Quantitative EEG

 

ADVANCED QUANTITATIVE EEG SERVICE IN EUROPE

 

This service is intended for interested AHC families, but is also open to children, adolescents and adults suffering from other genetic dysfunctions affecting the central nervous system and brain, autism, etc.

 

This service will be provided by our colleagues Andrew and Alexander Fingelkurts and Luciana F. Moretti.

 

Andrew and Alexander Fingelkurts, PhDs and researchers, neuroscientists and experts in psychophysiology, consciousness, and identity. BM-Science – Brain and Mind Technologies Research Centre. Espoo, Finland. www.bm-science.com

 

Luciana F. Moretti, Ph.D., specializing in brain care and trauma treatment. Therapist specializing in neurofeedback and quantitative EEG (qEEG). www.lucianamoretti.com

 

Why is qEEG offered instead of EEG?

​​

Applied research

 

Improving well-being and quality of life is one of the most important and urgent goals of modern society. This goal can be achieved through a better understanding of human beings and our society, focusing on the main organ that defines us, the most complex of all: the brain. The integration of neuroscience and information science is essential to achieve this goal. This “marriage” has already generated vast new knowledge, useful for the assessment and optimization of neural and mental capacities (so-called neuroscience-guided well-being).

​

In the field of applied neuroscience, the main concern is to achieve inner balance and, consequently, increase resilience and adaptability to the stress and hectic pace of modern life. This can be achieved through an objective screening procedure that detects the brain's cognitive weaknesses and strengths, thus facilitating the design of tailor-made training protocols. The postmodern, tolerant and peaceful human quantitative electroencephalogram (QEEG) is the only direct neurological assessment tool that is cost-effective, portable, and 100% non-invasive, allowing the identification of individual neurophysiological types.

​

​

Why EEG?

​

Unlike any other neuroimaging technique, only qEEG allows both:

​

1) to measure neuronal activity directly and non-invasively;

2) not to require any overt cooperative behavior from the person;

3) to be independent of language, ethnic or cultural origin and stable from 16 to 60 years old

4) presents very high test-retest reliability (1 h to 5 years);

5) constitutes the most heritable biosignal (genetic factors have a strong influence on the variation of the EEGq);

6) has a temporal resolution suitable for mental and cognitive processes;

7) allows to distinguish the activation of excitatory and inhibitory neurons having the same metabolic needs;

8) allows us to distinguish different time scales of information processing inherent in mental and cognitive processes.

​

There is currently a consensus in the field of cognitive neuroscience that qEEG reflects the conditions, functional properties, and global states of brain functioning and is closely linked to information processing and cognitive activity. The interaction of large populations of neurons gives rise to rhythmic electrical events in the brain, observable at multiple time scales: qEEG oscillations. They underlie many behavioral patterns and sensory mechanisms. QEEG oscillations are phylogenetically preserved, making them functionally relevant.

 

Numerous studies have demonstrated that qEEG characteristics can confound functionally different psychophysiological determinants. Given the extensive scientific data on the frequency-dependent functional significance of qEEG oscillatory activity, different aspects of this activity may help reveal the types of brain function involved in mental activity.

​

In this context, the qEEG is an accurate, unambiguous, orderly and stable reflection of the brain processes underlying cognitive and mental activity.

​

Assessment of neuronal and mental capacities and cerebral (im)balances

​

The assessment of neural and mental abilities and brain (im)balances is performed by recording a digital electroencephalogram (EEG), followed by a complex and advanced statistical and mathematical analysis of quantitative EEG (qEEG), which measures different characteristics of brain electrical activity sensitive to various neuropsychophysiological aspects and neural and mental abilities. Here, neurophysiological information (qEEG) is used as an independent variable to identify psychophysiological brain (im)balances.

​

What is an electroencephalogram (EEG)?

 

It is a “window” into your brain and an objective assessment of neural and mental abilities.

​

EEG is a rapid, non-invasive, painless, and accurate measurement of functional brain activity. The intimate and dynamic structure of this activity is rich in information about underlying cellular and intercellular processes, the brain's physiological, cognitive, and mental functions and resources, as well as its states and conditions. The EEG thus reflects the brain's functional state.

