Status of quantitative EEG (QEEG) in clinical practice, 1994

A scalable platform for acquisition of high-fidelity human intracranial EEG with minimal clinical burden

Human neuroscience research has been significantly advanced by neuroelectrophysiological studies from people with refractory epilepsy-the only routine clinical intervention that acquires multi-day, multi-electrode human intracranial electroencephalography (iEEG). While a sampling rate below 2 kHz is sufficient for manual iEEG review by epileptologists, computational methods and research studies may benefit from higher resolution, which requires significant technical development. At adult and pediatric Stanford hospitals, research ports of commercial clinical acquisition systems were configured to collect 10 kHz iEEG of up to 256 electrodes simultaneously with the clinical data. The research digital stream was designed to be acquired post-digitization, resulting in no loss in clinical signal quality. This novel framework implements a near-invisible research platform to facilitate the secure, routine collection of high-resolution iEEG that minimizes research hardware footprint and clinical workflow interference. The addition of a pocket-sized router in the patient room enabled an encrypted tunnel to securely transmit research-quality iEEG across hospital networks to a research computer within the hospital server room, where data was coded, de-identified, and uploaded to cloud storage. Every eligible patient undergoing iEEG clinical evaluation at both hospitals since September 2017 has been recruited; participant recruitment is ongoing. Over 350+ terabytes (representing 1000+ days) of neuroelectrophysiology were recorded across 200+ participants of diverse demographics. To our knowledge, this is the first report of such a research integration within a hospital setting. It is a promising approach to promoting equitable participant enrollment and building comprehensive data repositories with consistent, high-fidelity specifications towards new discoveries in human neuroscience.

The focused quantitative EEG bio-marker in studying childhood atrophic encephalopathy

Although it is a normal involution process in advanced age, brain atrophy—also termed atrophic encephalopathy—can also occur prematurely in childhood as a consequential effect of brain tissues injury through trauma or central nervous system infection, though in both normal and premature occurrences this condition always presents with loss of volume relative to the skull. A common tool for the functional study of brain activities is an electroencephalogram, but analyses of this have reportedly identified mismatches between qualitative and quantitative forms, particularly in the use of Delta-alpha ratio (DAR) indices, meaning that the values may be case dependent. The current study thus examines the value of Focused Occipital Beta-Alpha Ratio (FOBAR) as a modified biomarker for evaluating brain functional changes resulting from brain atrophy. This cross-sectional design study involves 260 patients under 18 years of age. Specifically, 207 patients with brain atrophy are compared with 53 control subjects with CT scan-proven normal brain volume. All the children underwent digital electroencephalography with brain mapping. Results show that alpha posterior dominant rhythm was present in 88 atrophic children and 44 controls. Beta as posterior dominant rhythm was present in an overwhelming 91.5% of atrophic subjects, with 0.009 p-values. The focused occipital Beta-alpha ratio correlated significantly with brain volume loss presented in diagonal brain fraction. The FOBAR and DAR values of the QEEG showed no significant correlation. This work concludes that QEEG cerebral dysfunctional studies may be etiologically and case dependent from the nature of the brain injury. Also, the focused Beta-alpha ratio of the QEEG is a prospective and potential biomarker of consideration in studying childhood atrophic encephalopathy.

Quantitative EEG (QEEG) Analysis of Emotional Interaction between Abusers and Victims in Intimate Partner Violence: A Pilot Study

Background: The perpetrators of intimate partner violence (IPV) and their victims have different emotional states. Abusers typically have problems associated with low self-esteem, low self-awareness, violence, anger, and communication, whereas victims experience mental distress and physical pain. The emotions surrounding IPV for both abuser and victim are key influences on their behavior and their relationship. Methods: The objective of this pilot study was to examine emotional and psychological interactions between IPV abusers and victims using quantified electroencephalogram (QEEG). Two abuser–victim case couples and one non-abusive control couple were recruited from the Mental Image Recovery Program for domestic violence victims in Seoul, South Korea, from 7–30 June 2017. Data collection and analysis were conducted using BrainMaster and NeuroGuide. The emotional pattern characteristics between abuser and victim were examined and compared to those of the non-abusive couple. Results: Emotional states and reaction patterns were different for the non-abusive and IPV couples. Strong delta, theta, and beta waves in the right frontal and left prefrontal lobes were observed in IPV case subjects. This indicated emotional conflict, anger, and a communication block or impaired communication between abuser and victim. Conclusions: Our study findings suggest brainwave control training via neurofeedback could be a possible therapy in managing emotional and communication problems related to IPV.

Automated Detection of Epileptic Biomarkers in Resting-State Interictal MEG Data

Certain differences between brain networks of healthy and epilectic subjects have been reported even during the interictal activity, in which no epileptic seizures occur. Here, magnetoencephalography (MEG) data recorded in the resting state is used to discriminate between healthy subjects and patients with either idiopathic generalized epilepsy or frontal focal epilepsy. Signal features extracted from interictal periods without any epileptiform activity are used to train a machine learning algorithm to draw a diagnosis. This is potentially relevant to patients without frequent or easily detectable spikes. To analyze the data, we use an up-to-date machine learning algorithm and explore the benefits of including different features obtained from the MEG data as inputs to the algorithm. We find that the relative power spectral density of the MEG time-series is sufficient to distinguish between healthy and epileptic subjects with a high prediction accuracy. We also find that a combination of features such as the phase-locked value and the relative power spectral density allow to discriminate generalized and focal epilepsy, when these features are calculated over a filtered version of the signals in certain frequency bands. Machine learning algorithms are currently being applied to the analysis and classification of brain signals. It is, however, less evident to identify the proper features of these signals that are prone to be used in such machine learning algorithms. Here, we evaluate the influence of the input feature selection on a clinical scenario to distinguish between healthy and epileptic subjects. Our results indicate that such distinction is possible with a high accuracy (86%), allowing the discrimination between idiopathic generalized and frontal focal epilepsy types.

