Lecture 3: EEG part 2

Question 1

participant generated noise

Answer 1

• eye blinks
• electrical interference
• muscle activity
• head movement

Question 2

Muscle activity

Answer 2

• Generates electrical currents
• Can be removed or eliminated by asking participants to relax.

Question 3

Eye movements and blinks

Answer 3

• The eye has a strong electromagnetic field that is established by neurons in the retina.
• Should record eye movements with using eye-trackers or EEG electrodes near the eyes.

Question 4

Bell’s phenomenon

Answer 4

• When the eye blinks, the eyeballs move upwards.
• The retina is negatively charged, and the corneas is positively charged.
• We can see these deflections on the EEG data

Question 5

Electrical interference

Answer 5

• Unavoidable
• Reducing by correct wiring and shielding rooms.
• Interference from TVs, phones, pacemakers
• However, EEG has high discrimination and input impedance - usually rejects extreme interference

Question 6

Electrodes and equipment

Answer 6

• Faulty equipment can be an artefact
• Movement of electrodes can cause severe artefacts
• Make sure electrodes are securely attached.

Question 7

Impedance

Answer 7

Impedance is a term that refers to the electrical resistance of the scalp, measured in kΩ. The higher the electrical impedance of the scalp, the greater will be the impact on the recording

Question 8

how to have low impedence

Answer 8

• Make sure participants have their hair washed and dried
• No pins or hair clips

Question 9

Types of analysis

Answer 9

1. Frequency-based analysis: not about precise timing of stimulus related activity, but around general mental states
2. ERPs: study brain processes in relation to events or stimuli

Question 10

Pre-processing

Answer 10

Transforming raw data into data suitable for interpretation and analysis.

Question 11

What does pre-processing do?

Answer 11

• removes noise e.g. blinks, movement

Question 12

Steps in pre-processing

Answer 12

1. filter data - digital filters are used to reduce noise.
2. removing bad channels - automatically detects bad electrodes
3. re-referencing: reference electrodes placed in neutral place, average of two mastoids/earlobes or average of all electrodes often used.

Question 13

Frequency based analysis

Answer 13

Examines how frequencies vary in the brain, depending on changes in internal states or environment (5 different wave bands)

Question 14

What can frequency-based analysis do?

Answer 14

• reveal mental, affective or cognitive state of participants
• reveal abnormal brain activities such as epilepsy or sleep disorders.

Question 15

How to start frequency-based analysis

Answer 15

• record EEG data for 2 minutes with eyes open
• record 2 mins with eyes closed

Question 16

Eyes closed and open: FBA

Answer 16

• Closed: higher frequency alpha band - usually see alpha when eyes are closed.
• Alpha power reduced when eyes open - this is called Alpha blocking
• Alpha power increases when eyes close again.

Question 17

differential amplifier

Answer 17

amplifier takes two inputs and displays the output as the difference between two outputs

Question 18

Alpha rythm

Answer 18

• Upward deflections: negative polarities, represent the eyeballs moving down and eyes opening
• Downward deflections: positive polarities, eyeballs moving upwards as the eyes close (Bells)

Question 18

bipolar montage

Answer 18

• with FBA, a further difference is taken than the differential amplifier
• further difference is taken by two active eletrodes
• this will then create a tracing, which then becomes a chain

Question 19

Characteristics of Alpha example.

Answer 19

• Alpha rhythm is blocked with the eye opening, and re-emerges after eye closure
• this is known as reactivity

Question 20

Frequency of alpha example.

Answer 20

• should normally be between 8-12
• can assess by looking at a second of artefact free recoding when eyes are closed
• 11 cycles per second, this is considered normal

Question 21

Amplitude of alpha example.

Answer 21

• switch to referential montage instead of bipolar montage
• insert scale legend to estimate alpha amplitude
• measure by looking at total deflection from lowest to highest point
• this is 1/3, meaning it’s between 40-50 mvs
• this is normal

Question 22

Symmetry of alpha rhythm example.

Answer 22

• shift scale legend to other hemisphere
• common to have higher voltage on right than left
• asymmetry fine, as long as less than 50%

Question 23

Distribution of alpha rhythm.

Answer 23

• normally in the posterior head regions; the particularly occipital electrodes

Question 24

Goal of ERPs

Answer 24

collect brain processes triggered by an event
- events are a time period of interest usually in an experiment.

Question 25

Event codes

Answer 25

• Cars vs faces shown
• Embed event codes for the time of the experiment that corresponds to the event of interest
• e.g. event code for stimulus onset, and response (correct or incorrect)

Question 26

Uncovering ERP from messy data

Answer 26

1. have sufficient number of events - at least 50 points of interest
2. pre-processing: filtering, re-referencing etc.
3. epoching: extract data according to event codes, around 1-1.5 millisecs around event
4. baseline correction: make epochs the same scale, take average signal from baseline period (time before event) and subtract from entire epoch
5. remove epochs with extreme values
6. average epochs within a subject: average all epochs from a given condition - e.g. all car trials
7. average across subjects: average of all averages for each participant

Question 27

Peaks or components

Answer 27

• all peaks are named
• N1 = first negative
• P1 = first positive
• can also be named by time period.

Question 28

We might analyse ERP…

Answer 28

• peak amplitude
• peak to peak deflection
• latency of peaks
• distribution of peaks on scalp