EEG power spectra in normal and dyslexic children. I. Reliability during passive conditions

EEG correlates of developmental dyslexia: a systematic review

Dyslexia is one of the most studied learning disorders. Despite this, its biological basis and main causes are still not fully understood. Electroencephalography (EEG) could be a powerful tool in identifying the underlying mechanisms, but knowledge of the EEG correlates of developmental dyslexia (DD) remains elusive. We aimed to systematically review the evidence on EEG correlates of DD and establish their quality. In July 2021, we carried out an online search of the PubMed and Scopus databases to identify published articles on EEG correlates in children with dyslexia aged 6 to 12 years without comorbidities. We follow the PRISMA guidelines and assess the quality using the Appraisal Tool questionnaire. Our final analysis included 49 studies (14% high quality, 63% medium, 20% low, and 2% very low). Studies differed greatly in methodology, making a summary of their results challenging. However, some points came to light. Even at rest, children with dyslexia and children in the control group exhibited differences in several EEG measures, particularly in theta and alpha frequencies; these frequencies appear to be associated with learning performance. During reading-related tasks, the differences between dyslexic and control children seem more localized in the left temporoparietal sites. The EEG activity of children with dyslexia and children in the control group differed in many aspects, both at rest and during reading-related tasks. Our data are compatible with neuroimaging studies in the same diagnostic group and expand the literature by offering new insights into functional significance.

Stability, change, and reliable individual differences in electroencephalography measures: a lifespan perspective on progress and opportunities

Electroencephalographic (EEG) methods have great potential to serve both basic and clinical science approaches to understand individual differences in human neural function. Importantly, the psychometric properties of EEG data, such as internal consistency and test-retest reliability, constrain their ability to differentiate individuals successfully. Rapid and recent technological and computational advancements in EEG research make it timely to revisit the topic of psychometric reliability in the context of individual difference analyses. Moreover, pediatric and clinical samples provide some of the most salient and urgent opportunities to apply individual difference approaches, but the changes these populations experience over time also provide unique challenges from a psychometric perspective. Here we take a developmental neuroscience perspective to consider progress and new opportunities for parsing the reliability and stability of individual differences in EEG measurements across the lifespan. We first conceptually map the different profiles of measurement reliability expected for different types of individual difference analyses over the lifespan. Next, we summarize and evaluate the state of the field's empirical knowledge and need for testing measurement reliability, both internal consistency and test-retest reliability, across EEG measures of power, event-related potentials, nonlinearity, and functional connectivity across ages. Finally, we highlight how standardized pre-processing software for EEG denoising and empirical metrics of individual data quality may be used to further improve EEG-based individual differences research moving forward. We also include recommendations and resources throughout that individual researchers can implement to improve the utility and reproducibility of individual differences analyses with EEG across the lifespan.

Objective Assessments in Diagnoses and Treatment: A Proposed Change in Paradigm

For patients with psychiatric disorders, current diagnostic and treatment approaches are far from optimal. The clinical interview drives the standard approach-matching symptoms to diagnostic criteria-and results in standardized pharmacological and behavioral treatments, often, with inadequate outcome; but now, recent imaging advances can correlate behavioral assessments with brain function and measure them against normative databases to provide data critical for the reevaluation of patient diagnosis and treatment. This article addresses the data that support a redefinition of our current paradigm. We believe a neurobehavioral approach provides for more personalized treatment approaches unbound from classically defined diagnostic biases.

Reproducibility of power spectrum, functional connectivity and network construction in resting-state EEG

BACKGROUND

Characteristics from resting-state electroencephalography (rsEEG) provides relevant information about individual differences in cognitive tasks and personality traits. Due to its increasing application, it is crucial to know the reproducibility of several analysis measures of rsEEG.

NEW METHOD

A new brain network construction method was proposed based on simplified forward model (SFM). In addition, we aimed to carry out an extensive examination of the reproducibility of the power spectrum and functional connectivity at both the sensor-level and the source-level. We systematically proposed multiple new pipelines by integration source imaging, time-course extraction and network reconstruction.