​

Digital EEG is the digital recording of electrical activity generated by the brain. Typically, EEG is obtained using electrodes placed on the scalp using the International 10-20 System with conductive gel (see digital EEG recording procedure). The brain contains millions of neurons, each generating weak electrical voltage fields. The aggregation of these electrical fields creates an electrical measurement that the scalp electrodes can detect and record.

​

The fundamental principle of quantitative EEG (qEEG) is based on the precise and objective quantification of brain electrophysiological activity using computerized analytical and statistical techniques. It allows for more precise information to be extracted from brain electrical activity than simple unassisted visual inspection of the EEG signal. qEEG assesses the organization of a person's physiological, cognitive, and mental brain functions, as well as how the brain uses its strengths and resources to cope with and compensate for stress or illness.

​

Numerous studies have demonstrated the stability and specificity of certain qEEG parameters. These parameters have been quantitatively studied in large samples of healthy individuals from different countries and across a wide range of ages. These studies have confirmed the high specificity of normative distributions of qEEG parameters for different EEG frequencies (delta, theta, alpha, and beta bands). Positive results, differing from normative values in healthy, functioning individuals, have repeatedly been found to be within chance limits, with very high test-retest reliability. The normative data have been extended to the age range of 1 to 95 years for each EEG electrode of the International Standardized System 10-20 and include many qEEG parameters. The independence of qEEG normative descriptors from cultural and ethnic factors allows for objective assessment of functional status and brain integrity in individuals of any age, origin, or background.

​

The scientific literature on qEEG shows that up to 89% of EEGs performed in neurological patients and up to 68% in psychiatric patients provide pathophysiological evidence. These findings have additional utility beyond simply ruling out organic brain lesions. Such EEG studies can also contribute to differential diagnosis, treatment selection, and assessment. For example, several longitudinal studies have shown that initial qEEG profiles can distinguish, among patients with the same DSM diagnosis, those who will respond preferentially to different medications or those who will exhibit a different course of the disease. In its position paper on qEEG, the American Medical EEG Association concludes that qEEG is now of great clinical value in dementia, mood disorders, mild traumatic brain injury, learning and attention disorders, and schizophrenia and its developments. Furthermore, the "scientific", "technical" and "specialist" knowledge of qEEG meets the standards of the Supreme Court rulings, confirming that qEEG is an admissible and clinically valid method for assessing the nature and severity of neuropsychiatric disorders.

​

What types of questions can a qEEG help answer?

​

​

Identify the neurophysiology of mental status changes: are these changes diffuse or focal, are there epileptiform or other specific patterns, or are these changes possibly functional or psychogenic.

 

Identify the presence, location, persistence and type of epileptic activity.

 

Identify the psychiatric nature of an individual's abnormal behavior.

 

Assess the extent of the organic basis of the individual's complaints and their degree of severity.

 

Assess a functional state of the brain.

 

To assess the cognitive, emotional and motivational strategies involved in mental activity.

 

Identify weaknesses and strengths in the organization and neurophysiological state of the individual's brain.

 

To establish a baseline of the current level of brain (dys)function in order to be able to detect stability, improvement or recovery (or lack thereof) in the future and to assess the individual's prognosis.

 

Understanding our children's brain characteristics is a fundamental tool for providing personalized and comprehensive support.

 

To screen for potential risks of neurological/psychiatric illnesses that the person may have or will have in the future.

​

Why a resting-state qEEG?

​

The study of eyes-closed rest provides an important opportunity to examine basic EEG patterns, independent of any task. Rest avoids the disruptive effects of visual scenes, instructions, and task performance (i.e., match with expectancies, strategies employed, motivation or lack thereof, fatigue), and anxiety associated with task performance). Moreover, the resting state appears to be more self-relevant than standard cognitive tasks, which typically cause subjects to divert their attention from personal concerns. The resting state allows for the assessment of “pure” self-relevant baseline brain activity. This activity reflects the individual type of spontaneous processing of an internal mental context (top-down processing), such as random episodic memory and associated imagery, conceptual processing, stimulus-independent thought, self-reflection, internal “narrative,” and the “autobiographical” self. The frequently expressed concern that unconstrained brain activity varies unpredictably does not apply to the passive resting state of the human brain. Scientific studies have shown that it is rather inherently limited by the default functionality of the resting state, which includes the individual's neurophysiological type.