Demonstrating test-retest reliability of electrophysiological measures for healthy adults in a multisite study of biomarkers of antidepressant treatment response

Growing evidence suggests that loudness dependency of auditory evoked potentials (LDAEP) and resting EEG alpha and theta may be biological markers for predicting response to antidepressants. In spite of this promise, little is known about the joint reliability of these markers, and thus their clinical applicability. New standardized procedures were developed to improve the compatibility of data acquired with different EEG platforms, and used to examine test-retest reliability for the three electrophysiological measures selected for a multisite project-Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care (EMBARC). Thirty-nine healthy controls across four clinical research sites were tested in two sessions separated by about 1 week. Resting EEG (eyes-open and eyes-closed conditions) was recorded and LDAEP measured using binaural tones (1000 Hz, 40 ms) at five intensities (60-100 dB SPL). Principal components analysis of current source density waveforms reduced volume conduction and provided reference-free measures of resting EEG alpha and N1 dipole activity to tones from auditory cortex. Low-resolution electromagnetic tomography (LORETA) extracted resting theta current density measures corresponding to rostral anterior cingulate (rACC), which has been implicated in treatment response. There were no significant differences in posterior alpha, N1 dipole, or rACC theta across sessions. Test-retest reliability was .84 for alpha, .87 for N1 dipole, and .70 for theta rACC current density. The demonstration of good-to-excellent reliability for these measures provides a template for future EEG/ERP studies from multiple testing sites, and an important step for evaluating them as biomarkers for predicting treatment response.

The Learning Curve in neurofeedback of Peter Van Deusen: A review article

The Learning Curve (TLC) in neurofeedback concept emerged after Peter Van Deusen compiled the results of articles on the expected electrical activity of the brain. This concept was subsequently tested on patients at four clinics in Atlanta between 1994 and 2001. The aim of this paper was to report the historical aspects of TLC. Articles published on the electronic databases MEDLINE/PubMed and Web of Science were reviewed. During patient evaluation, TLC investigates categories called disconnected, hot temporal lobes, reversal of alpha and beta waves, blocking, locking, and filtering or processing. This enables neuroscientists to use their training designs and, by means of behavioral psychology, to work on neuroregulation, as self-regulation for patients. TLC shows the relationships between electrical, mental and behavioral activity in patients. It also identifies details of patterns that can assist physicians in their choice of treatment.

Electroencephalogram of Healthy Horses During Inhaled Anesthesia

Background

Previous study of the diagnostic validity of electroencephalography (EEG) to detect abnormalities in equine cerebral cortical function relied on the administration of various drugs for sedation, induction, and maintenance of general anesthesia but used identical criteria to interpret recordings.

Objectives

To determine the effects of 2 inhalation anesthetics on the EEG of healthy horses.

Animals

Six healthy horses.

Methods

Prospective study. After the sole administration of one of either isoflurane or halothane at 1.2, 1.4, and 1.6 times the minimum alveolar concentration, EEG was recorded during controlled ventilation, spontaneous ventilation, and nerve stimulation.

Results

Burst suppression was observed with isoflurane, along with EEG events that resembled epileptiform discharges. Halothane results were variable between horses, with epileptiform‐like discharges and bursts of theta, alpha, and beta recorded intermittently. One horse died and 2 were euthanized as the result of anesthesia‐related complications.

Conclusions and Clinical Importance

The results of this study indicate that the effects of halothane and isoflurane on EEG activity in the normal horse can be quite variable, even when used in the absence of other drugs. It is recommended that equine EEG be performed without the use of these inhalation anesthetics and that general anesthesia be induced and maintained by other contemporary means.

EEG brain mapping and brain connectivity index for subtypes classification of attention deficit hyperactivity disorder children during the eye-opened period

Attention deficit hyperactivity disorder (ADHD) is one of the most prevalent neurological disorders. It is classified by the DSM-IV into three subtypes, i.e. 1) predominately inattentive type, 2) predominately hyperactive-impulsive type, and (3) combined type. In order to make the treatment via the neurofeedback or the occupational therapy, quantitative evaluations as well as ADHD subtype classification are the important problems to be solved to enhance an alternative way to treat ADHD. Hence, in this paper, we systematically classify all of these three subtypes by the 19-channel EEG data. Three brain mapping (QEEG) techniques, i.e. absolute power of frequency bands, coherence, and phase lag, are employed to visualize each type of the ADHD. ADHD children with combined type have deficit in delta theta and alpha activity. For the inattentive type, there are excessive delta and theta absolute power in the frontal area as well as the excessive coherence in beta and high beta frequency bands. For the hyperactivity and impulsive type, the behavior is dominated by the slow wave. This information will give benefits to the psychiatrist, psychologist, neurofeedback therapist as well as the occupational therapist for quantitatively planning and analyzing the treatment.

Quantitative EEG and neurofeedback in children and adolescents: anxiety disorders, depressive disorders, comorbid addiction and attention-deficit/hyperactivity disorder, and brain injury

This article explores the science surrounding neurofeedback. Both surface neurofeedback (using 2-4 electrodes) and newer interventions, such as real-time z-score neurofeedback (electroencephalogram [EEG] biofeedback) and low-resolution electromagnetic tomography neurofeedback, are reviewed. The limited literature on neurofeedback research in children and adolescents is discussed regarding treatment of anxiety, mood, addiction (with comorbid attention-deficit/hyperactivity disorder), and traumatic brain injury. Future potential applications, the use of quantitative EEG for determining which patients will be responsive to medications, the role of randomized controlled studies in neurofeedback research, and sensible clinical guidelines are considered.