RESULTS/COMPARISON WITH EXISTING METHOD(S)

Our results revealed that the reproducibility of eyes-closed was slightly higher than that of eyes-open, and the relative power was more repeatable than the absolute power, especially in high-frequency bands. The reproducibility of the sensor-level was higher than that of the source-level, both for power and connectivity. Remarkably, connectivity measures could be separated into two classes according to their reproducibility. Notably, the reproducibility of power envelope correlation (PEC) was generally the highest among those connectivity measures which are insensitive to volume conduction effect. For the whole-brain network construction, single dipole modeling was better than the dimensionality reduction methods, such as mean or principal component analysis (PCA) of multiple dipoles of a region.

CONCLUSIONS

In conclusion, our results described the reproducibility of rsEEG power spectrum, connectivity measures, and network constructions, which could be considered in assessing inter-individual differences in brain-behavior relationships, as well as automatic biometric applications.

Longitudinal EEG power in the first postnatal year differentiates autism outcomes

An aim of autism spectrum disorder (ASD) research is to identify early biomarkers that inform ASD pathophysiology and expedite detection. Brain oscillations captured in electroencephalography (EEG) are thought to be disrupted as core ASD pathophysiology. We leverage longitudinal EEG power measurements from 3 to 36 months of age in infants at low- and high-risk for ASD to test how and when power distinguishes ASD risk and diagnosis by age 3-years. Power trajectories across the first year, second year, or first three years postnatally were submitted to data-driven modeling to differentiate ASD outcomes. Power dynamics during the first postnatal year best differentiate ASD diagnoses. Delta and gamma frequency power trajectories consistently distinguish infants with ASD diagnoses from others. There is also a developmental shift across timescales towards including higher-frequency power to differentiate outcomes. These findings reveal the importance of developmental timing and trajectory in understanding pathophysiology and classifying ASD outcomes.

Brain oscillations may be disrupted in children with autism spectrum disorder. The authors performed a longitudinal study of electroencephalography recordings and found that EEG recordings from the first year after birth can distinguish healthy children from children with autism spectrum disorder.

Reliability of EEG Measures of Interaction: A Paradigm Shift Is Needed to Fight the Reproducibility Crisis

Measures of interaction (connectivity) of the EEG are at the forefront of current neuroscientific research. Unfortunately, test-retest reliability can be very low, depending on the measure and its estimation, the EEG-frequency of interest, the length of the signal, and the population under investigation. In addition, artifacts can hamper the continuity of the EEG signal, and in some clinical situations it is impractical to exclude artifacts. We aimed to examine factors that moderate test-retest reliability of measures of interaction. The study involved 40 patients with a range of neurological diseases and memory impairments (age median: 60; range 21–76; 40% female; 22 mild cognitive impairment, 5 subjective cognitive complaints, 13 temporal lobe epilepsy), and 20 healthy controls (age median: 61.5; range 23–74; 70% female). We calculated 14 measures of interaction based on the multivariate autoregressive model from two EEG-recordings separated by 2 weeks. We characterized test-retest reliability by correlating the measures between the two EEG-recordings for variations of data length, data discontinuity, artifact exclusion, model order, and frequency over all combinations of channels and all frequencies, individually for each subject, yielding a correlation coefficient for each participant. Excluding artifacts had strong effects on reliability of some measures, such as classical, real valued coherence (~0.1 before, ~0.9 after artifact exclusion). Full frequency directed transfer function was highly reliable and robust against artifacts. Variation of data length decreased reliability in relation to poor adjustment of model order and signal length. Variation of discontinuity had no effect, but reliabilities were different between model orders, frequency ranges, and patient groups depending on the measure. Pathology did not interact with variation of signal length or discontinuity. Our results emphasize the importance of documenting reliability, which may vary considerably between measures of interaction. We recommend careful selection of measures of interaction in accordance with the properties of the data. When only short data segments are available and when the signal length varies strongly across subjects after exclusion of artifacts, reliability becomes an issue. Finally, measures which show high reliability irrespective of the presence of artifacts could be extremely useful in clinical situations when exclusion of artifacts is impractical.

