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Q-Pro
Human Brain Institute
Russia-Switzerland-USA
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CONTENTS
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1. Personal and clinical
data – Questionnaire
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2
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2. Description of the
procedure of EEG recording and analysis.
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3
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3. Automated spike detection
- search for signs of epileptic discharges
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4
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4. Eyes Open – background
EEG rhythms and activities
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5
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5. Eyes Closed - background
EEG rhythms and activities
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11
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6. GO/NOGO task –EEG
rhythms and activities
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16
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7. Behavioral data and
cognitive Event Related Potentials (ERPs) in GO/NOGO
task
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18
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8. Event Related De/Synchronization
- ERD/ERS
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21
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9. Conclusion
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23
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10. Recommendations for therapy
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24
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Appendix 1. Methodological
principles for QEEG/ERP assessment.
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26
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Appendix 2. Artifact correction
by means of spatial filtration.
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32
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Appendix 2. Glossary
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34
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1. Personal and clinical data
–Questionnaire[1].
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Questions
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Descriptive answers
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Yes
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Category
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Name
(family name, given name)
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XXXXXXX
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General information
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Date
of birth (Day.Month.Year)
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xx.xx.xxxx
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Gender
(M-male, F-female)
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M
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Handed
(L- left, R – right)
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R
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Diagnosis
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ADHD,
Dyslexia, Dyspraxia
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Reason
of having QEEG assessment
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Want
a neurotherapy treatment
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Medication
taken now.[2].
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No
medication or drugs are taken now.
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Source
of referral
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Birth
trauma and/or hypoxia
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Pre- and post-natal history
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Started
to talk too late
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Head
trauma (with loss of consciousness)
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Poor
grades in school, poor performance at work
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Often
having headaches and/or migraines.
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General Brain Regulation
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Feel
weak and passive during daytime
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Sleep-related
difficulties
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+
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Abuse alcohol
or drugs.
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Perceptual
difficulties (paresis, dyslexia, Wernike aphasia,
neglect…)
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+
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Sensory system
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Autistic
spectrum behavior
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Motor-related
difficulties (akenesia, bradokinesia, tremor, rigidity,
Broca aphasia…)
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Motor system
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Attention-related
difficulties
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+
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Executive system
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Impulsiveness
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Difficulties
in correcting behavior
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Psychosis
(hallucinations, delusions…)
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Occupied
by mostly positive thoughts, manic
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Affective system
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Occupied
by mostly negative emotions, depressed
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Anxious
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Poor
memory for recent events
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+
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Memory system
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Other
forms of memory deficit
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2. Description
of the procedure of EEG recording and analysis.
EEG
was recorded by means of the Mitsar (Mitsar, Ltd.) amplifier[3]
from 19 electrodes (Fp1, Fp2, F7, F3, Fz, F4, F8, T3, C3,
Cz, C4, T4, T5, P3, Pz, P4, T6, O1, O2 sites in the International
10-20 system) with 250 Hz sampling rate in 0.3 – 70 Hz frequency
range in the following conditions: 1) eyes opened (EO)
– at least 3 minutes, 2) eyes closed (EC) – at least 3 minutes,
and 3) a modification of GO/NOO task (20 minutes).
The task consisted
of 400 trials presenting to a subject every 3 seconds.
In the task we selected four categories of stimuli: 1) 20
different images of animals –referred to later as A,
2) 20 different images of plants - P, 3) 20 different
images of humans presented together with an artificial sound
- HS[4]. Trials consisted of presentation
of a par of stimuli with interstimulus interval of 1.1 sec.
Four categories of trials were selected: A-A, A-P,
P-P, and P-HS. The trials were grouped into
four sessions with one hundred trials each. In each session
a unique set of five A stimuli, five P and
five HS stimuli was selected. Each session consisted
of a pseudo-random presentation of 100 pairs of stimuli
with equal probability for each category and each stimulus.