​

In this context, resting-state EEG manifests the fundamental self-organizing mechanisms that regulate multiple brain systems adapting the brain and body to a constantly changing environment. Thus, resting-state EEG reflects the basic/default intrinsic activity that ensures the maintenance of information necessary for interpreting, responding to, and even predicting environmental demands.

​

The human brain represents only 2% of total body mass, but consumes 20% of the body's energy, most of which is used to support continuous neuronal signaling at rest. Task-related increases in neuronal metabolism are generally small (<5%) compared to this significant energy consumption at rest. These facts confirm the importance of neuronal activity at rest, which consumes the majority of brain energy.

​

The resting state provides a baseline against which all cognitive and physiological states can be considered. Cognitively induced fluctuations can only be interpreted within the context of the default system. The default mode of brain activity at rest has a specific functional connotation, with cognitive and emotional processes centered on the subject's internal state rather than on current external events or circumstances.

​

Thus, resting-state qEEG patterns serve as a functional localizer (“context”), providing a priori information about how the brain will respond to a wide variety of tasks and conditions (“content”).

​

Selected references

​

Basar E. Brain function and oscillations: I. Brain oscillations, principles and approaches. Berlin: Springer; 1998.

Basar E. Brain Function and Oscillations: II. Integrative Brain Function. Neurophysiology and Cognitive Processes. Berlin: Springer; 1999.

Basar E. Macrodynamics of electrical activity in the whole brain. Int J Bifurcat Chaos, 2004;14(2):363-81.

Basar E. Oscillations in “brain-body-mind” — A holistic view including the autonomous system. Brain Res, 2008;1235:2-11.

Basar E, Basar-Eroglu C, Karakas S, Schurmann M. Oscillatory brain theory: a new trend in neuroscience. IEEE Eng Med Biol Mag, 1999;18(3):56-66.

Bullock TH. Signals and signs in the nervous system: the dynamic anatomy of electrical activity. Proc Natl Acad Sci USA, 1997;94:1-6.

Buzsaki G, Draguhn A. Neuronal oscillations in cortical networks. Science, 2004;304:1926-29.

Duffy F., Hughes J., Miranda F., Bernad P., Cook P. Status of quantified EEG (qEEG) in clinical practice. Clinical Electroencephalography, 1994;25:VI-XXII.

Fingelkurts Al.A., Fingelkurts An.A. Short-term EEG spectral pattern as a single event in EEG phenomenology. The Open Neuroimaging Journal, 2010;4:130-156.

Fingelkurts Al.A., Fingelkurts An.A., Ermolaev V.A., Kaplan A.Ya. Stability, reliability and consistency of the compositions of brain oscillations. International Journal of Psychophysiology, 2006;59(2):116-126.

Fingelkurts An.A., Fingelkurts Al.A. Alpha rhythm Operational Architectonics in the continuum of normal and pathological brain states: Current state of research. International Journal of Psychophysiology, 2010;76(2):93-106.

Fingelkurts An.A., Fingelkurts Al.A. Brain-mind Operational Architectonics imaging: technical and methodological aspects. The Open Neuroimaging Journal, 2008;2:73-93.

Fingelkurts An.A., Fingelkurts Al.A. Making complexity simpler: Multivariability and metastability in the brain. International Journal of Neuroscience, 2004;114(7):843-862.

Fingelkurts An.A., Fingelkurts Al.A. Timing in cognition and EEG brain dynamics: discreteness versus continuity. Cognitive Processing, 2006;7(3):135-162.