Reliability of EEG Interactions Differs between Measures and Is Specific for Neurological Diseases

Alterations of interaction (connectivity) of the EEG reflect pathological processes in patients with neurologic disorders. Nevertheless, it is questionable whether these patterns are reliable over time in different measures of interaction and whether this reliability of the measures is the same across different patient populations. In order to address this topic we examined 22 patients with mild cognitive impairment, five patients with subjective cognitive complaints, six patients with right-lateralized temporal lobe epilepsy, seven patients with left lateralized temporal lobe epilepsy, and 20 healthy controls. We calculated 14 measures of interaction from two EEG-recordings separated by 2 weeks. In order to characterize test-retest reliability, we correlated these measures for each group and compared the correlations between measures and between groups. We found that both measures of interaction as well as groups differed from each other in terms of reliability. The strongest correlation coefficients were found for spectrum, coherence, and full frequency directed transfer function (average rho > 0.9). In the delta (2–4 Hz) range, reliability was lower for mild cognitive impairment compared to healthy controls and left lateralized temporal lobe epilepsy. In the beta (13–30 Hz), gamma (31–80 Hz), and high gamma (81–125 Hz) frequency ranges we found decreased reliability in subjective cognitive complaints compared to mild cognitive impairment. In the gamma and high gamma range we found increased reliability in left lateralized temporal lobe epilepsy patients compared to healthy controls. Our results emphasize the importance of documenting reliability of measures of interaction, which may vary considerably between measures, but also between patient populations. We suggest that studies claiming clinical usefulness of measures of interaction should provide information on the reliability of the results. In addition, differences between patient groups in reliability of interactions in the EEG indicate the potential of reliability to serve as a new biomarker for pathological memory decline as well as for epilepsy. While the brain concert of information flow is generally variable, high reliability, and thus, low variability may reflect abnormal firing patterns.

On the invariance of EEG-based signatures of individuality with application in biometric identification

One of the main challenges in EEG-based biometric systems is to extract reliable signatures of individuality from recorded EEG data that are also invariant against time. In this paper, we investigate the invariability of features that are extracted based on the spatial distribution of the spectral power of EEG data corresponding to 2-second eyes-closed resting-state (ECRS) recording, in different scenarios. Eyes-closed resting-state EEG signals in 4 healthy adults are recorded in two different sessions with an interval of at least one week between sessions. The performance in terms of correct recognition rate (CRR) is examined when the training and testing datasets are chosen from the same recording session, and when the training and testing datasets are chosen from different sessions. It is shown that an CRR of 92% can be achieved based on the proposed features when the training and testing datasets are taken from different sessions. To reduce the number of recording channels, principal component analysis (PCA) is also employed to identify channels that carry the most discriminatory information across individuals. High CRR is obtained based on the data from channels mostly covering the occipital region. The results suggest that features based on the spatial distribution of the spectral power of the short-time (e.g. 2 seconds) ECRS recordings can have great potentials in EEG-based biometric identification systems.

Traumatic brain injury detection using electrophysiological methods

Measuring neuronal activity with electrophysiological methods may be useful in detecting neurological dysfunctions, such as mild traumatic brain injury (mTBI). This approach may be particularly valuable for rapid detection in at-risk populations including military service members and athletes. Electrophysiological methods, such as quantitative electroencephalography (qEEG) and recording event-related potentials (ERPs) may be promising; however, the field is nascent and significant controversy exists on the efficacy and accuracy of the approaches as diagnostic tools. For example, the specific measures derived from an electroencephalogram (EEG) that are most suitable as markers of dysfunction have not been clearly established. A study was conducted to summarize and evaluate the statistical rigor of evidence on the overall utility of qEEG as an mTBI detection tool. The analysis evaluated qEEG measures/parameters that may be most suitable as fieldable diagnostic tools, identified other types of EEG measures and analysis methods of promise, recommended specific measures and analysis methods for further development as mTBI detection tools, identified research gaps in the field, and recommended future research and development thrust areas. The qEEG study group formed the following conclusions: (1) Individual qEEG measures provide limited diagnostic utility for mTBI. However, many measures can be important features of qEEG discriminant functions, which do show significant promise as mTBI detection tools. (2) ERPs offer utility in mTBI detection. In fact, evidence indicates that ERPs can identify abnormalities in cases where EEGs alone are non-disclosing. (3) The standard mathematical procedures used in the characterization of mTBI EEGs should be expanded to incorporate newer methods of analysis including non-linear dynamical analysis, complexity measures, analysis of causal interactions, graph theory, and information dynamics. (4) Reports of high specificity in qEEG evaluations of TBI must be interpreted with care. High specificities have been reported in carefully constructed clinical studies in which healthy controls were compared against a carefully selected TBI population. The published literature indicates, however, that similar abnormalities in qEEG measures are observed in other neuropsychiatric disorders. While it may be possible to distinguish a clinical patient from a healthy control participant with this technology, these measures are unlikely to discriminate between, for example, major depressive disorder, bipolar disorder, or TBI. The specificities observed in these clinical studies may well be lost in real world clinical practice. (5) The absence of specificity does not preclude clinical utility. The possibility of use as a longitudinal measure of treatment response remains. However, efficacy as a longitudinal clinical measure does require acceptable test-retest reliability. To date, very few test-retest reliability studies have been published with qEEG data obtained from TBI patients or from healthy controls. This is a particular concern because high variability is a known characteristic of the injured central nervous system.