The
data were stored on the hard disk in the linked ears reference
montage and processed offline by means of WinEEG software.
The software is based on the 30 years experience obtained
in the laboratory at the Institute of the Human Brain of
Russian Academy of Sciences (director Prof. Dr. Juri Kropotov).
Absolute
and relative magnitude spectra and coherences in all conditions
computed and compared with the corresponding parameters
from the Human Brain Institute (HBI) normative database.
The normative database includes data of about 1000 healthy
people of 7-89 years old age. EEG was recorded in Chur,
Switzerland (under supervision of Dr. Andreas Mueller) in
the Institute of the Human Brain, St. Petersburg, Russia
(under supervision of Prof., Dr. Juri Kropotov).
Patient’s
event related potentials are subjected to spatial filtration.
The spatial filters are computed on the basis of Independent
Component Analysis preformed with the whole set of ERPs
in healthy individuals. The extracted components are further
compared with the mean values averaged over the corresponding
age group. Each component corresponds to a specific psychological
operation.
3.
Automated spike detection.
The
method automated spike detection is based on temporal
parameters of spikes as well on spatial location of the
corresponding spike dipole[5]. The amplitude-temporal parameters have defined
on the basis of comparison spike detection by the program
and by experienced experts on the data base of more than
300 EEG recordings in epileptic patients. There are three
characteristics that define a spike or a sharp wave in EEG.
They are paroxysmal character, high degree of sharpness
and short duration. These parameters are presented in Fig[6].

The
relative residual energy for dipole approximation of the
detected spike is chosen less than 0.2.
For
this client the automatic spike detection was performed
on EEG in the common average montage for both eyes open
and eyes closed conditions. In total 266 spikes were detected
and averaged. The waveform, topography and dipole approximation
of the averaged spike are presented below.
Note that spiky alpha activity is generated in the left occipital area.


4.
Eyes Open – background EEG rhythms and activities (page1)
Two
fragments of EEG recorded in Eyes Opened (EO) condition
in a reference-free montage - “weighted average according
to Lemos” are presented below. This montage will be further
referred to as the data base montage.
Scale:
50 mcV/cm, speed – 30mm/sec, time constant – 0.3 sec, low
frequency filter – 30 Hz. Vertical and horizontal eye movement
artifact correction was done by means of Independent Component
Analysis (ICA) (see Appendix 2)

4.
Eyes Open – background EEG rhythms and activities (page
2)
Spectra
(EEG power vs. EEG frequency) in Eyes Open condition
for all 19 electrodes in the database
montage are presented below. The spectra are computed as
follows[7]:
1) The interval in EO condition is divided into equal parts
(epochs). The length of an epoch is 4 s. Overlapping of
the epochs is set to 50% so that the first 50% of each epoch
overlaps the final 50% of the next epoch. 2) To suppress
energy infiltration through boundaries of epochs maxima,
each epoch is filtered by the Hanning time window. 3) The
power spectra(periodogram) are computed by means of "fast
Fourier transformation" (FFT) algorithm. 4) Finally
the averaged (over time of recording) spectra are calculated
for each EEG channel separately.EEG rhythms are expressed
in form of spectra peaks. In this client the following
rhythms can be separated (topographies and frequencies are
depicted at the bottom).
Comparison
EEG spectra in eyes open condition with the normative database.
The
comparison was made for absolute and relative magnitudes
on EEG spectrums.
Relative
amplitude was computed as a ratio of the EEG amplitude in
the corresponding frequency to the EEG amplitude averaged
over 3-30 Hz[8] range.
The
bins with statistically significant (t-test) differences
are marked by bars at the bottom of each curve. The smallest
ones correspond to p<0.05 (z-score >2), the largest
ones - to p<0.001 (z-score>2.6), the medium ones –
to p<0.01 (z-score>3). Topographies of significant
deviations from normality are presented at the bottom.
Note: excess of the left temporal-occipital alpha activity
both for absolute and relative values.
Absolute
magnitude.

Relative
magnitude.

4.
Eyes Open – background EEG rhythms and activities (page
4)
The map of theta/beta
ratio (Theta=4-8 Hz. Beta – 13-21 Hz) is presented below
(at the left).
For
comparison, at the right the corresponding map for a group
of healthy subjects is presented.
Theta beta ratio
is called “inattention index” because it negatively correlates
with age and positively correlates with errors in continuous
performance tasks (such as TOVA – Test for variances of
attention or IVA ). In ADHD patients this index is elevated
in comparison to norms[9].
Note NO significant increase of this index at Cz in this patient in comparison
to norms.

4.
Eyes Open – background EEG rhythms and activities
(page 5)
Asymmetry
maps of power spectra in eyes open conditions for 1 Hz bands.
Note that an asymmetry
higher than 50% may be a sign of abnormality[10].

4.
Eyes Open – background EEG rhythms and activities (page
6)
Diagrams
of excessive (in red) or reduced (in blue) coherence in
sagital (top) and coronal (bottom) planes.
Note reduction of coherency in alpha band in frontal areas in coronal planes
and between central-parietal areas in sagital planes.