Guidelines for the recording and evaluation of pharmaco-sleep studies in man: the International Pharmaco-EEG Society (IPEG)

The International Pharmaco-EEG Society (IPEG) presents guidelines summarising the requirements for the recording and computerised evaluation of pharmaco-sleep data in man. Over the past years, technical and data-processing methods have advanced steadily, thus enhancing data quality and expanding the palette of sleep assessment tools that can be used to investigate the activity of drugs on the central nervous system (CNS), determine the time course of effects and pharmacodynamic properties of novel therapeutics, hence enabling the study of the pharmacokinetic/pharmacodynamic relationship, and evaluate the CNS penetration or toxicity of compounds. However, despite the presence of robust guidelines on the scoring of polysomnography -recordings, a review of the literature reveals inconsistent -aspects in the operating procedures from one study to another. While this fact does not invalidate results, the lack of standardisation constitutes a regrettable shortcoming, especially in the context of drug development programmes. The present guidelines are intended to assist investigators, who are using pharmaco-sleep measures in clinical research, in an effort to provide clear and concise recommendations and thereby to standardise methodology and facilitate comparability of data across laboratories.

A data-driven process for the development of an eyes-closed EEG normative database

A normative database constitutes a representative sample of a neurologically and clinically healthy population. The practical utility of a normative EEG database is to evaluate the clinical status of a subject whose EEG patterns statistically diverge from average population patterns. These normative data are daily used in clinical practice and in the evaluation of therapeutical interventions. The main obstacle of all normative databases developed to date is inter-individual variability. Such difficulty has been addressed by stratifying the population by age and then using regression in the EEG groups to bound variability, which is always an approximation. This paper describes the first data-driven EEG normative database that explicitly deals with EEG variability by stratifying the population based on their EEG patterns. The database has been constructed for 84 subjects in eyes-closed condition and has been validated by cross validation, leading to a global specificity of 100%.

Multimodal quantitative neuroimaging databases and methods: the Cuban Human Brain Mapping Project

This article reviews the contributions of the Cuban Neuroscience Center to the evolution of the statistical parametric mapping (SPM) of quantitative Multimodal Neuroimages (qMN), from its inception to more recent work. Attention is limited to methods that compare individual qMN to normative databases (n/qMN). This evolution is described in three successive stages: (a) the development of one variant of normative topographical quantitative EEG (n/qEEG-top) which carries out statistical comparison of individual EEG spectral topographies with regard to a normative database--as part of the now popular SPM of brain descriptive parameters; (b) the development of n/qEEG tomography (n/qEEG-TOM), which employs brain electrical tomography (BET) to calculate voxelwise SPM maps of source spectral features with respect to a norm; (c) the development of a more general n/qMN by substituting EEG parameters with other neuroimaging descriptive parameters to obtain SPM maps. The study also describes the creation of Cuban normative databases, starting with the Cuban EEG database obtained in the early 90s, and more recently, the Cuban Human Brain Mapping Project (CHBMP). This project has created a 240 subject database of the normal Cuban population, obtained from a population-based random sample, comprising clinical, neuropsychological, EEG, MRI and SPECT data for the same subjects. Examples of clinical studies using qMN are given and, more importantly, receiver operator characteristics (ROC) analyses of the different developments document a sustained effort to assess the clinical usefulness of the techniques.

Brain-mind operational architectonics imaging: technical and methodological aspects

This review paper deals with methodological and technical foundations of the Operational Architectonics framework of brain and mind functioning. This theory provides a framework for mapping and understanding important aspects of the brain mechanisms that constitute perception, cognition, and eventually consciousness. The methods utilized within Operational Architectonics framework allow analyzing with an incredible detail the operational behavior of local neuronal assemblies and their joint activity in the form of unified and metastable operational modules, which constitute the whole hierarchy of brain operations, operations of cognition and phenomenal consciousness.

A Comparison of Cognitive and Psychosocial Function for Males Within the ADHD Continuum

Two case studies are presented illustrating neurophysiological dysfunction suggesting input or output deficits in ADHD assessed across multiple domains. Data included child and family history, behavior ratings, information processing, speed, cognitive, neurophysiological, and academic function. Pretreatment data indicated impaired processing speed, excessive slow to fast wave ratios indicative of attentional disregulation, and poor psychosocial function evident in both children. Posttreatment assessment indicated improvement in slow to fast wave ratios and psychosocial functioning for both children. Additional improvement was also noted in cognitive and academic function in MH, the child with learning disabilities, and in processing speed for CX, the child with elevated cognitive function. Neurophysiological disregulation in ADHD may result in input or output impairment differentially affecting cognitive, academic, and psychosocial functioning. Heterogeneity within the ADHD continuum underscores the need for multifaceted assessment to guide diagnosis and treatment. In ADHD children nonresponsive to stimulants, neurofeedback can be a viable treatment to enhance attentional focus and on-task behavior.

Composition of brain oscillations and their functions in the maintenance of auditory, visual and audio–visual speech percepts: an exploratory study

In the present exploratory study based on 7 subjects, we examined the composition of magnetoencephalographic (MEG) brain oscillations induced by the presentation of an auditory, visual, and audio-visual stimulus (a talking face) using an oddball paradigm. The composition of brain oscillations were assessed here by analyzing the probability-classification of short-term MEG spectral patterns. The probability index for particular brain oscillations being elicited was dependent on the type and the modality of the sensory percept. The maintenance of the integrated audio-visual percept was accompanied by the unique composition of distributed brain oscillations typical of auditory and visual modality, and the contribution of brain oscillations characteristic for visual modality was dominant. Oscillations around 20 Hz were characteristic for the maintenance of integrated audio-visual percept. Identifying the actual composition of brain oscillations allowed us (1) to distinguish two subjectively/consciously identical mental percepts, and (2) to characterize the types of brain functions involved in the maintenance of the multi-sensory percept.

