Lecture 2 - CNS Flashcards

1
Q

modern EEG device components

A
A/D converter
battery
USB relayer
acquisition computer
stimulus computer
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2
Q

why is EEG with battery

A

main would create electrical noise

to exclude risk of electrical shock

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3
Q

why two computers for EEG measurment

A

to ensure both have enough resources

less of a problem with modern computers

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4
Q

Nyquist rate

A

you sampling rate has to be at least twice as high as the highest expected frequency
in practice it’s usually 3 to 5 times as high

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5
Q

Nyquist frequeny

A

the maximal frequency you can reliably extract with your sampling rate
i. e. sampling rate / 2

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6
Q

aliasing

A

when sampling rate is too low
high frequencies get recorded as low frequencies
sample connects peaks to minimums

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7
Q

CD sampling rate

A

44 kHz

because lowest distinguishable frequency is 22 kHz

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8
Q

greatest sources of noise in EEG

A

muscle movements, e. g. chewing
blinks
lateral eye movements

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9
Q

drifts

A

noise from mains

50 hz in Europe, 60 in us

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10
Q

slow voltage drifts

A

due to electrode polarisation, sweat etc.

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11
Q

pre-processing pipeline

A
  1. re-referencing
  2. filtering
  3. ocular correction with ICA
  4. artifact rejection
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12
Q

re-referencing

A

changing the location of the reference electrode

the artificial zero, that is never actually zero

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13
Q

common reference electrode locations

A

most common is mastoids
also earlobes
or tip of the nose

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14
Q

common mode noise

A

when impedance differs between active, ground and reference electrodes
the higher the impedance the more common mode noise
solution: high impedance input amplifiers

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15
Q

getting rid of common mode noise

A

(A-G) - (R - G) = A - R

= active electrode - reference

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16
Q

pattern decompostion

A

location of reference electrode does not matter

17
Q

high-pass filer

A

lets only high frequencies through

18
Q

low-pass filter

A

lets only low frequencies through

19
Q

notch filters

A

filter out specific frequencies

20
Q

band-pass

A

removes a range of frequencies

between two defined points

21
Q

band-stop filters

A

attenuated frequencies between x and y

22
Q

disadvantage filters

A

always change the signal
throw out data
can change shape of the ERP

23
Q

ocular correction

A

with ICA
or Gratton & Coles method
VEOG and HEOG

24
Q

VEOG

A

vertical electric oculogram

one electrode above, one below the eye

25
Q

HEOG

A

horizontal electro oculogram

one electrode lateral of each eye

26
Q

Gratton & Coles method

A

regressing out blinks
with linear regression
problem: might remove actual brain activity from VEOG

27
Q

ICA

A

independent component analysis
for approximating solution to superposition problem
blinks and eye movements are biggest contributors
therefore ICA works good on them
number of component = number of electrodes
assumes normal distribution of random activity
everything non-normal is something important
rotates distribution to best fit the observation

28
Q

after ocular correction

A

components can be removed manually

ICA can be repeated and components can be thrown out as much as you want

29
Q

artifact rejection

A

removing whole trials containing artifacts
throwing data out instead of correcting it
can be done automatically or by visual inspection