5. Eyes Closed – background EEG rhythms and activities
(page1)
Two
fragments of EEG recorded in Eyes Closed (EC) condition
in the data base montage.
Scale:
50 mcV/sm, speed – 30mm/sec, time constant – 0.3 sec, low
frequency filter – 30 Hz. Vertical and horizontal eye movement
artifact correction was done by means of Independent Component
Analysis (ICA) (see Appendix 2)


5.
Eyes Closed – background EEG rhythms and activities (page
2)
Spectra
(EEG power vs. EEG frequency) in Eyes Closed condition
for all 19 electrodes in the database montage are presented
below. EEG rhythms are expressed in forms of peaks on spectra.
In
this client the following rhythms can be separated (topographies
and frequencies are depicted at the bottom).

5.
Eyes Closed – background EEG rhythms and activities (page
3)
Difference
spectra Eyes closed – Eyes open.
The
results of subtraction spectrograms in Eyes Open condition
from those in Eyes Closed condition are presented below.
Note
that opening eyes produces increase of alpha activity at
9.3 Hz at the occipital areas. This rhythm dominates on
the spectra[11]
and is named the dominant alpha rhythm.

Comparison
EEG spectra in eyes closed condition with the normative
database.
The
comparison was made for absolute and relative amplitudes
on EEG spectrums.
Relative
amplitude was computed as a ratio of the EEG amplitude in
the corresponding frequency
Absolute
magnitude.

Relative
magnitude.

5.
Eyes Closed – background EEG rhythms and activities
(page 5)
Asymmetry
maps of power spectra in eyes closed conditions for 1 Hz
bands.
Note that an asymmetry
higher than 50% may be a sign of abnormality[12].

6. GO/NOGO task –EEG rhythms and activities (page 1)
Spectra
(EEG power vs. EEG frequency) in GO/NOGO task condition
for all 19 electrodes in the database montage are presented
below. EEG rhythms are expressed in forms of peaks on spectra.
In this client the following rhythms can be identified:
6. GO/NOGO task –EEG rhythms and activities (page 2)
Comparison
EEG spectra in GO/NOGO task condition with the normative
database.
The
comparison was made for absolute and relative magnitudes
on EEG spectrums.
Absolute
magnitude.

Relative
magnitude.

- Behavioral data
and cognitive Event Related Potentials (ERPs) in a GO/NOGO
task
(page
1).
Behavioral
data (omission and commission errors, reaction times and
variances) are presented below.
Note: too many omission errors.

- Behavioral data
and cognitive Event Related Potentials (ERPs) in GO/NOGO
task
(page 2).
ERPs in the GONOGO
task computed for GO, NOGO stimuli and ERP differences (NOGO-GO).
GO stimuli – green, NOGO stimuli (animal-plant) – red,
NOGO-GO – blue. Bars under ERPs represent levels of statistical
significance of deviation from the pre-stimulus interval
(small bar – p<0.05, medium – p<0.01, big – p<0.001).
Note: at the bottom ERPs topographies taken at the maximums of ERPs and ERPs
differences.

- Behavioral
data and cognitive Event Related Potentials (ERPs) in
GO/NOGO task
(page 3).
ICA
analysis of ERPs in GO/NOGO task – comparison with the normative
data base.
Table
of Normal Components.
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Name
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Functional
meaning
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Location
of maximum
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Peak
latency in ms
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Normal
range in ms
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Amplitude in μV
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Normal range in μV
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P1 component
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Index
of information processing in the visual system
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O1,
O2
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130)
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124-148
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24.1
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3.1-17.2
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P2H component
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Index
of information processing in the auditory system
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Fz
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210
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194-216
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16.6
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6.2-14.3
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P3GO component
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Index
of engagement operation
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Pz
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320
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309-357
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7.3
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5.0-11.5
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P2NOGO component
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Index
of comparison operation
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T5,
T6
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260
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223-299
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5.2
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2.2
-12.7
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P3NOGO component
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Index
of monitoring operation
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Fz
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380
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367-400
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2.5
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1.4-3.1
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The
client’s components (green) in comparison to the normative
components (red) and difference components (Client – Norm)
are presented below.
Note strong deviations
in sensory visual information processing component.

