  • Effectively gives us the difference between A and R, removing the noise from the ground circuitry
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9
Q

Describe a channel

A
  • The three electrodes are combined into a single channel
  • The waveforms we see on the screen are the potential from A-G and R-G
  • So we look at the electrical flow of current in the brain using three electrodes
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10
Q

Why shouldn’t we have the reference site on the body?

A
  • Must be on the scalp
  • If on the body – picks up a signal produced by the heartbeat called EKG
  • Dipoles we want to measure are tiny, signal from the heartbeat is massive
  • Would massively interfere with the signal
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11
Q

Where should we place the reference electrode?

A
  • Placed at neutral site ideally to allow us to see the flow of current towards the region of interest
  • This is because the amplifier looks at the difference between the active and reference site, taking activity from both areas in to consideration
  • ERP reflects activity from both sites
  • We want a site with the least noise – otherwise will influence the results
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12
Q

what are some common reference sites used?

A
  • tip of the nose (annoying for n)
  • chin (annoying)
  • mastoids (most common)
  • earlobes
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13
Q

things to consider when choosing a site for the reference electrode

A
  • Electrically neural as possible
  • Convenient for n
  • Not biased towards a particular hemisphere
  • Are you comparing your findings with another study? Important to use the same reference site
  • Where you place it in relation to the active electrode
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14
Q

When chosing a refernce site why do you need to consider how far it is from the active electrode?

A
  • The location of reference affects the size of the thing we are measuring
  • if both nearby, on the same hemisphere then the result (the voltage between both areas) wont be so big
  • thus the absolute size of the ERP will differ based on the reference site used
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15
Q

Average mastoid reference – why can’t you just use one of the mastoids?

A
  • Left mastoid or right mastoid
  • Reference is biased towards one hemisphere
  • Would lead to an imbalance In between the active electrodes in the left and right hemisphere
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16
Q

How do we calculate the average mastoid?

A
  • How is this done – during recording you couple the active electrode and one of the mastoids (e.g., left) and reference this with the other (right) – after recording EEG is pretty cool – allows you to now play around with stuff. Thus after the recording is complete we calculate the average mastoid
  • Subtract half the difference between the LM and RM from the active electrodes.
  • = average mastoid reference
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17
Q

What does digitization do

A
  • converts continuous signal (waveform deflections) into a series of numbers
  • the more numbers the better
  • the numerical range depends on the resolution of the digitizer
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18
Q

What is a digitizer government name

A

analogue-to-digital converter (ADC)

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19
Q

how does the digitiser convert a deflection into a number

A

• Record different voltage values
• Resolution of 12 bites = records 2 to the power of 12 or 4096 voltage values
• waveform goes up and down on the y axis with say 4096 diff points on the y axis (for 12 bite resolution)
• Amplifier is set to measure the difference between -5 and +5 microvolts – divided into 4096 points.
- 4096 is coded as +5 and 0 is coded as -5. The numbers are coded as somewhere between 0 and 4096.

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20
Q

What is “amplifier blocking”

A
  • Something that prevents us from recording values above +5 (4096) or below -5 (0)
  • If a voltage is out of this range it will be represented as either 4096 or 0
  • Gain of the amplifier is set so these values it not exceeded – set to a range that makes sense. Otherwise, the values we get would not be meaningful. All it would tell us is if a value is smaller or higher than another
  • Most EEG systems have 24 bites of resolution so the issue of amplifier blocking isn’t such a problem today
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21
Q

What does the Y axis of a waveform reflect?

A
  • The size of the potential

* Measured in microvolts

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22
Q

What does the x axis of a waveform reflect?

A

time

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23
Q

How can we convert to a signal into a waveform

A
  • So each time is associated with a value between 0 and 4096 (depending on the resolution of the amplifier), at another time point there is another value between 0 and 4096
  • This is the waveform is constructed
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24
Q

Why do we have so much information with EEG waveform

A
  • Because each time point is associated with a value between 0-4096
  • And at each time point this isn’t just the value associated with one but 64 channels
  • Very quickly becomes a lot of information
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25
Q

How can we reduce the information load of the continuous EEG signal

A
  • Sampling
  • continuous EEG signal is converted into s sequence of discrete-time points
  • lower number of time points for each of the 64 channels
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26
Q

what is the sampling period?

A

• Time between consecutive samples

27
Q

What is the sampling rate

A
  • Number of samples per unit of time (seconds)
  • Measured in Hz
  • 500Hz = 500 samples per second
28
Q

How do we determine the sampling rate is?

