• Artifact can make everything upside down and meaningless
• Remove artifact to find reliable answers
• VHS Zimbardo #3, ~15 min, E Roy John’s work
Recording Montages
Montages
We measure different electrical potential between sensors
• Bipolar montage = two active channels
• Monopolar or referential montage = one active, one “inactive” such as ear– Linked Ears– Linked Mastoids– Nose
• Average reference montage
Mathematical sharpening techniques (e.g., Laplacian)
Dis/Advantages
• Disadvantage with Monopolar – No such thing as inactive reference (including
ear, neck, nose – cortical signal bleeds through – see scallop shaped topometric)
• Disadvantage with Bipolar– Source of signal not localizable directly, but
only through inference and comparison with other channels
Effect of monopolar reference (linked ears) (temporal lobe activity attenuated)
98% of EEG energy is between 0.1 & 30 Hz
Artifact
• Equipment-related
• Physiological (non-cerebral signals)
• Computational
• Functional (unstable background/state transitions; transients, sleep!)
Impedence <5-10K Ohm
Impedence artifact?
Eye movement & blinks
Muscles: Heart, jaw, and neck
Non-biological artifacts60 Hz, electrode pops
Equipment or gross movement artifacts
Eye blinks in 19 channel NeuroNavigator
Muscle, forehead and jaw
Sleep “artifact”
The Problems with Artifact
Computational Artifact:Undersampling
• Heart beat of 60 sec– 60 samples/min = DC– 90 samples/min = 15
bpm
Spectral Leakage
See ShowDFT.xlsMAGN
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MAGN
MAGN
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Data Windows eliminate leakage significantly
But they come with two artifacts of their own: 1. Smearing (spectral broadening), & 2. Sampling bias
Sampling bias makes analysis sensitive to epoch positions
Arbitrary segmentation (epoching) of signal can produce different spectral means
Artifact Management
Seaming
Power vs Magnitude (the square root of power)
Ln Magn (or Ln Power)
• Ln = Natural log (base e, not base 10) • e = 1 + 1/1! + 1/2! + 1/3! + ... or ~= 2.718…
Skewed distribution of power
Greek Astronomer Hipparchus (190-120BC)
• 6 brightness classification for stars
• Each 2.5x as bright as next classification
• Logarithmic
relationship
Psychophysical Function
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S
ub
ject
ive
Bri
gh
tnes
s (
S)
jnd
un
its
Light energy (I)
Psychophysical Function Fechner’s Law: S = (1/k) log (I)
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ean
mag
nit
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e es
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(S)
Stimulus intensity (I)
Psychophysical Function Stevens’ Power Law: S = aIm
Electric shock (m > 1)
Brightness (m < 1)
Apparent length (m = 1)
Basic law of psychophysics (correspondence between physical energies
and mental experiences) appears linear
Untailored Dominant Frequency
• IAF – individual’s alpha frequency
State Transitions
State transitions
Sources of artifact by frequency
