QEEG
Quantitative electroencephalography (QEEG)
Our services are based on the results of Individual quantitative electroencephalography (QEEG)
assessment. Additional event related potential (ERP) measures may be added to get a clear individualized
picture of the person's brain function. Traditional neuropsychological testing is also often included.
Neurofeedback or Brain Computer Interface training is well documented in hundreds of well controlled
research studies and among the world's most recognized neuroscience authorities it is not consider
experimental. Due to the complexity and costs associated with training and certification, most doctors are
unaware of the benefits and methods.
The EEG or electroencephalogram has long been used to record and study the electrical activity of the
outermost layer of the brain – the cerebral cortex. It is usually thought of exclusively as a way to diagnose
epilepsy (seizure disorders). In this routine EEG, a neurologist or electroencephalographer (EEG
specialist) visually examines the traces of the oscilloscope which show the brain’s electrical activity in the
form of a line with repetitive wave-like activity. Hence the name “brainwaves”.
It is well established that the speed of this EEG waveform, measured as the number of times per second
that the wave goes from one peak to the next (cycles per second or cps), reflects the degree of activation of
the area of the brain beneath the electrode. Slower waveform activity (fewer cycles per second), as in the
delta, theta or alpha traces, indicate lowered blood flow and fuel (glucose) use in that part of the brain.
Faster activity as in the beta trace, shows increased brain activity. These types of brain electrical activity
also reflect the level of arousal of the person: delta activity (2-4 cps) accompanies deep sleep, theta (4-
7cps) states of drowsiness, alpha (8-11 cps) relaxed states. Beta range activity reflects an engaged or
active brain, and, with very fast beta activity, an excited or urgent/emergency state of mind.
In the last decade or so, a more advanced form of EEG has been developed, called quantitative EEG or
QEEG, in which the signal is converted to digital form and compared to a database of individuals without
any known neurologically based disorder. In this way, we are able to analyze the background activity with
sophisticated statistical techniques to reveal patterns invisible to the naked eye. The results of these
analyses can then be presented in graphical form, resulting in topographical displays of brain electrical
activity - sometimes called “brain maps".
Research in several university centers has demonstrated the ability of the QEEG to reveal aspects of brain
function important to the understanding of a variety of neurodevelopmental disorders, including ADHD,
learning disabilities, anxiety, depression, obsessive compulsive disorder, eating disorders, and addictive
disorders. A recent study conducted at NYU has shown that a QEEG study can predict the occurrence of
dementia in the elderly up to 10 years before symptoms appear with a very high degree of accuracy. QEEG
measures of the relative degree of activation in the left versus the right frontal cortex are a good indicator of
the current mood state of the person monitored, and of mood traits such as a tendency toward negative
emotion or mood (depression, anxiety) or positive emotion or mood. The same measures distinguish
children who were identified as having an anxious temperament in the second year of life from those
without such a temperament.
Interestingly, researchers at the University of Wisconsin have used these same measures of the relative
degree of activation in the left and right frontal cortex to show that when individuals with Autistic Spectrum
Disorder are shown photographs of people making strong emotional facial expressions, negative
emotional centers are activated in the brain. In addition, QEEG measures have allowed for reliable
prediction of response to psychiatric medications independent of symptom pattern and for the
determination of whether or not a depressed individual will respond positively to antidepressant medication
within only 48 hours of administration, well before the typical 4-6 week period required for symptom
reduction to begin. So, clearly, the QEEG is revealing information about brain function that is useful for
understanding neurodevelopmental problems.
In addition, research and clinical experience has shown that quantitative EEG assessment of brain function
can be used to predict what the phenotypes of ADHD and depression and psychiatric medications an
individual is likely to respond favorably to. This allows for the informed prescription of medication based on
the underlying brain physiology. Use of this medication-referenced EEG can eliminate the often
complicated and trying process of selecting medication through trial and error, and can be helpful with
individuals who have not responded well to multiple medications.
QEEG testing continues to have legal (Tramontano, 2006) and clinical support for cognitive functions
problem and traumatic brain injury (Thornton, 2009).