Regional differences in trait-like characteristics of the waking EEG in early adolescence

BACKGROUND

The human waking EEG spectrum shows high heritability and stability and, despite maturational cortical changes, high test-retest reliability in children and teens. These phenomena have also been shown to be region specific. We examined the stability of the morphology of the wake EEG spectrum in children aged 11 to 13 years recorded over weekly intervals and assessed whether the waking EEG spectrum in children may also be trait-like. Three minutes of eyes open and three minutes of eyes closed waking EEG was recorded in 22 healthy children once a week for three consecutive weeks. Eyes open and closed EEG power density spectra were calculated for two central (C3LM and C4LM) and two occipital (O1LM and O2LM) derivations. A hierarchical cluster analysis was performed to determine whether the morphology of the waking EEG spectrum between 1 and 20 Hz is trait-like. We also examined the stability of the alpha peak using an ANOVA.

RESULTS

The morphology of the EEG spectrum recorded from central derivations was highly stable and unique to an individual (correctly classified in 85% of participants), while the EEG recorded from occipital derivations, while stable, was much less unique across individuals (correctly classified in 42% of participants). Furthermore, our analysis revealed an increase in alpha peak height concurrent with a decline in the frequency of the alpha peak across weeks for occipital derivations. No changes in either measure were observed in the central derivations.

CONCLUSIONS

Our results indicate that across weekly recordings, power spectra at central derivations exhibit more "trait-like" characteristics than occipital derivations. These results may be relevant for future studies searching for links between phenotypes, such as psychiatric diagnoses, and the underlying genes (i.e., endophenotypes) by suggesting that such studies should make use of more anterior rather than posterior EEG derivations.

Childhood abuse and EEG source localization in crack cocaine dependence

Fourteen subjects with histories of sexual and/or physical abuse in childhood and 13 matched control subjects were selected from a consecutive series of clients in residential treatment for crack cocaine dependence. Standardized low-resolution electromagnetic brain tomography (sLORETA) was used to estimate the source generators of the EEG in a cortical mask with voxel z-scores referenced to normative data at frequency intervals of 039 Hz, with nonparametric permutation to correct by randomization for the number of comparisons and the intercorrelations and variance of distribution of voxel values. Subjects with histories of abuse in childhood had significantly greater EEG power than controls in the theta frequency range (3.51-7.41 Hz), with greatest differences in the 3.90-Hz band distributed mainly in the parahippocampal, fusiform, lingual, posterior cingulate, and insular gyri. The groups did not differ significantly with regard to delta (1.56-3.12 Hz), alpha (7.81-12.48 Hz), beta (12.87-19.89 Hz), and gamma (20.28-35.10 Hz) frequency power. In excess, theta EEG power, a bandwidth of transactions among hippocampus and amygdala and paralimbic and visual association cortex, may be a correlate of childhood exposure to abuse.