8.
Event Related De/Synchronization - ERD/ERS (pages 1 and
2).
The
results of wavelet analysis for GO/NOGO task are presented
below.
The wavelet analysis
provides the Power-Time-Frequency representations of EEG
responses to GO and NOGO trials separately.
X-axis – time
(Zero corresponds to the first stimulus onset). Y-axis
– EEG frequency (from 4 to 40 Hz). Color reflects increase
(red) or decrease (blue) of EEG power in the corresponding
frequency band.
The
main components in this client are:
For
GO+NOGO stimuli:

9. Conclusion:
I. Spontaneous
EEG abnormality.
Spectrograms
of spontaneous EEG in all conditions (Eyes Open, Eyes Closed,
GO/NOGO task) persistently show an abnormality manifested
in:
1)
increase of occipital alpha.
2)
Spiky morphology in the occipital areas.

II. ERPs abnormalities.
ERPs
in GONOGO task show strong deviations from normality in
sensory-related (not executive) components indicating the
hyper-sensitivity of the ventral visual pathway.
III. Event-related
desynchronization (ERD) abnormalities.
ERD
in GO/NOGO task show strong alpha desynchronization at the
occipital areas.
IV. Brain dysfunction
associated with EEG abnormality.
These
QEEG abnormalities are associated with the occipital lobe
dysregulation.
This dysregulation
is manifested in idling of the occipital area and delay
of the sensory component in this area. This pattern is
seen in a dyslexic group.
10. Recommendations
for therapy.
a)
Neurofeedback protocol.
Recommendations
are made on the basis of the bulldozer principle of neurofeedback
and on the client’s complaints.
In
the case of memory problems the protocol might be as follows:
Inhibiting (training DOWN) alpha activity at the left occipital
(O1). The map of deviations from normality at
9 Hz in EEG power in Eyes Open condition in this client
is presented below.
As you can see from
the map electrodes position may be: O1,
Pz bipolar. A spectrogram and an EEG fragment
in EO condition in this client in bipolar montage (O1, Pz) are presented below.
On
the basis of spectrogram the neurofeedback suppression band
for this client is chosen as:
Alpha =8.5-10 Hz.


Appendix 1. Methodological
principles for QEEG/ERP assessment.
Principle
1.
EEG oscillations
and event related potentials reflect different qualities
of brain electrophysiology.
They are obtained
by different computational algorithms: EEG oscillations
are assessed by means of Fourier and wavelet transformations.
ERPs are assessed by averaging techniques and independent
component analysis.
Principle
2.
Different
oscillating patterns of the background EEG (such as theta,
alpha and beta rhythms) reflect distinct processes of modulation
of information processing in neuronal networks.
In the healthy brain,
alpha rhythms are generated in cortico-thalamic reciprocally
connected networks and reflect idling states of sensory
systems. Beta rhythms are generated by the interplay between
excitatory and inhibitory neurons in local cortical networks
and serve as a reset following cortical activation. Frontal
midline theta rhythm is generated in septo-hyppocampal circuits
and is associated with encoding of episodic memory. Any
type of impairment in the corresponding mechanisms can lead
to excess or lack of a particular rhythm when compared with
a normative data.
Normal
rhythms of the human brain.
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Name
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Hz
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Location
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Mechanism of generation
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Function
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Dysfunction
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Posterior alpha rhythms
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8-12
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O1, O2,
Pz (in older people also T5, T6)
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Thalamo-cortical networks. Rebound
Ca++ spikes following inhibition in the
thalamo-cortical neurons.
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Reflects an idling state of the visual
system. Primary and secondary visual information
is shunted but the cortex is ready to promptly process
it.
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Excess of amplitudes (z>2) indicates
idling of the corresponding occipital, temporal or
parietal area. Deficit of amplitude indicates hyper-activation
of the area. A shift into a lower frequency also
indicates idling: the lower frequency, the more sever
is hypo-activation.
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Rolandic (Mu)-rhythm
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9-13
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C3, C4
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Similar to the one of posterior alpha rhythms.
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Reflects an idling state of the somato-sensory system..
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Excess of amplitudes (z>2) indicates
idling of the sensory-motor strip. Deficit of amplitude
indicates hyper-activation of the area.
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Beta rhythms
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13-30
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Mostly in frontal or central areas
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The interplay between excitatory and inhibitory neurons in cortical networks
in the state following strong activation.
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Is associated with resetting the information processing.
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Excess of amplitude usually (but not always) indicates hyper-activation of
the corresponding area.
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Frontal midline theta rhythm
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5- 8
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Fz. Generated in middle prefrontal and anterior cingulate
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Strong activation in the septo-hippocampal circuit induces a burst of theta
that gates the information flow in the hippocampus.
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Reflects the encoding (chunking) information into episodic memory trace.
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Excess in amplitude and especially in duration (more than 1-2 sec) indicates
a dysfunction of the limbic system.
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Principle
3.
ERPs
components are associated with different psychological operations.
For decomposing ERPs
or ERPs difference waves into separate components we use
independent component analysis on a set of ERPs or ERPs
difference waves computed for a large (about 1000) group
of healthy subjects. The extracted components are associated
with distinct psychological operations on the basis of correlation
with behavior and other imaging (such as PET, fMRI) techniques.
An example of grand
averaged ERPs computed for a group of healthy adult (older
than 20 years) subjects (N=796) is presented below. ERPs
were computed in a two stimulus task (see description above)
for two conditions: GO (depicted as green) and NOGO (depicted
as red).