Cortex functional connectivity as a neurophysiological correlate of hypnosis: an EEG case study

Cortex functional connectivity associated with hypnosis was investigated in a single highly hypnotizable subject in a normal baseline condition and under neutral hypnosis during two sessions separated by a year. After the hypnotic induction, but without further suggestions as compared to the baseline condition, all studied parameters of local and remote functional connectivity were significantly changed. The significant differences between hypnosis and the baseline condition were observable (to different extent) in five studied independent frequency bands (delta, theta, alpha, beta, and gamma). The results were consistent and stable after 1 year. Based on these findings we conclude that alteration in functional connectivity of the brain may be regarded as a neuronal correlate of hypnosis (at least in very highly hypnotizable subjects) in which separate cognitive modules and subsystems may be temporarily incapable of communicating with each other normally.

A meta-analysis of quantitative EEG power associated with attention-deficit hyperactivity disorder

A meta-analysis was performed on quantitative EEG (QEEG) studies that evaluated attention-deficit hyperactivity disorder (ADHD) using the criteria of the DSM-IV (Diagnostic and Statistical Manual of Mental Disorders, 4th edition). The nine eligible studies (N = 1498) observed QEEG traits of a theta power increase and a beta power decrease, summarized in the theta/beta ratio with a pooled effect size of 3.08 (95% confidence interval, 2.90, 3.26) for ADHD versus controls (normal children, adolescents, and adults). By statistical extrapolation, an effect size of 3.08 predicts a sensitivity and specificity of 94%, which is similar to previous results 86% to 90% sensitivity and 94% to 98% specificity. It is important to note that the controlled group studies were often with retrospectively set limits, and that in practice the sensitivity and specificity results would likely be more modest. The literature search also uncovered 32 pre-DSM-IV studies of ADHD and EEG power, and 29 of the 32 studies demonstrated results consistent with the meta-analysis. The meta-analytic results are also supported by the observation that the theta/beta ratio trait follows age-related changes in ADHD symptom presentation (Pearson correlation coefficient, 0.996, P = 0.004). In conclusion, this meta-analysis supports that a theta/beta ratio increase is a commonly observed trait in ADHD relative to normal controls. Because it is known that the theta/beta ratio trait may arise with other conditions, a prospective study covering differential diagnosis would be required to determine generalizability to clinical applications. Standardization of the QEEG technique is also needed, specifically with control of mental state, drowsiness, and medication.

Routine and quantitative EEG in mild traumatic brain injury

This article reviews the pathophysiology of mild traumatic brain injury, and the findings from EEG and quantitative EEG (QEEG) testing after such an injury. Research on the clinical presentation and pathophysiology of mild traumatic brain injury is reviewed with an emphasis on details that may pertain to EEG or QEEG and their interpretation. Research reports on EEG and QEEG in mild traumatic brain injury are reviewed in this setting, and conclusions are drawn about general diagnostic results that can be determined using these tests. QEEG strengths and weaknesses are reviewed in the context of factors used to determine the clinical usefulness of proposed diagnostic tests. Clinical signs, symptoms, and the pathophysiologic axonal injury and cytotoxicity tend to clear over weeks or months after a mild head injury. Loss of consciousness might be similar to a non-convulsive seizure and accompanied subsequently by postictal-like symptoms. EEG shows slowing of the posterior dominant rhythm and increased diffuse theta slowing, which may revert to normal within hours or may clear more slowly over many weeks. There are no clear EEG or QEEG features unique to mild traumatic brain injury. Late after head injury, the correspondence is poor between electrophysiologic findings and clinical symptoms. Complicating factors are reviewed for the proposed commercial uses of QEEG as a diagnostic test for brain injury after concussion or mild traumatic brain injury. The pathophysiology, clinical symptoms and electrophysiological features tend to clear over time after mild traumatic brain injury. There are no proven pathognomonic signatures useful for identifying head injury as the cause of signs and symptoms, especially late after the injury.

Evaluation and validity of a LORETA normative EEG database

To evaluate the reliability and validity of a Z-score normative EEG database for Low Resolution Electromagnetic Tomography (LORETA), EEG digital samples (2 second intervals sampled 128 Hz, 1 to 2 minutes eyes closed) were acquired from 106 normal subjects, and the cross-spectrum was computed and multiplied by the Key Institute's LORETA 2,394 gray matter pixel T Matrix. After a log10 transform or a Box-Cox transform the mean and standard deviation of the *.lor files were computed for each of the 2394 gray matter pixels, from 1 to 30 Hz, for each of the subjects. Tests of Gaussianity were computed in order to best approximate a normal distribution for each frequency and gray matter pixel. The relative sensitivity of a Z-score database was computed by measuring the approximation to a Gaussian distribution. The validity of the LORETA normative database was evaluated by the degree to which confirmed brain pathologies were localized using the LORETA normative database. Log10 and Box-Cox transforms approximated Gaussian distribution in the range of 95.64% to 99.75% accuracy. The percentage of normative Z-score values at 2 standard deviations ranged from 1.21% to 3.54%, and the percentage of Z-scores at 3 standard deviations ranged from 0% to 0.83%. Left temporal lobe epilepsy, right sensory motor hematoma and a right hemisphere stroke exhibited maximum Z-score deviations in the same locations as the pathologies. We conclude: (1) Adequate approximation to a Gaussian distribution can be achieved using LORETA by using a log10 transform or a Box-Cox transform and parametric statistics, (2) a Z-Score normative database is valid with adequate sensitivity when using LORETA, and (3) the Z-score LORETA normative database also consistently localized known pathologies to the expected Brodmann areas as an hypothesis test based on the surface EEG before computing LORETA.