Neurofeedback outcomes in clients with Asperger's syndrome

This paper summarizes data from a review of neurofeedback (NFB) training with 150 clients with Asperger's Syndrome (AS) and 9 clients with Autistic Spectrum Disorder (ASD) seen over a 15 year period (1993-2008) in a clinical setting. The main objective was to investigate whether electroncephalographic (EEG) biofeedback, also called neurofeedback (NFB), made a significant difference in clients diagnosed with AS. An earlier paper (Thompson et al. 2009) reviews the symptoms of AS, highlights research findings and theories concerning this disorder, discusses QEEG patterns in AS (both single and 19-channel), and details a hypothesis, based on functional neuroanatomy, concerning how NFB, often paired with biofeedback (BFB), might produce a change in symptoms. A further aim of the current report is to provide practitioners with a detailed description of the method used to address some of the key symptoms of AS in order to encourage further research and clinical work to refine the use of NFB plus BFB in the treatment of AS. All charts were included for review where there was a diagnosis of AS or ASD and pre- and post-training testing results were available for one or more of the standardized tests used. Clients received 40-60 sessions of NFB, which was combined with training in metacognitive strategies and, for most older adolescent and adult clients, with BFB of respiration, electrodermal response, and, more recently, heart rate variability. For the majority of clients, feedback was contingent on decreasing slow wave activity (usually 3-7 Hz), decreasing beta spindling if it was present (usually between 23 and 35 Hz), and increasing fast wave activity termed sensorimotor rhythm (SMR) (12-15 or 13-15 Hz depending on assessment findings). The most common initial montage was referential placement at the vertex (CZ) for children and at FCz (midway between FZ and CZ) for adults, referenced to the right ear. Metacognitive strategies relevant to social understanding, spatial reasoning, reading comprehension, and math were taught when the feedback indicated that the client was relaxed, calm, and focused. Significant improvements were found on measures of attention (T.O.V.A. and IVA), core symptoms (Australian Scale for Asperger's Syndrome, Conners' Global Index, SNAP version of the DSM-IV criteria for ADHD, and the ADD-Q), achievement (Wide Range Achievement Test), and intelligence (Wechsler Intelligence Scales). The average gain for the Full Scale IQ score was 9 points. A decrease in relevant EEG ratios was also observed. The ratios measured were (4-8 Hz)(2)/(13-21 Hz)(2), (4-8 Hz)/(16-20 Hz), and (3-7 Hz)/(12-15 Hz). The positive outcomes of decreased symptoms of Asperger's and ADHD (including a decrease in difficulties with attention, anxiety, aprosodias, and social functioning) plus improved academic and intellectual functioning, provide preliminary support for the use of neurofeedback as a helpful component of effective intervention in people with AS.

Variability of model-free and model-based quantitative measures of EEG

Variable contributions of state and trait to the electroencephalographic (EEG) signal affect the stability over time of EEG measures, quite apart from other experimental uncertainties. The extent of intraindividual and interindividual variability is an important factor in determining the statistical, and hence possibly clinical significance of observed differences in the EEG. This study investigates the changes in classical quantitative EEG (qEEG) measures, as well as of parameters obtained by fitting frequency spectra to an existing continuum model of brain electrical activity. These parameters may have extra variability due to model selection and fitting. Besides estimating the levels of intraindividual and interindividual variability, we determined approximate time scales for change in qEEG measures and model parameters. This provides an estimate of the recording length needed to capture a given percentage of the total intraindividual variability. Also, if more precise time scales can be obtained in future, these may aid the characterization of physiological processes underlying various EEG measures. Heterogeneity of the subject group was constrained by testing only healthy males in a narrow age range (mean = 22.3 years, sd = 2.7). Eyes-closed EEGs of 32 subjects were recorded at weekly intervals over an approximately six-week period, of which 13 subjects were followed for a year. QEEG measures, computed from Cz spectra, were powers in five frequency bands, alpha peak frequency, and spectral entropy. Of these, theta, alpha, and beta band powers were most reproducible. Of the nine model parameters obtained by fitting model predictions to experiment, the most reproducible ones quantified the total power and the time delay between cortex and thalamus. About 95% of the maximum change in spectral parameters was reached within minutes of recording time, implying that repeat recordings are not necessary to capture the bulk of the variability in EEG spectra.

