L9: MEG Event Related Analyses

Question 1

Event-related analyses in MEG happens when

Answer 1

we got data preprocessed and taking as much artefacts as we can

Question 2

The most popular statistical analysis for EEG/MEG is

Answer 2

event-related analyses

Question 3

The effects of averaging time course over multiple repetitions of condition, to increase SNR, depends on - (2)

Answer 3

kind of response - only work if responses are consistent and happen same time in different trials

can improve SNR but lose signal if responses are not consistent

Question 4

What does this diagram show - evoked responses? - (3)

Answer 4

Perfect sample as responses on 3 different trials is identical and has same time course - (looking 100ms after stimulus onset) = time-locked

The averaging of 3 different trial’s response gets same strong peak (all peaks line up - phase-locked)

(evoked response)

Question 5

What is evoked response?

Answer 5

Time locked and phase lock

Question 6

What does time-locked mean?

Answer 6

Same amount of time after stimulus onset

Question 7

What does phase lock means

Answer 7

At that time its the same phase

Question 8

Diagram of cycle, amplitude phase and explain what phase is (2)

Answer 8

phase is where we are in oscillation

we have up and down measure of activity and phase is whether we are at baseline, peak or second hit to baseline or at bottom

Question 9

Evoked responses are good to average across trials and thus use

Answer 9

event-related analyses

Question 10

Induced responses is when responses are not

Answer 10

phase-locked

Question 11

Diagram of evoked vs induced responses

Answer 11

Question 12

Diagram of evoked vs induced

For induced - (3)

Answer 12

Responses are at slightly different times and because slightly different phases

Time locked as 100 milliseconds after stimulus onset, all responses are happening so all around 100 ms

Not phase locked as peaks are not same and when we average we get reduced signal and unlikely to miss effects so no longer improving SNR

Question 13

Event-related analyses depend on averaging so

Answer 13

can used on evoked responses but not induced responses (can’t average)

Question 14

We don’t average when - (2)

Answer 14

responses that are not time-locked (e.g., changes in attention or steady-state or resting state-analyses) as well as responses that are not phase-locked

bad to average across time course of trials

Question 15

For responses that are not time-locked and phase-locked we instead calculate

Answer 15

power in a given frequency per trial and average those (lose phase info as it is varying)

Question 16

When we have induced responses, what analysis we do?

Answer 16

frequency-based analyses

Question 17

An event-related potential (ERP) is created In EEG when

Answer 17

averaging over many trials across their time courses gets a complex waveform

Question 18

An ERP asks in EEG

Answer 18

when (and broadly where -topography spatially) is there a change in strength of the electric potential

Question 19

What does event-related analyses give us in EEG

Answer 19

ERP

Question 20

Diagram of ERP in EEG and what graph shows? - (4)

Answer 20

N = negative effects

P = positive effects

Label by number they happen in data (e.g., N1, N2, P1,P2) - label positive and negative deflections sequentially

Negative voltages are plotted upwards

Question 21

In ERP in EEG, you are measuring the - (2)

Answer 21

amplitude (strength) of responses and response latency (how long after stimulus presentation [0ms] it occurs

ERPs can be compared across conditions e.g., clinical groups etc..

Question 22

Diagram of latency and amplitude what it shows EEG ERP - (2)

Answer 22

• Amplitude = how high peak is from baseline
• latency - was response after 100 or 200 ms

Question 23

ERP components can be given standard labels

Answer 23

by approximate time they occur in milliseconds

Question 24

Why is it useful to give ERP components standard labels by the approximate time they occur in milliseconds?

Answer 24

Able to discuss EEG findings across studies

Question 25

ERP components can be given standard labels by the (approximate) time they occur in milliseconds - (6)

Answer 25

P100 – basic visual response (occipital) - positive effect after 100 ms N100 – basic auditory response (more anterior) - negative effect after 100 ms N170 – to face stimuli - negative effect after 170 ms P300 – decision making Lateralized readiness potential (LRP) ( an indicator of motor planning) N400 – semantic processing (e.g., differences in response at N400 when given sentence 'John ate democry at dinner' vs 'John ate broccili' at dinner')

Question 26

Event-related analyses is most widely used approach in

Answer 26

MEG

Question 27

In event-related analyses in MEG it pools over

Answer 27

lots of trials and average out the noise to get clearer signals

Question 28

In event-related analyses in MEG, it assesses

Answer 28

the time course of changes in magnetic field after stimulus presentation

Question 29

In MEG event-related analyses we record a

Answer 29

magnetic evoked potential (MEP) - MEG version of ERP

Question 30

The MEP asks

Answer 30

when (and broadly where) is there a change in the magnetic field strength

Question 31

Note that MEP can also stand for

Answer 31

Motor Evoked Potential - a paradigm where electrical or magnetic stimulation causes a motor response – make sure you don’t get confused!

Question 32

Diagram of butterfly plot in MEG shows

Answer 32

Different sensors and magnetic field strength shown across time and black is average

Question 33

In components of MEP, the sign of deflections is less stereotyped than ERPs in EEG as...

Answer 33

we usually prefix them with M for magnetic rather than P for positive and N for negative

Question 34

In components of MEP, the sign of deflections is less stereotyped than ERPs in EEG for example.. - (2)

Answer 34

For example, the M100 is an early visual response, the M170 is associated with stimuli such as faces The M170 can appear as a positive or negative change in the magnetic strength

Question 35

Diagram example of MEP components less stereotyped - (3)

Answer 35

Around 170ms we get negative effect for faces and scrambled faces on left In another graph to right around 170ms we get positive effect for faces and scrambled faces For incidental reasons (e.g., cortical folding)

Question 36

Typical in MEG to use senor topographies of magnetic field strength at a single time point (e.g., 170 ms) or averaged across time window to show

Answer 36

spatial distribution of MEPs

Question 37

Diagram of sensor topography in MEG

Answer 37

Question 38

The sensor topography in MEG can differ between participants because of

Answer 38

individual differences in cortical folding and overall brain anatomy

Question 40

The sensor topography in MEG can look different from EEG topographies for identical experimental condition because

Answer 40

magnetic fields are at right angles to electrical potential differences

Question 41

Diagram of how we make comparisons between conditions in MEG using butterfly plots - explain

Answer 41

take butterfly plot of faces subtracted from scrambled faces to give our difference

Question 42

In MEG we can compare its response in two conditions - (2) butterfly plots

Answer 42

We can subtract the time courses for each condition and look at the difference in activity Can test for significant differences at the group level e.g., with t-test per time point (details in lecture 11) - see if its different from 0 and difference greaer than 0 and outside CI -sig Asks – when do the responses differ between two conditions?

Question 43

In MEG we can compare its response in two conditions - (3) topographies of head spatially -where is the difference?

Answer 43

Also possible to subtract topographies across the whole head In general, we will do group-level statistics such as t-tests on data like this (more details in lecture 8) Asks – (broadly) where do the responses differ between two conditions? (until we go into source space – lecture 11)

Question 44

In MEG calculate global power by...

Answer 44

summarising the MEG activity across all sensors -quick check of seeing if something is different in responses in conditions

Question 45

Global field power can be thought of

Answer 45

average amount of activity detected by scanner -summing everything across

Question 46

Global field power sometimes can show... but can not... - (2)

Answer 46

coarse differences between conditions and when they occur but can not tell us where

Question 47

What does power mean in global field power?

Answer 47

amplitude squares so values are always positive

Question 48

Diagram of global field power shown in the bottom of all the time coruse we run

Answer 48