Detection of EEG background abnormalities in epilepsy by a new spectral index

OBJECTIVE

In epileptic disorders, EEG background activity is disorganized in or near the epileptogenic focus and spectral EEG analysis (SEA) can provide useful information about the focus. We tried to develop a new spectral index from basic spectral parameters to detect the epileptic abnormalities at EEG background activity.

METHODS

A new spectral EEG index, epileptic abnormality index (EAI), was constructed from frequency band power and power asymmetry parameters. Within the index, parameters were weighted due to both conventional EEG knowledge and their power in discrimination healthy subjects from patients. EEG background activity from 99 epileptic patients and 146 healthy subjects was examined both by EAI and by a conventional SEA method, by using z-scoring statistic. Each test results were compared with visual EEG interpretation of subjects.

RESULTS

In patient groups, EAI was most successful in lateralization of epileptic abnormalities. It was also helpful in discrimination of epileptic patients from normals in the case where visual EEG interpretation was 'normal'.

CONCLUSIONS

EAI depends on basic spectral parameters and it combines statistical methods and clinical knowledge about EEG. It increases the analysis capacity of SEA in evaluation of EEG background activity.

SIGNIFICANCE

EAI is a new and useful approach in detection of EEG background abnormalities in epilepsy and its logical base can also be used in the detection of brain electrical activity abnormalities other than epileptic disorders.

New perspectives in pharmaco-electroencephalography

Recent research emphasizes that majority of brain disorders and psychiatric problems are accompanied by disruption in the temporal structure of brain activity. From this perspective, disruption is viewed as a disorder of the metastable balance between large-scale integration and independent processing in the brain, in favor of either independent or hyper-ordered processing. This paper proposes that the future of psychopharmacology lies in its ability to design the psychotropic drugs which can restore the normal temporal structure and metastable structure of brain activity. Quantitative electroencephalography (QEEG) is one of the key complex technologies utilized in psychopharmacology for this purpose. However, conventional approaches for EEG analysis used in clinical practice are not suitable for studying temporal structure of brain activity. To overcome this limitation, and in order to reveal dynamic and temporal characteristics of brain activity, the advanced analysis of EEG micro-structure should be used.

The usefulness of quantitative EEG (QEEG) and neurotherapy in the assessment and treatment of post-concussion syndrome

Mild traumatic brain injury (TBI) is associated with damage to frontal, temporal and parietal lobes. Post-concussion syndrome has been used to describe a range of residual symptoms that persist 12 months or more after the injury, often despite a lack of evidence of brain abnormalities on MRI and CT scans. The core deficits of post-concussion syndrome are similar to those of ADHD and mood disorders, and sufferers often report memory, socialization problems and frequent headaches. While cognitive rehabilitation and psychological support are widely used, neither has been shown to be effective in redressing the core deficits of post-concussion syndrome. On the other hand, quantitative EEG has been shown to be highly sensitive (96%) in identifying post-concussion syndrome, and neurotherapy has been shown in a number of studies to be effective in significantly improving or redressing the symptoms of post-concussion syndrome, as well as improving similar symptoms in non-TBI patients.

The interplay of lorazepam-induced brain oscillations: microstructural electromagnetic study

OBJECTIVE

The effects on cortical rhythms of a single-dose (30 microg/kg) administration of the GABAA agonist lorazepam were examined in a randomized, double-blind, cross-over, placebo-controlled study with 8 healthy volunteers using simultaneous electroencephalography (EEG) and magnetoencephalography (MEG).

METHODS

The oscillations were assessed by means of adaptive classification of short-term spectral patterns.

RESULTS

Lorazepam (a) decreased the percentage of EEG/MEG segments with fast-theta, delta-alpha, fast-theta-alpha and alpha activity and increased percentage of EEG/MEG segments with delta, delta-slow-theta, delta-beta, slow-theta and polyrhythmic activity; (b) decreased diversity of EEG/MEG signals (in terms of spectral patterns) and increased the general instability of the signal; (c) increased stabilization periods of the spectral patterns (reduced brain information processing); (d) maintained larger maximum periods of temporal stabilization for delta, slow-theta, delta-slow-theta, delta-beta and polyrhythmic activity (in terms of spectral patterns); (e) did not increase power in the independent beta rhythm.

CONCLUSIONS

Lorazepam caused significant reorganization of the EEG/MEG microstructure. These results suggest also that adaptive classification analysis of single short-term spectral patterns may provide additional information to conventional spectral analyses.

Quantitative EEG findings of a temporal lobe abnormality not detected by magnetic resonance or SPECT imaging in a patient with dementia

The last three decades have seen significant advances in structural neuroimaging techniques such as computerized tomography and magnetic resonance imaging. These seem to have surpassed EEG as modalities for the identification of focal CNS lesions. Reported here is the case of a patient with a temporal lobe lesion not evident with magnetic resonance imaging or single photon emission computerized tomography but detected by EEG and positron emission tomography. EEG, particularly quantitative EEG, remains a valuable tool for the demonstration of the degree of dysfunctional changes associated with a cerebral lesion.

EEG and behavioral changes following neurofeedback treatment in learning disabled children

Neurofeedback (NFB) is an operant conditioning procedure, by which the subject learns to control his/her EEG activity. On one hand, Learning Disabled (LD) children have higher values of theta EEG absolute and relative power than normal children, and on the other hand, it has been shown that minimum alpha absolute power is necessary for adequate performance. Ten LD children were selected with higher than normal ratios of theta to alpha absolute power (theta/alpha). The Test Of Variables of Attention (TOVA) was applied. Children were divided into two groups in order to maintain similar IQ values, TOVA values, socioeconomical status, and gender for each group. In the experimental group, NFB was applied in the region with highest ratio, triggering a sound each time the ratio fell below a threshold value. Noncontingent reinforcement was given to the other group. Twenty half-hour sessions were applied, at a rate of 2 per week. At the end of the 20 sessions, TOVA, WISC and EEG were obtained. There was significant improvement in WISC performance in the experimental group that was not observed in the control group. EEG absolute power decreased in delta, theta, alpha and beta bands in the experimental group. Control children only showed a decrease in relative power in the delta band. All changes observed in the experimental group and not observed in the control group indicate better cognitive performance and the presence of greater EEG maturation in the experimental group, which suggests that changes were due not only to development but also to NFB treatment.