ICA decomposition
was performed as described in (Makage et al., 1999) after
re-referencing to common average reference. In Fig. we
present the results of ICA analysis of the whole set of
ERPs computed for a group of healthy adult subjects for
GO and NOGO conditions. Six independent components were
separated. Each of the component has a unique 2D topography
(left), a unique s-LORETA generators (right), and unique
temporal pattern (middle, right). In the middle, left –
vertically stalking (from younger age -20 years old – to
older age up to 89 years old) thin-color-coded horizontal
bars representing a component at a single subject. Note
the latency (but not topography) of some of the components
increases with age.

It should be stressed
that different psychological tasks may be associated with
different components and, consequently, with different psychological
operations. The main of them are listed in the table below.
Main ERPs components:
|
ERP component
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Task
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Peak latency (ms)
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Location
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Generator
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Functional meaning
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Brain System
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MMN
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Auditory oddball task (passive or active)
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140
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Fz
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Temporal cortex (the largest part) and frontal cortex.
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Automatic comparison of an acoustic stimulus with the sensory trace.
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Sensory system
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P1 and N1
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Any task with stimulus presentation
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Around 100
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Modality specific
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In vicinity of primary sensory areas
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Information processing in sensory systems
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Sensory system
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P3b or engagement component
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Active oddball task in any modality
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Around 300
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Pz
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Widely distributed cortical areas
with higher activities in temporal parietal areas.
The basal ganglia and prefrontal areas are also involved.
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Engagement operation, i.e. activation of posterior anterior regions needed
for executing action.
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Executive system
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P2 comparison component
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Discrimination tasks (active selection from two or many choises
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240-300
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T5, T6 in visual modality
F7, F8 in auditory modality
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Association areas in visual and auditory modalities.
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Active comparison operation follows
automatic comparison operation. Needed for organization
of further actions.
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Sensory system
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P3 NOGO
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GO/NOGO task
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Around 400 ms
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Fz
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Anterior gurus cingulus and medial prefrontal cortex
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Monitoring operation, comparing the results of executed action with the plans
for actions..
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Executive system
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P3a
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Active or passive three stimulus oddball tasks
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Around 300 ms but less than P3b
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Fz
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Widely distributed prefrontal areas
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Attention shift. Activation of prefrontal
top-down circuits needed for controlling information
flow.
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Executive system
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Principle
3.
Brain is decomposed
into basic systems: sensory systems, affective system, executive
system and memory systems.
Each of the system
is characterized by specific rhythms and by ERPs specific
components. Distinct systems are controlled by distinct
neuro-modulators of the brainstem, and consequently, can
be treated by pharmacological interventions in these systems,
such as increasing (or decreasing) the level of neuromodulator
by giving to patients pre-coursors of mediators, blocking
the post-synaptic receptor, blocking the reuptake mechanism,
or and changing the cellular mechanisms of transmission.
Association between psychiatric/neurological diseases and
brain systems are presented in Table below.
|
Disease/System
|
Sensory
|
Affective
|
Memory
|
Executive
|
|
Dyslexia
|
______________
|
|
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Neglect
|
______________
|
|
|
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Depression
|
|
______________
|
|
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Anxiety
|
|
______________
|
|
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Alzheimer’s
|
|
|
______________
|
|
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Parkinson’s
|
|
|
|
______________
|
|
Schizophrenia
|
|
|
|
______________
|
|
OCD
|
|
|
|
______________
|
|
ADHD
|
|
|
|
______________
|
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Addiction
|
|
______________
|
______________
|
______________
|
Principle
4.
Any of the brain
systems obeys to the inverted U law. The law claims that
responses of the system are largest if the activity of the
system stays within the normal range and are abnormally
smaller if the activity turns out to be below or higher
than the normal range of activation.