A
  • Depends on the frequency content of the signal we are recording
  • Must be at least 4 times faster than the highest frequency you have
29
Q

How do we extract the ERP from the EEG signal?

A
  • Activity is time-locked to a specific event
  • We can then average together different signals all time-locked to the same event
  • The background noise is random and would cancel each other out
  • Would leave behind only the signal of interest
30
Q

What things can cause noise in EEG signal?

A

> electrical activity that is not the signal of interest
Electrical signals form the environment
Non EEG biological signals

31
Q

Voltage fluctuations measured by EEG are tiny, by how much do we amplify the signal so that it is detectable?

A

• 10-50k

32
Q

What do we mean by electrical noise from the environment?

A
  • Electrical sources produce electromagnetic fields
  • this can be picked up by the electrodes on n’s head
  • any electrical device induces quite a dramatic voltage change in the signal
  • much bigger than the one where inrteresyed in
33
Q

How exactly do electrical devices affect the EEG signal ? explain this using a cable as an example of the electrical device in the room.

A
  • Cable = is a conductor with an oscillatory voltage inside
  • Brings with it an electromagnetic field
  • This produces voltage changes (electrical noise) in n, the electrical wires, and the electrodes

> Oscillating voltages influence voltages in nearby conductors – this electrical noise will be observed in the EEG.

34
Q

What are the two major sources of electrical nosie

A
  • AC current line - induces 50Hz – causes oscillations in the EEG of exactly 50Hz.
  • Video monitor - these have a refresh rate, they will produce 120 new images every second. Here you have an oscillation of 120Hz
  • Ac line noise is sinusoidal, noise from monitors = more spikey.
35
Q

Name 2 ways to reduce background noise

A

• Passive shielding – conductive metal that surrounds to-be-shielded regions.
- this will cancel out electromagnetic fields.
- Rooms, cables – both can be shielded
• Electrodes with front end amplifiers

36
Q

How do electrodes with front end amplifiers boost the signal-to-noise ratio?

A
  • Normally, the active electrode sends a signal through a cable to an amplifier and the signal is boosted
  • But here, a small amplifier is placed near the electrode, amplifying the signal before you send it somewhere else.
  • if you have a tiny signal and noise interferes with it, the effect is strong. If you have a much bigger signal and that is then faced with noise, less interference
37
Q

what are the disadvantages of front-end amplifiers

A
  • Expensive
  • Must fiddle with it a lot and they break easy
  • imagine you have 64 electrodes and then 64 tiny amplifiers sitting with them, it’s a bit much
38
Q

what are non EEG signals (biological noise), name 3 examples

A

Internal noise comes from the body and cannot be eliminated
• skin potential
• blinks
• muscle movements

39
Q

why are post processing techniques not perfect

A

• because they always distort the original signal

40
Q

how can we minimise biological noise

A
  • getting n as comfortable as possible.
  • Any muscle activity, stiff neck, clenched teeth will produce muscle activity, electromyography which is itself a large signal
  • muscles you have are larger than the generators in the brain - produce much bigger electrical signal
41
Q

how can we deal with artifacts in the data

A
  • artifact correction – correcting data

* artifact rejection – just getting rid of contaminated trials

42
Q

where could electrodes pick up EKG signals?

A
  • on the body
  • on the head
  • E.g. by placing an electrode on the blood vessel which pulsates with the heartbeat
43
Q

What waveforms might emerge that are NOT artifacts (e.g. caused by muscle movment)

A
  • Those appearing when n becomes sleepy
  • results in slow waves that are bigger in amplitude.
  • Within a certain frequency range – alpha frequency – which is between 8 and 12 Hz.
44
Q

Why might sometimes we not be able to do artifact rejection?

A
  • Because the artifact might be produced in a systemic manner
  • EKG – happens every second – cant throw away the whole data set
45
Q

What is the most common artifact ?

A
  • Eye blinks
  • induce massive change in amplitude most pronounced over electrodes over the front of the head
  • this is bc the eye is a small dipole. Each of our eyes has an electrical gradient.
  • This has a positive end at the front and a negative at the back. Each time we move our eyelids – changes modulation of the electrical potential of eyes to surrounding areas.
  • (if we close our eyelids, it changes this electrical field).
46
Q

How to know if you have a blink artifact?

A

you will have a characteristic scalp distribution – helps to discern them

47
Q

how can we correct artifacts? E.g. blinks

A
  • fourier transform

* filtering

48
Q

What is Fourier transform?