Quantitative spectral analysis of EEG in psychiatry revisited: drawing signs out of numbers in a clinical setting

OBJECTIVE

To evaluate the incidence, sensitivity and specificity of abnormal quantitative EEG (QEEG) measures in normal subjects and patients with mental disorders.

METHODS

Normalized QEEG measures were blindly assessed in 67 normal human beings and 340 psychiatric patients. QEEG results were correlated to subject condition or diagnosis and magnetic resonance imaging (MRI) findings.

RESULTS

QEEG was abnormal in 83% of patients, and 12% of normal subjects. The most frequent abnormality was a decrease in slow (delta and/or theta) bands, either alone, with beta increase, or with alpha decrease, followed by increase in beta band. No normal subject showed delta and/or theta decrease. Slow band decrease was more frequent in depression and mental disorders due to general medical condition, alcohol and drug dependence. However, no pattern was specific of any entity, and patients within the same diagnostic may present different patterns. Delta-theta decrease was correlated with cortical atrophy as seen in MRI. Beta increase was correlated with psychoactive medication. No association was found between any other QEEG pattern and MRI abnormalities, or medication.

CONCLUSIONS

Decrease in the delta and theta bands of the QEEG can be regarded as a specific sign of brain dysfunction, and is correlated with cortical atrophy. However, this sign, as other QEEG abnormal patterns, can be found in many different disorders and none of them can be considered as pathognomonic of any specific disorder.

SIGNIFICANCE

This work attempted to circumvent the alleged lack of Class I evidence of QEEG utility in the study of psychiatric patients by means of a prospective, blinded study, searching for specific signs of physiopathology in individual patients.

Structural (operational) synchrony of EEG alpha activity during an auditory memory task

Memory paradigms are often used in psycho-physiological experiments in order to understand the neural basis underlying cognitive processes. One of the fundamental problems encountered in memory research is how specific and complementary cortical structures interact with each other during episodic encoding and retrieval. A key aspect of the research described below was estimating the coupling of rapid transition processes (in terms of EEG description) which occur in separate cortical areas rather than estimating the routine phase-frequency synchrony in terms of correlation and coherency. It is assumed that these rapid transition processes in the EEG amplitude correspond to the "switching on/off" of brain elemental operations. By making a quantitative estimate of the EEG structural synchrony of alpha-band power between different EEG channels, it was shown that short-term memory has the emergent property of a multiregional neuronal network, and is not the product of strictly hierarchical processing based on convergence through association regions. Moreover, it was demonstrated that the dynamic temporal structure of alpha activity is strongly correlated to the dynamic structure of working memory.

P300 (Latency) Event-Related Potential: An Accurate Predictor of Memory Impairment

To determine if P300 latency changes precede and correlate with memory and mental status, patients (N=1506 aged 20–100 years) who received medical and psychiatric diagnoses (from 1997 to 2002), were assessed for P300 (N=1496), WMS-III (N=694), and MMSE (N=456). Patient and control groups included, a) normal WMS-III on all 4 subscales (N=36), b) normal WMS-III and MMSE (N=189) with subjective memory/mental status complaints, and c) medical patients with normal WMS-III and no memory complaints (N=205), and d) P300 control group without medical, psychiatric or memory problems for ROC.

Patients with impaired/borderline memory had a prolonged P300 latency (P<0.02) compared to age matched non-impaired controls; in patients with normal WMS-III/MMSE, with subjective mild memory/mental status impairment, P300 latency was prolonged compared to controls (P=0.0004). The P300 latency increased by 0.72ms per year (P=7.9×10−65) and voltage decreased by 0.03dV per year (P=6.7×10−10), and both parameters were linearly correlated with the age of the subjects.

Male subjects had an average voltage of 6.1dV and female 6.8dV(P=0.00009). Statistically, prolonged latency began at age range 41–50 (P=0.0002); reduced P300 voltage began at age range 51–60 (P=0.003). WMS-III memory decline for all measures began in females at age range 61–70 (P value at least=0.02) and for males at age range 61–80 (P=0.02). Prolonged P300 latency (P≤0.0001) and memory impairment (at least <0.02) were greater for females than males. MMSE memory decline, male and female, began at age range 81–90 (P value of at least 0.00007).

In our logistic regression model P300 latency was more predictive of WMS-III impairment than MMSE >24. In patients whose WMS-III score is impaired ≤69, or borderline ≤79 (P at least =0.004), a P300 latency more prolonged than the norm (≥300 + 30 + Age) identifies these patients, whereas a MMSE >24 failed. With the ROC curve, we confirmed that P300 latency could accurately identify borderline/impaired memory.

Quantitative electroencephalographic findings in beagles anaesthetized with propofol

The purpose of this study was to assess quantitative electroencephalography (q-EEG) in 10 healthy beagle dogs under propofol anaesthesia in order to determine objective guidelines for diagnostic electroencephalographic (EEG) recordings and interpretation. The basic pattern after preliminary visual examination of EEG recordings was characterized by spindles, k-complexes, vertex sharp transients, and positive occipital transients that were superimposed on the slow background activity. The results of the q-EEG were characterized by the prevalence of slow rhythms delta and theta, both in absolute and relative power spectrum analysis, while fast rhythms (alpha and beta) were poorly represented. The distribution of single frequency bands was widespread for delta, focal for frontal and central for theta, as well as for most alpha and beta patterns. The present study has shown that the use of quantitative EEG gives information on the frequency content of the bio-electrical activity and defines the distribution of the single frequency bands under a standardized anaesthetic protocol.