Fig.
The inverted U law.
(Top)
Schematic representation of the dependence of the overall
activity of a hypothetical neuronal network on the input
that drives this system. (Bottom) Schematic representation
of the dependence of the response of the system on its input.
The response is defined as a change in the activity of the
system as reaction to a small and elementary increase of
the input.
Note that increase of the input (for example, due to a stressful situation)
at two points of the system (depicted by black dots with
arrows) will lead to enhancing or deteriorating performance
depending on the initial state.
The overall activity
of the system can be assessed by spectral analysis of the
spontaneous EEG while system responses are associated with
the corresponding ERPs components. For example, abnormally
high amplitude of beta activity generated in the medial
prefrontal cortex indicates over-activation of this part
of the executive system while abnormally small P3 monitoring
component indicates a reduced response of this system in
situations that need monitoring of actions.
Principle
5.
Brain
disorders can be classified in associated with impairment
of brain systems and diagnosed according to deviations from
normality in the corresponding EEG spectral and ERP parameters.
Scientists tried
to classify brain disorders for centuries. Nowadays, there
are two parallel sets of diagnostic criteria. One is American
Psychiatric Association’s Diagnostic and Statistical Manual
of Mental Disorders (the latest edition is DSM-IV). The
other one is World Health Organization’s International Classification
of Disease (the latest version is ICD-10). Any classification
made on descriptive behavioral level is to some extent arbitrary.
The need for endophenotypes as objective indexes of disorders
could not be overestimated. Several components of QEEG
and ERPs have be suggested as probable candidates for endophenotypes.
Although more systematic research is required the first
results are very promising (see table below).
Table. Classification
of brain diseases and their endophenotypes.
|
Diagnostic category DSM-IV
|
Examples of Disorders
|
Brain System
|
EEG endophenotype
|
ERP endophenotype
|
|
Disorders usually first diagnosed in infancy, childhood, and adolescence
|
ADHD
Autism
Learning disorders
Conduct disorder
Dyslexia
|
Executive system
|
Increase of theta-beta ratio fronto-centrally
|
Decrease of P2 comparison
Decrease of P3 monitoring
|
|
Psychotic disorders
|
Schizophrenia
|
Executive system
|
Increase of beta activity frontally?
|
Decrease of P3b
|
|
Mood disorders
|
Major depression
Bipolar disorder
|
Affective system
|
Left>Right asymmetry in frontal alpha activity
|
Elevated ERPs to negative stimuli
|
|
Anxiety disorders
|
OCD
Generalized anxiety disorder
Post-traumatic stress disorder
|
Executive system
|
Increase of beta activity centrally?
|
Decrease of P3 monitoring
|
|
Delirium, dementia, amnesia and other cognitive disorders
|
Alzheimer’s disease
|
Episodic Memory System
|
Increase of theta activity fronto-centrally
|
Decrease of monitoring components
|
|
Substance-related disorders
|
Heroin addiction
Alcoholism
|
Interaction between Affective and Executive systems
|
Partly similar to OCD
|
Partly similar to OCD
|
Principle
6.
tDCS and neurofeedback
provide electrophysiologically-based tools for activation
or suppression of cortical neuronal networks.
tDCS implies passive
injection of small amount of DC currents that depolarize
(anodal currents) and hyperpolarize (cathodal currents)
cortical pyramidal cells under the stimulation electrode.
Neurofeedback implies active involvement of the subject
in voluntarily changing the EEG parameters recorded from
a given electrode. Our recent studies have shown that the
combination of these two techniques might be the best way
of activating the brain.
Appendix 2. Artifact
correction by means of spatial filtration.
EEG
is contaminated by various artifacts. Eye movement artifacts
are the largest ones. They are generated by vertical and
horizontal eye movements. The main source of the artifacts
is the potential of the eyeball. The eyeball acts as an
electric dipole with the positive pole oriented anteriorly.
Eye blink results in reflexive upward vertical eye movement
that produces positive deflection at frontal areas with
maximum at Fp1, Fp2 electrodes. Eyes
closing is associated with similar artifact, while eyes
opening results in downward vertical eye movement and negative
deflection at Fp1, Fp2 electrodes.
Horizontal e |