Gevins A. Electrophysiological Imaging of Brain Function. P. 175–188. In: Brain mapping. The methods. Toga A.W., Mazzoitta J.C. (eds). 2 edition. Elsevier Science (USA), 2002; pp. 877.

Gevins A. The future of electroencephalography in assessing neurocognitive functioning. Electroencephalogr. Clinical Neurophysiology, 1998;106:165–172.

Hughes J.R., John E.R. Conventional and Quantitative Electroencephalography in Psychiatry. The Journal of Neuropsychiatry and Clinical Neurosciences, 1999;11:190-208.

Inui K., Motomura E., Okushima R., et al: Electroencephalographic findings in patients with DSM-IV mood disorder, schizophrenia, and other psychotic disorders. Biological Psychiatry, 1998;43:69–75.

John E.R., Karmel B.Z., Corning W.C., Easton P., Brown D., Ahn H., John M., Harmony T., Prichep L., Toro A., Gerson I., Bartlett F., Thatcher R., Kaye H., Valdes P., Schwartz E. Neurometrics: Numerical taxonomy identifies different profiles of brain functions within groups of behaviourally similar people. 1977;196(4297):1393-1410.

John E.R., Prichep L.S., Winterer G., Herrmann W.M., diMichele F., Halper J., Bolwig T.G., Cancro R. Electrophysiological subtypes of psychotic states. Acta Psychiatr Scand 2007;116:17–35.

Johnstone J., Gunkelman J., Lunt J. Clinical database development: characterization of EEG phenotypes. Clinical EEG and Neuroscience, 2005;36(2):99-107.

Kanda P.A.dM., Anghinah R., Smidth M.T., Silva J.M. The clinical use of quantitative EEG in cognitive disorders. Dementia & Neuropsychologia, 2009;3(3):195-203.

Klimesch W. Memory processes, brain oscillations and EEG synchronization. Int J Psychophysiol, 1996;24(1-2):61-100.

Klimesch W. EEG alpha and theta oscillations reflect cognitive and memory performance: a review and analysis. Brain Res Rev, 1999;29:169-95.

Klimesch W. Interindividual differences in oscillatory EEG activity and cognitive performance. In: Reinvang I, Greenlee M, Herrmann M, Eds. The cognitive neuroscience of individual differences. BIS: Oldenburg, 2003.

Knyazev GG. EEG correlates of personality types. Neth J Psychol, 2006;62(2):78-87.

Knyazev G.G., Savostyanov A.N., Levin E.A. Uncertainty, anxiety, and brain oscillations. Neuroscience Letters, 2005;387:121–125.

Lazarev VV. On the intercorrelation of some frequency and amplitude parameters of the human EEG and its functional significance. Communication I: multidimensional neurodynamic organization of functional states of the brain during intellectual, perceptive and motor activity in normal subjects. Int J Psychophysiol, 1998;28:77-98.

Nunez P.L. Physiological Foundations of Quantitative EEG Analysis. In: Shanbao Tong and Nitish V. Thakor, editors. Quantitative EEG Analysis Methods and Clinical Applications. ARTECH HOUSE, 2009, p.1-22.

Pizzagalli D.A., Nitschke J.B., Oakes T.R., Hendrick A.M., et al. Brain electrical tomography in depression: The importance of symptom severity, anxiety, and melancholic features. Biological Psychiatry, 2002;52:73-85.

Prichep L.S., John E.R., Ferris S.H., Rausch L., Fang Z., Cancro R., Torossian C., Reisberg B. Prediction of longitudinal cognitive decline in normal elderly with subjective complaints using electrophysiological imaging. Neurobiology of Aging, 2006;27:471–481.

Sanei S., Chambers J.A. EEG signal processing. John Wiley & Sons Ltd, 2007, pp.289.

Schutter D.J.L.G., Leitner C., Kenemans J.L., van Honk J. Electrophysiological correlates of cortico-subcortical interaction: A cross-frequency spectral EEG analysis. Clinical Neurophysiology, 2006;117:381–387.