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.

Correlation of PET and qEEG in normal subjects

Positron emission tomography (PET) and quantitative electroencephalography (qEEG) were obtained in 15 normal male subjects with eyes closed at rest. Correlations between qEEG variables and regional metabolism were examined as an approach to investigating the metabolic and neuroanatomical basis of the generation of the EEG. Analogous to the neurometric approach to qEEG, a normative 2-fluoro-deoxyglucose voxel data base was developed for the PET image. The PET image was transformed to an idealized cylindrical set of coordinates to allow registration with the Talairach stereotactic atlas. PET regions of interest for the thalamus, the left and right temporal lobes, the medial frontal cortex and the dorsolateral prefrontal cortex were defined using Talairach coordinates and correlated to the QEEG. Salient findings included a negative correlation of thalamic metabolism to alpha power and a positive correlation of medial frontal cortical metabolism to delta EEG power. The significance of these findings is discussed with reference to the existing literature on the physiology of the generation of the EEG.

Time course and variability of power in different frequency bands of EEG during resting conditions

The aim of the present study was to evaluate the variability of EEG power spectrum data, considering the time course of the EEG spectrum in resting conditions, and the relationship between the spectral parameters and the length of the analyzed segments. Recordings were performed in 57 normal subjects, with a protocol consisting of regular cycles with open eyes (5 s) followed by closed eyes (55 s) repeated during 10 min. Towards the end of the recording there was a decrease in the alpha and beta power and an increase in the delta and theta power. The coefficient of variation (CV) for the power of 4 s epochs was in the range 0.49-0.67 (delta), 0.53-0.58 (theta), 0.58-0.76 (alpha), 0.37-0.49 (beta) and 0.09-0.12 for the alpha peak frequency. CV decreased with the increase of the sample size, being inversely proportional to the square root of the sample size. Increasing the recording length from 40 to 400 s increased CV by 36% (alpha), 41% (beta), 29% (delta) and 35% (theta), while the standard error of the mean decreased by 55-60%. It is concluded that the power estimates of the EEG activity are heavily dependent on the length of the analyzed segments, and the way they are selected. This observation is particularly relevant for clinical and drug studies where short recordings are often used, thus significantly biasing the estimation of the EEG parameters. The present data provide an estimate on the minimal length of EEG required for a given level of variability.

EEG Power and Coherence in Children with Educational Problems

SUMMARY

SUMMARY This study deals with the quantitative EEG (QEEG) of children attending schools for the mentally retarded and learning disabled. Questions are in which way do the EEGs of these children differ from normal development and whether deviations are restricted to a subgroup of children. The topographic distribution of EEG power is of particular interest. Based on a sample of n = 158 normal children, age-standardized values of absolute power (delta, theta, alpha 1, alpha 2, beta 1, beta 2 at F4, F3, C4, C3, CZ, PZ, O2, O1) and of coherence are computed for all children. The topographic distribution is assessed by analysis of variance (ANOVA) and by a principal component approach. The EEG of children with educational problems differs substantially from normal development in the slow bands and differs less in the fast bands. Deviations affect a subgroup of children, mainly children attending a school for the mentally retarded. Topographic distribution is an important factor in all bands. Coherence analysis leads to rather weak results that lack a clear interpretation. The QEEG is useful for understanding neurophysiological development in children with educational problems as a group more than individually. Parameters of topographic distribution provide strong additional information to power itself.

Sources of EEG activity in learning disabled children

The sources of different EEG frequencies were studied in 25 normal children and 46 learning disabled (not otherwise specified) children between 7 and 11 years old. The EEG sources were computed using Frequency-domain Variable Resolution Electromagnetic Tomography which produces a three dimensional picture of the currents at each EEG frequency. Significant differences between groups were observed. LD children showed more theta activity (3.5 to 7.02 Hz) in the frontal lobes and control children more alpha (9.75 to 12.87 Hz) in occipital areas. These results may support the maturational lag hypothesis, as the neurobiological cause of learning deficiencies not otherwise specified.

