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
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
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
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
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
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
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
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
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
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
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
12
Q
what are some common reference sites used?
A
- tip of the nose (annoying for n)
- chin (annoying)
- mastoids (most common)
- earlobes
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
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
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
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
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
18
Q
What is a digitizer government name
A
analogue-to-digital converter (ADC)
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.
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
21
Q
What does the Y axis of a waveform reflect?
A
- The size of the potential
* Measured in microvolts
22
Q
What does the x axis of a waveform reflect?
A
time
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
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
25
How can we reduce the information load of the continuous EEG signal
* Sampling
* continuous EEG signal is converted into s sequence of discrete-time points
* lower number of time points for each of the 64 channels
26
what is the sampling period?
• Time between consecutive samples
27
What is the sampling rate
* Number of samples per unit of time (seconds)
* Measured in Hz
* 500Hz = 500 samples per second
28
How do we determine the sampling rate is?
* 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
How do we extract the ERP from the EEG signal?
* 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
What things can cause noise in EEG signal?
> electrical activity that is not the signal of interest
> Electrical signals form the environment
> Non EEG biological signals
31
Voltage fluctuations measured by EEG are tiny, by how much do we amplify the signal so that it is detectable?
• 10-50k
32
What do we mean by electrical noise from the environment?
* 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
How exactly do electrical devices affect the EEG signal ? explain this using a cable as an example of the electrical device in the room.
* 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
What are the two major sources of electrical nosie
* 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
Name 2 ways to reduce background noise
• 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
How do electrodes with front end amplifiers boost the signal-to-noise ratio?
* 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
what are the disadvantages of front-end amplifiers
* 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
what are non EEG signals (biological noise), name 3 examples
Internal noise comes from the body and cannot be eliminated
• skin potential
• blinks
• muscle movements
39
why are post processing techniques not perfect
• because they always distort the original signal
40
how can we minimise biological noise
* 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
how can we deal with artifacts in the data
* artifact correction – correcting data
| * artifact rejection – just getting rid of contaminated trials
42
where could electrodes pick up EKG signals?
* on the body
* on the head
* E.g. by placing an electrode on the blood vessel which pulsates with the heartbeat
43
What waveforms might emerge that are NOT artifacts (e.g. caused by muscle movment)
* 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
Why might sometimes we not be able to do artifact rejection?
* Because the artifact might be produced in a systemic manner
* EKG – happens every second – cant throw away the whole data set
45
What is the most common artifact ?
* 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
How to know if you have a blink artifact?
you will have a characteristic scalp distribution – helps to discern them
47
how can we correct artifacts? E.g. blinks
* fourier transform
| * filtering
48
What is Fourier transform?
* 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
What is filtering?
* 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
What is low or high pass filtering?
* a type of filtering
| * anything below X hz we keep, and everything above it – we delete. Vice versa
51
After you have got the data and eliminated the noise as much as possible whats next?
* 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
What is signal averaging?
* 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
is it the more trials the better the signal to noise ratio? Would 1 mil trials then be a dream?
* 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
What would a variable latency affect in the waveform?
* The peak
* Jitters in latency between trials will reduce the amplitude of a peak in the average
* Results in different ERP amplitude!
55
Name a scenario in which varied latencies in activity across trials would be problematic (limitation)
* 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
How can we mitigate the problem of jitters in latency across trials affecting the averaged peak (counter to the limitation)
• Measure the area of the waveform as opposed to peak
57
why is it difficult to capture the underlying neural response with an average? (big limitation)
• 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
What are ways to reduce confounds in EEG
* 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
Ways to reduce confounds: physical properties
* 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
Ways to reduce confounds: using identical stimuli In diff conditions
* 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
Ways to reduce confounds: motor responses
* 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
Ways to reduce confounds: vary conditions within blocks
* 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
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?
No each cell in V1 has a small receptive field and responds to stimuli in that receptive field
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