This document provides information about EEG recordings and analysis. It discusses topics like the Nyquist theorem, types of EEG recordings, artifacts in EEG like EMG and eye blinks, reviewing EEG characteristics, spectral maps of EEG under different conditions, microstates in EEG, normal and abnormal distributions in EEG data, and life span normative EEG databases.

1. EEG recordings in man
Examples of records and results of
analysis made by Braintune (St.
Petersbuurg) hardware/software.

2. Nyquist Theorem
• The highest frequency which can be
accurately represented is one-half of
the sampling rate.
• The sampling rate here is below the
Nyquist frequency, so the result of
sampling is nothing like the
input:aliasing.
• For practical purposes the sampling
rate should be 10 higher than the
highest frequency in the signal.
•

3. EEG is a difference in potential
between two electrodes
• If two electrodes are “active”, it is called “bipolar”
recording.
• If one electrode is “silent”, it is called “monopolar”
recording. The reference sites: ear lobe, mastoid,
nose.

4. Bipolar vs. monopolar recordings
• Monopolar recording is used in research,
because it enables the researcher to localize
the event of interest.
• Bipolar recording is used in BF, because it
reduces shared artifacts. Electrodes should
be placed on the sites with the strongest
gradients of the potentials under training.

5. EMG and eye blink artifacts in
EEG
• These types of
artifacts can be
detected by visual
inspection.
• Eye blinks can be
excluded from
data analysis.
• EMG should be
taken into
account during
spectral analysis.

6. EEG recorded at Cz
• EEG is a mixture of waves at different
frequencies and amplitudes.

7. EEG recorded at T5
• At each time interval several sine-waves at
different frequencies may be present in the
signal.

8. Quality control of EEG recording
• 1) EEG amplifies must be calibrated with
daily checks
• 2) acquisition parameters must be checked
daily and keep the same
• 3) the same procedures must be employed
in all individuals
• 4) all artifacts must be eliminated or taken
into account prior to spectral analysis.

9. EMG Artifact
• EMG artifact starts as low as 12 Hz and ranges to
300 Hz. Most of the spectrum lies between 30-150
Hz.
• Sites F3, F4, T3, T4, P3, P4 can pick up EMG the
massester and temporalis muscles.
• Posterior electrodes can pick up EMG from
occipitalis, trapezius and supraspinal muscles.
• To avoid this type of artifact one can relax or
position the head properly or change slightly the
position of electrode.
• Fz, Cz, Pz can give a relatively pure EEG signal.

10. EKG artifact
• ECG artifacts occur from the electrodes that
pick up activity from underlying pulsating
blood vessels in the scalp.
• EKG artifact gets more prevalent with
aging.

11. Ocular, blinks and electroretinal
activity
• Eye movement and blinks artifacts occur in
the delta range 0-4 Hz and occur over the
anterior part of the scalp.

12. The noise from the standard AC
electrical line current
• This noise can be diminished by the proper
grounding of the equipment (both computer and
amplifies).
• It could be also eliminated by a so called notch filter
which selectively removes 50 (60 for the US) Hz
activity from the signal.
• This noise could be attenuated by obtaining good
contact of electrodes with the scalp. The electrode
impedance less than 10 kOhms is desirable.

13. EEG recording in man
• Eyes opened condition.
• Examples of different waves.

14. Reviewing EEG
• EEG is characterized by:
• 1) voltage
• 2) frequency (is used for BF)
• 3) spatial location (is used for BF)
• 4) inter-hemispheric symmetries
• 5) reactivity (reaction to state change)
• 6) character of waveform occurrence
(random, serial, continuous)
• 6) morphology of transient events

15. Reviewing EEG: voltage
• Amplitude is the voltage in microvolts
measured from the peak of the wave to the
trough of the wave. Varies from 10 mcV to
100 mcV with average around 20-50 mcV.
•

16. Reviewing EEG: frequency
• Spectrums reflect the amount of energy in a
certain frequency range of EEG.
• Term monorhythmic means that a particular
portion of EEG shows a rhythmic
component in a singular frequency.
• Term polyrhythmic means that several
rhythmic frequencies are present in EEG.
• The presence of large-amplitude delta-
activity may indicate infarct or other lesion.