Quantitative EEG and the Frye and Daubert standards of admissibility

The 70-year-old Frye standards of "general acceptance" were replaced by the Supreme Court's 1993 Daubert criteria of the scientific method, which established the standards for admissibility of evidence in Federal Court. The four Daubert criteria were: 1- Hypothesis testing, 2- Estimates of error rates, 3- Peer reviewed publication and 4- General acceptance (Daubert v. Merrell Dow Pharmaceuticals, 61 U.S.LW 4805 (U.S. June 29, 1993)). The present paper starts with the Daubert four factors and then matches them, step by step, to the scientific peer reviewed literature of quantitative EEG (QEEG) in relation to different clinical evaluations. This process shows how the peer reviewed science of the Digital EEG and the Quantitative EEG (QEEG) meet all of the Daubert standards of scientific knowledge. Furthermore, the science and technical aspects of QEEG in measuring the effects of neurological and psychiatric dysfunction also match the recent Supreme Court standards of "technical" and "other specialized" knowledge (General Electric Co v. Joiner, 1997, Kumho Tire Company, Ltd. v. Carmichael, 1999). Finally, it is shown that QEEG scientific knowledge and QEEG "technical" and "other specialized" knowledge meet the trilogy standards of the Supreme Court rulings in support of QEEG's admissibility as a clinically valid method in the evaluation of the nature and extent of neurological and psychiatric disorders.

Brain electrical activity mapping of EEG for the diagnosis of (sub)clinical hepatic encephalopathy in chronic liver disease

We studied the role of brain electrical activity mapping (BEAM) in the assessment of neuropsychiatric disturbances in 48 cirrhotic patients without clinical evidence of hepatic encephalopathy (no HE, n = 19), with subclinical HE (grade 0, denoting pathological psychometric tests, n = 13) and mild-to-moderate HE (grade I, n = 6; grade II, n = 10). Results were compared with 23 healthy controls. BEAM variables quantified were: (i) the peak frequency (PF); (ii) the amplitude of PF; and (iii) the topographic localization of the maximum peak amplitude digitized for quantification by using a coordinate system. Mean amplitudes and their topographic localization in the following frequency-bands were analysed: delta (1.0-3.5 Hz), theta (4.0-7.5 Hz), alpha 1 (8.0-9.5 Hz), alpha 2 (10.0-11.5 Hz), beta 1 (12.0-15.5 Hz), beta 2 (16.0-19.5 Hz), and beta 3 (20.0-23.5 Hz). The PF was significantly slower in all HE patients than in healthy controls (8.5 +/- 2.0 Hz v. 10.1 +/- 1.0 Hz, P< 0.001). Even in no HE, the PF was significantly slower than in controls (8.6 +/- 1.5 Hz v. 10.1 +/- 1.0 Hz, P< 0.01). No relevant topographic differences of PF were observed. The mean amplitudes of the following bands differed significantly between controls and patients: theta (increased in HE, P< 0.05), alpha 2 (decreased in HE, P< 0.05), and beta 2 and beta 3 (increased in HE, (P < 0.05). In HE patients, the topographic localization of all beta bands showed a significant shift from parieto-occipital areas to central areas of the cortex. We conclude that BEAM is a sensitive tool for detecting neuropsychiatric disturbances in cirrhotics with no HE and with subclinical HE. The combination of PF in the theta band, increased mean amplitude in the beta 2 band, and the localization of the latter band in the frontocentral area of the cortex is an objective and sensitive tool for identifying neuropsychiatric disturbances in 85% of cirrhotic patients with no HE. Further studies are required to determine the clinical implications of these abnormal findings in the absence of overt clinical symptoms.

Detecting symmetric patterns in EEG data: a new method of analysis

Theoretical models of higher cognitive function predict that cortical activity will exhibit families of spatial-temporal patterns of activity whose individual members are related to each other by specific symmetry transformations. In the trion model, it is suggested that these inherent symmetries play a vital role in how we think and reason. We have developed a method of analysis (SYMMETRIC analysis), which detects families of patterns in EEG data, and characterizes the symmetry relationships between members of those pattern families. Using this analysis, significant symmetry families have been found in EEG and single unit spike train data. If symmetry is a crucial aspect of brain function, it is possible that different pathologies are associated with specific types of symmetry relationships in brain activity that could be detected in EEG data by a SYMMETRIC analysis.

Methylphenidate effects on global and complex measures of EEG

Methylphenidate (MPH) effects on global and complex measures of electroencephalography were examined in boys with attention-deficit-hyperactivity disorder between the ages of 9 and 11 years. Electroencephalogram (EEG) data were collected separately from the administration of a continuous performance task and were evaluated for changes in overall frequency, coherence, phase, and asymmetry and against a referential database. MPH did not produce a clear change in EEG frequency measures compared with the task condition, although it did induce regional changes in the EEG and produced an improvement in task performance. In comparison against the referential database, MPH appeared to lessen the impact of abnormalities in EEG coherence, EEG phase, and EEG asymmetry on performance measures.