Shelley B.P., Trimble M.R., Boutros N.N. Electroencephalographic cerebral dysrhythmic abnormalities in the trinity of nonepileptic general population, neuropsychiatric, and neurobehavioral Disorders. The Journal of Neuropsychiatry and Clinical Neurosciences, 2008;20:7–22.

Thatcher R.W., Lubar J.F. History of the scientific standards of QEEG normative databases. Introduction to QEEG and Neurofeedback: Advanced Theory and Applications” Thomas Budzinsky, H. Budzinski, J. Evans and A. Abarbanel editors, Academic Press, San Diego, Calif (2008).

Thatcher R.W., Biver C.J., North D.M. Quantitative EEG and the Frye and Daubert standards of admissibility. Clinical Electroencephalography, 2003;34(2):39-53.

 

Advanced Quantitative EEG (reporting grid)

 

s4100 Custom analysis

s4102 Custom analysis - scientific consulting: program of nutraceuticals (vitamins/supplements/diet) EXTENDED

s4103 Custom analysis - personalized lifestyle recommendations

s9000 EEG Registration

s9001 Functional state of the brain (for ages above 19 years old; mature brain)

s9002 BrainAge - Biological age of the brain (for ages above 20 years old; mature brain)

s9006 Stress levels characterization

s9007 Brain maturation process (for ages bellow 19 years old)

s9009 Possible deviation of brain activity and degree of this deviation from the norm (for ages above 19

years old; mature brain)

s9010 Potential risks of Mild Cognitive Impairment (MCI) / Vascular Dementia (VD) / Alzheimer Disease

(AD)

s9011 Potential risks of Attention Deficit/Hyperactivity Disorder (AD/HD) and related diseases

s9012 Potential risks of Depression and determination of affective style

s9013 Potential risks of Anxiety and/or anxious individuality

s9014 Potential risks of Schizophrenia and/or schizotypal individuality

s9015 Potential risks of Alcoholism

s9016 Potential risks of Cerebro-vascular insufficiency

s9017 Potential risks of Consequences of Traumatic Brain Injury (TBI)

s9018 Potential risks of Consequences of Post-Concussion Syndrome (PCS)

s9019 Potential risks of long-term consequences of childhood emotional/psychological trauma / risk of

Post-Traumatic Stress Disorder (PTSD)

s9020 Potential risks of Psychopathy

s9021 Potential risks of Migraine

s9022 Potential risks of Bipolar Disorder and related diseases

s9023 Potential risks of Tinnitus

s9024 Potential risks of Neurosis and determination of neurosis type

s9025 Learning style

s9026 Potential risks of Epilepsy

s9027 Degree of recovery from substance abuse / addiction

s9028 Potential risk of Distress and its components

s9029 Potential risk of Obsessive Compulsive Disorder (OCD)

s9030 Brain Executive Functions - Overall status

s9031 Brain Executive Control Function: Ability to Focus (Attention)

s9032 qEEG characteristics related to Autism Spectrum Disorder (ASD)

s9101 Comparison with earlier data (1-3 services)

s9102 Comparison with earlier data (4-5 services)

s9103 Comparison with earlier data (6-10 services)

s9104 Comparison with earlier data (&gt;10 services)

s9220 Brain Mind Audit - EEG screening of the status of brain and mind (1 EEG session)

s9301 Psychopharmacologic response - EEG-guided probabilistic treatment responsivity profile

​

Below is a standard proposal for a qEEG recording for an AHC patient (over 18 years old):

​

s4100 Includes as a basis (i) the possible deviation of brain activity (and degree of this deviation) from the norm and (ii) brain maturational processes status

s9026  Potential risks of Epilepsy

s9029  Potential risk of Obsessive Compulsive Disorder (OCD)

s9031  Brain Executive Control Function: Ability to Focus (Attention)

s9032  qEEG characteristics related to Autism Spectrum Disorder (ASD)

​

Normally the standard proposal can be complemented with:

​

1)   Scientific recommendations based on the results of the analyses, including a nutraceutical program (vitamins, supplements and diet)

2)   Analysis and report for neurofeedback treatment

3)   Functional state of the brain