Our services are based on the results of Individual quantitative electroencephalography (QEEG)
assessment. Additional event related potential (ERP) measures may be added to get a clear individualized
picture of the person's brain function. Traditional neuropsychological testing is also often included.
Neurofeedback or Brain Computer Interface training is well documented in hundreds of well controlled
research studies and among the world's most recognized neuroscience authorities it is not consider
experimental. Due to the complexity and costs associated with training and certification, most doctors are
unaware of the benefits and methods.
The EEG or electroencephalogram has long been used to record and study the electrical activity of the
outermost layer of the brain – the cerebral cortex. It is usually thought of exclusively as a way to diagnose
epilepsy (seizure disorders). In this routine EEG, a neurologist or electroencephalographer (EEG
specialist) visually examines the traces of the oscilloscope which show the brain’s electrical activity in the
form of a line with repetitive wave-like activity. Hence the name “brainwaves”.
It is well established that the speed of this EEG waveform, measured as the number of times per second
that the wave goes from one peak to the next (cycles per second or cps), reflects the degree of activation of
the area of the brain beneath the electrode. Slower waveform activity (fewer cycles per second), as in the
delta, theta or alpha traces, indicate lowered blood flow and fuel (glucose) use in that part of the brain.
Faster activity as in the beta trace, shows increased brain activity. These types of brain electrical activity
also reflect the level of arousal of the person: delta activity (2-4 cps) accompanies deep sleep, theta (4-
7cps) states of drowsiness, alpha (8-11 cps) relaxed states. Beta range activity reflects an engaged or
active brain, and, with very fast beta activity, an excited or urgent/emergency state of mind.
In the last decade or so, a more advanced form of EEG has been developed, called quantitative EEG or
QEEG, in which the signal is converted to digital form and compared to a database of individuals without
any known neurologically based disorder. In this way, we are able to analyze the background activity with
sophisticated statistical techniques to reveal patterns invisible to the naked eye. The results of these
analyses can then be presented in graphical form, resulting in topographical displays of brain electrical
activity - sometimes called “brain maps".
Research in several university centers has demonstrated the ability of the QEEG to reveal aspects of brain
function important to the understanding of a variety of neurodevelopmental disorders, including ADHD,
learning disabilities, anxiety, depression, obsessive compulsive disorder, eating disorders, and addictive
disorders. A recent study conducted at NYU has shown that a QEEG study can predict the occurrence of
dementia in the elderly up to 10 years before symptoms appear with a very high degree of accuracy. QEEG
measures of the relative degree of activation in the left versus the right frontal cortex are a good indicator of
the current mood state of the person monitored, and of mood traits such as a tendency toward negative
emotion or mood (depression, anxiety) or positive emotion or mood. The same measures distinguish
children who were identified as having an anxious temperament in the second year of life from those
without such a temperament.
Interestingly, researchers at the University of Wisconsin have used these same measures of the relative
degree of activation in the left and right frontal cortex to show that when individuals with Autistic Spectrum
Disorder are shown photographs of people making strong emotional facial expressions, negative
emotional centers are activated in the brain. In addition, QEEG measures have allowed for reliable
prediction of response to psychiatric medications independent of symptom pattern and for the
determination of whether or not a depressed individual will respond positively to antidepressant medication
within only 48 hours of administration, well before the typical 4-6 week period required for symptom
reduction to begin. So, clearly, the QEEG is revealing information about brain function that is useful for
understanding neurodevelopmental problems.
In addition, research and clinical experience has shown that quantitative EEG assessment of brain function
can be used to predict what the phenotypes of ADHD and depression and psychiatric medications an
individual is likely to respond favorably to. This allows for the informed prescription of medication based on
the underlying brain physiology. Use of this medication-referenced EEG can eliminate the often
complicated and trying process of selecting medication through trial and error, and can be helpful with
individuals who have not responded well to multiple medications.
QEEG testing continues to have legal (Tramontano, 2006) and clinical support for cognitive functions
problem and traumatic brain injury (Thornton, 2009).
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