[Guidelines for recording/analyzing quantitative EEG and evoked potentials. Part II: Clinical aspects]

Digital EEG (DEEG) and quantitative EEG (QEEG) are recently developed tools present in many clinical situations. Besides showing didactic and research utility, they may also have a clinical role. Although a considerable amount of scientific literature has been published related to QEEG, many controversies still subsist regarding its clinical utilization. Clinical applications are: 1. DEEG is already an established substitute for conventional EEG, representing a clear technical advance. 2. Certain QEEG techniques are an established addition to DEEG for: 2a) screening for epileptic spikes or seizures in long-term recordings; 2b) Operation room and intensive care unit EEG monitoring. 3. Certain QEEG techniques are considered possible useful additions to DEEG: 3a) topographic voltage and dipole analysis in epilepsy evaluations; 3b) frequency analysis in cerebrovascular disease and dementia, mostly when other tests have been inconclusive. 4. QEEG remains investigational for clinical use in postconcussion syndrome, learning disability, attention disorders, schizophrenia, depression, alcoholism and drug abuse. EEG brain mapping and other QEEG techniques should be clinically used only by physicians highly skilled in clinical EEG interpretation and as an adjunct to traditional EEG work.

Interictal quantitative EEG in epilepsy

The interictal EEG is often normal in epilepsy patients, particularly with partial seizures of extratemporal origin. Quantitative techniques of EEG analysis may increase the yield of diagnostic abnormality in such patients. Thirty patients with partial seizures of frontal or temporal origin had EEG recorded from left frontal (F7-C3), right frontal (F8-C4), left posterior (T5-O1), and right posterior (T6-O2) derivations. Four-second epochs were used to compute power in the delta (0.25-4.0 Hz), theta (4.25-8.0 Hz), alpha (8.25-13 Hz), and beta (13.25-30 Hz) bands. The ratio of high (8.25-30 Hz) to low (0.25-8 Hz) power on the left and the right was measured, as was the ratio between the left and the right hemisphere total power. The mean frequency deviation in the alpha band between the left and the right hemispheres was also measured, and spectral mobility was determined in the right and the left frontal regions. These values were also calculated in normal subjects and tension headache patients with normal EEGs. Seizure patients with abnormal interictal EEGs had decreased ratios of high to low power, greater asymmetry of total power and alpha frequency, and reduced spectral mobility on the side of their EEG foci. Epileptics with normal interictal EEGs had lower ratios of high to low power, greater alpha frequency asymmetry, and lower spectral mobility than did headache patients or normal controls. Power and frequency measurements, and determination of spectral measures such as mobility, can be done with commercially available digital EEG equipment. They may demonstrate otherwise obscure asymmetries in the interictal EEG and thereby aid in epilepsy diagnosis and classification.

Substance use disorder exacerbates brain electrophysiological abnormalities in a psychiatrically-ill population

OBJECTIVE

To assess by brain electrical activity mapping whether cocaine and alcohol abuse and dependence would exacerbate electro-physiological abnormalities in a psychiatrically-ill population.

DESIGN, SETTING, AND PARTICIPANTS

Utilizing a brain mapping system, we assessed EEG, Spectral Analysis (Quantitative EEG[QEEG]). Evoked Potentials (Auditory and Visual), and P300 (cognitive evoked potential), in a total of 111 probands divided into three groups: controls (N = 16), psychiatrically-ill without comorbid substance use disorder (N = 34), and psychiatrically-ill with comorbid substance use disorder (cocaine and alcohol abuse and dependence) (N = 61), at an outpatient neuropsychiatric clinic. With regard to demographic data, the group participating in this study did not differ significantly. A comparison was made among the groups to assist in differentiating the effects of substance use disorder compared to psychiatric disease on brain electrical activity.

MAIN OUTCOME MEASURES

An assessment of electrophysiological abnormalities and their brain location in psychiatric and substance use disorder patients was done with a brain electrical activity mapping test.

MAIN RESULTS

Among the non-substance use disorder, psychiatrically-ill (PI) and substance use disorder, psychiatrically-ill (PI/SD) groups, significantly different brain map abnormalities were observed relative to an assessed normal population MANOVA (P = .017). Moreover, with regard to Spectral Analysis, ANOVA was significant at a P = .038, and we found a weighted linear trend of increased abnormal total spectral analysis (P = .0113), whereby substance use was significantly worse than controls. Moreover among the PI and PI/SD groups, significantly greater total evoked potential (EP) brain trap abnormalities were observed when compared with a characterized normal population (P = .0023) with increasing abnormalities as a function of substance use disorder as measured by a weighted linear trend (P = .0022). In order to determine the site of the EPS abnormalities, we evaluated these abnormalities by location. In this regard, we found all temporal abnormalities (AVBITA, see Table 2) among the PI and PI/SD groups to be significantly greater relative to an assessed normal population (P = .0026). Furthermore, we observed a linear trend of increased temporal abnormalities with increasing substance use disorder (P < .0008). In terms of bitemporal abnormalities (AVBIT) among the PI and PI/SD groups, we also found significantly more bitemporal lobe abnormalities in the PI/SD group compared to our control population (P = .009). Additionally, a weighted linear trend of increased abnormal bitemporal lobe abnormalities was observed with increasing substance use disorder (P = .0022). In the frontal lobe similar findings were observed. With AVBIFA the ANOVA was P < .011, with a weighted linear trend of P < .005 and the PI/SD group were significantly more abnormal than PI or CS on a Duncan Range test. It is noteworthy that in a selected group of depressed (Major Depressive Disorder Recurrent, 296.3) patients, we found profound abnormalities in the various brain map parameters tested. MANOVA and Univariate ANOVA's revealed significantly greater abnormalities in the PI and PI/SD groups compared to assessed controls. A MANOVA for total brain abnormalities was significant at P = .043 and univariate ANOVA's for composite measurements of TSA (P = .017), EPS (P = .0002), AVBITA (P = .000015), and AVBIT (P < .00002) are also significant. With regard to EPS and AVBITA a weighted linear trend was observed where there were increasing abnormalities with increasing substance use disorder, P = .0001 and P = .000003, respectively. Most importantly we found that in addition to increased abnormalities with increasing substance use disorder the PI/SD group had significantly more abnormalities compared to the PI group with regard to both the TSA (P < .05) and AVBIT (P < .05) composite parameters as meas