17. Reviewing EEG: frequency
• Slow (0-4 Hz) and high (more 20 Hz)
frequency bands of EEG may pick up artifacts,
such as eye movements and muscle activity,
and therefore should be evaluated with caution.
• Despite the use of artifact rejection algorithms,
the failure to accurately distinguish true
physiological rhythmicity from the artifacts is a
serious shortcoming of current software
systems and requires the expert assessment.

18. Reviewing EEG: transient events
• A transient is an isolated form or feature that
stands out from the background activity.
• It is called a spike if it has the duration less
than 70 msec.
• It is called a sharp wave if it has the duration
between 70 and 200 msec.
• The presence of large amplitude spikes and
waves may indicate the presence of epilepsy.

19. Maps of EEG spectrums in
standards bands
• Eyes opened
condition.

20. EEG recording in man
• Eyes closed condition.
• Enhancement of alpha waves.

21. Maps of EEG spectrums
• Eyes closed condition

22. EEG
spectrums
• Three conditions (EC, R, M)
are compared to Eyes Opened
condition.
• Two peaks (in theta and alpha
band) with different scalp
distribution are observed.
• Reading and math produce big
(but different) changes in alpha
band and small changes in theta
and beta bands.
• Note that alpha activities are
different for all four conditions
both in distribution and
frequency.

23. EEG spectrums in individual
bands
• Regular theta -
idling rhythm
• Irregular theta -
working activity
• Reading and
math produce
alpha rhythms
that are different
in frequency and
location.

24. EEG as a sequence of micro-
states
• EEG consists of series of
short-lasting quasi-
stationary epochs
corresponding to what
Lehmann et al. (1987) have
called brain functional
micro-states.
• EEG reflects the changes in
the state of neuronal
networks rather than
specific aspects of
information processing.

25. Normal distribution
• When many independent
random factors act in an
additive manner to create
variability, data will follow a
bell-shaped distribution called
the Gaussian distribution. This
distribution is also called a
Normal distribution.
• Although no data follows that
mathematical ideal, many
kinds of data follow a
distribution that is
approximately Gaussian

26. Dysfunction as a deviation from
normal distribution
• If we measure some
parameter in the
population with some
brain dysfunction,
then this parameter
must has a different,
not Gaussian
distribution.
• There are statistical
tests that measure this
difference.

27. Bimodal distribution in ADHD?
• Clinicians who diagnose this disorder have been criticized
for merely taking a percentage of the normal population
who have the most evidence of inattention and continuous
activity and labeling them as having a disease. In fact, it is
unclear whether the signs of ADHD represent a bimodal
distribution in the population or one end of a continuum of
characteristics. This is not unique to ADHD as other
medical diagnoses, such as essential hypertension and
hyperlipidemia, are continuous in the general population,
yet the utility of diagnosis and treatment have been proven.
Nevertheless, related problems of diagnosis include
differentiating this entity from other behavioral problems
and determining the appropriate boundary between the
normal population and those with ADHD.

28. Life span normative EEG
database (LNDB)
• There are at least four eyes-closed LNDB:
• 1) E. Roy John et al. (1977)
• 2) Frank Duffy et al. (1994)
• 3) Robert Thatcher et al. (1987)
• 4) Barry Sterman et al. (199?)

29. Three goals of LNDB
• 1) to assess the neurological basis for the
patient’s complains (the issue of organicity)
• 2) to identify the weakness of
electrophysiological organization of the
brain (the issue of neurotherapy design)
• 3) to evaluate the efficacy of treatment ( the
issue of treatment evaluation)
• Thatcher, 1999

30. Active and “passive” conditions
for NDB
• 1) Eyes opened and eyes closed conditions
are often used in NDB, because of
simplicity and relative uniformity of
recording conditions.
• 2) Active tasks depend of many
uncontrolled factors, such as intensity of
stimuli, the subject’s involvement, the
distance from stimuli, etc. There are no
standards for active conditions.