A
  • waveform dispelled into sine waves of different frequencies
  • then Fourier Transform is a technique that plots each individual sine wave
  • then can eliminate specific frequencies. E.g. I don’t want that low frequency (eye blink) and I cut that frequency from the data.
  • then go back to see the full dataset without it.
49
Q

What is filtering?

A
  • Remove frequencies we are not interested in
  • if devices produce 50 Hz artifacts and the signal that we are interested = between 8-30 HZ - just filter out anything over 30Hz.
50
Q

What is low or high pass filtering?

A
  • a type of filtering

* anything below X hz we keep, and everything above it – we delete. Vice versa

51
Q

After you have got the data and eliminated the noise as much as possible whats next?

A
  • Signal averaging
  • EEG data in each trial contains both the ERP waveform and random noise.
  • Averaging enough of these trials together will considerably reduce this background noise.
52
Q

What is signal averaging?

A
  • The extraction of the signal specific to the event from the EEG signal
  • Time locked manner
  • then average together the waveforms generated at that time in a point-by-point manner
  • begins to emerge a kind of waveform
  • because the background noise is eliminated
53
Q

is it the more trials the better the signal to noise ratio? Would 1 mil trials then be a dream?

A
  • No – yes the more trials averaged together boost the signal to noise raito
  • But after a certain point – addition of more trials becomes less and less effective
54
Q

What would a variable latency affect in the waveform?

A
  • The peak
  • Jitters in latency between trials will reduce the amplitude of a peak in the average
  • Results in different ERP amplitude!
55
Q

Name a scenario in which varied latencies in activity across trials would be problematic (limitation)

A
  • comparing the effects of two groups, and one has more jittered latencies than the other e.g. in a study of cognitive ageing
  • Older groups might have more latency variability.
  • Simply by averaging trials together you cannot see the difference between two groups ERPs
  • need to analyse individual frequencies - other analysis techniques will help
56
Q

How can we mitigate the problem of jitters in latency across trials affecting the averaged peak (counter to the limitation)

A

• Measure the area of the waveform as opposed to peak

57
Q

why is it difficult to capture the underlying neural response with an average? (big limitation)

A

• Latency variability makes it hard to see a given neural response in an averaged waveform.

–> Should use time-frequency-analysis techniques to better see induced neural activity.

• sometimes latent components overlap with one another such that the movement of one would affect movement of the other

could be a shift in the a or b component that produced the overall waveform

58
Q

What are ways to reduce confounds in EEG

A
  • Consider physical properties of stimuli
  • Use as identical stimuli as you can in different experimental conditions
  • Bare in mind both the preparation and execution of a motor response will elicit ERP activity. Don’t mistake button presses for stimulus induced activity
  • Whenever you can, vary experimental conditions within blocks and not between them.
59
Q

Ways to reduce confounds: physical properties

A
  • Make sure physical properties of stimulus don’t evoke electrical activity in itself
  • some ERP components are sensitive to things like luminance/contrast
  • imagine study on race – claiming to find ERP component that detects ethnic identity but really it’s just picking up on light or dark colours
  • P1 sensitive to physical properties of stimuli e.g., colour – might find higher p1 amplitude - cant then conclude P1 computes race information
60
Q

Ways to reduce confounds: using identical stimuli In diff conditions

A
  • if you are comparing faces that are familiar and not familiar to n.
  • you can use a familiar face for one for the unfamiliar face for the other!
61
Q

Ways to reduce confounds: motor responses

A
  • motor activity in one body region activates the contralateral hemisphere
  • button press with the right hand would evoke activity in the left hemisphere
  • n press right botton with stimulus A; and left button with stimulus B
  • Don’t mistake button presses for stimulus induced activity
  • To deal with this: have one group use 1 button, other group use a diff one ; easy to check because activity should switch if left button press is switched to the right while stimuli stay fixed
62
Q

Ways to reduce confounds: vary conditions within blocks

A
  • Try and have all conditions in a single block.
  • Maybe n perform differently because they are more tired in blocks nearing the end of the trial.
  • Alternatively, they might get more practice as the study goes on and perform better in tasks near the end.
  • Changes in brain activity can reflect either of these.
63
Q

Let’s say we have a neuron that is selective to a line at 45 degree orientation to the right

will this respond to all lines of 45 degrees in an image?

A

No each cell in V1 has a small receptive field and responds to stimuli in that receptive field