Long-term intra-individual variability of the background EEG in normals

OBJECTIVES

Forty-five healthy adult volunteers underwent repeated qEEG examinations with retest intervals 25-62 months in order to investigate the long-term intra-individual variability of several qEEG features such as, absolute and relative power, power asymmetry, coherence, mean and peak frequency and entropy. Prior to any computations all parameters were transformed to Z-scores on the basis of a normal database.

METHODS

Correlation coefficients were used to test the effect of the time on the test-retest differences. Correlation coefficients were also computed between baseline and retest values, as a measure of intra-individual stability, to make our results comparable to most literature data. By computing the standard deviations for test-retest differences, the intra-individual variabilities of the examined parameters were obtained in the unit of inter-individual variability of normal population. The same calculations were carried out with values obtained from the odd and even numbered epochs of the same EEG sections. This way, that portion of the intra-individual variability was estimated that might be introduced even by chance only when the epochs were selected randomly from the same section of EEG conforming to selection criteria.

RESULTS

As for our results, further increase of test-retest differences with time after 25 months might be so insignificant that it could not be demonstrated in our test material. The long-term intra-individual variability for most parameters, especially for total absolute power and alpha mean frequency, was less than the inter-individual variability in the normal population. The moment-to-moment variability was least in the case of the absolute power.

CONCLUSIONS

Estimates for intra-individual variability expressed this way in Z-scores might easily be used in the follow-up of patients even for a few years.

Patterns of waking EEG spectral power in chemically intolerant individuals during repeated chemical exposures

Previous studies indicate that low level chemical intolerance (CI) is a symptom of several different controversial conditions with neuropsychiatric features, e.g., chronic fatigue syndrome, fibromyalgia, multiple chemical sensitivity, and "Persian Gulf Syndrome". Prior studies suggest that limbic and/or mesolimbic sensitization may contribute to development of CI. The purpose of this report was to document the waking electroencephalographic (EEG) patterns of individuals with CI during chemical exposures presented over repeated sessions. Three groups of adult subjects who were recruited from the community participated in the study: self-reported CI who had made associated lifestyle changes due to their intolerance (CI/ LSC), self-reported CI who had not made such changes (CI), and normal controls without self-reported CI. Subjects underwent two sessions involving one-minute EEG recordings during exposures to low level chemical odors (a probe for limbic activation). The CI, but not the CI/ LSC, subjects had increased absolute delta power after the chemical exposures during the second, but not the first, session. The findings support the neural sensitization hypothesis for intolerance to low levels of environmental chemicals in vulnerable individuals. As in human studies of stimulant drug sensitization, those with the strongest past history with sensitizing agents may not show-term sensitization to low level exposures in the laboratory.

Different temporal stability and partial independence of EEG asymmetries from different locations: implications for laterality research

In order to investigate a possible regional specificity of activation asymmetries of different parts of the cortex and the stability of these asymmetries across time and conditions, EEG was recorded during rest and stimulation conditions in a large sample of right-handed university students (n = 60). Recordings were made in two sessions (interval between sessions 2-4 weeks). In the first session two rest periods were conducted (interval 30 min) and one under stimulation. In the second session EEG was again recorded at rest. Reliability analyses show that the long-term stability of orbitofrontal asymmetries is markedly lower than that of dorsolateral, temporal, and parietal scores. Intercorrelations of EEG asymmetries at different electrode positions suggest that anterior and posterior EEG asymmetries are largely independent measures of cortical laterality. Both this partial independence of activation asymmetries and the differences in temporal stability underscore the significance of the anterior-posterior dimension in laterality research and may be one reason for several contradictory observations in studies on brain laterality.

Dimensional complexity of the EEG in subcortical stroke--a case study

The conventional electrophysiological methods used for the analysis of the functional characteristics of the nervous system are not able to grasp its non-linear and random features. Of the methods based on the application of chaos-theory the correlation dimension analysis can be used to quantify the complexity of the analyzed signal, such as the electroencephalogram (EEG). The new version (point-correlation dimension, PD2) was used in this study, which is more accurate than the other, currently used algorithms. The purpose of the present investigation was to compare the sensitivity of the methods based on chaos-theory with the traditional electrophysiological ones in a case when no apparent abnormality was present as judged on the basis of this latter methodology. The PD2 was calculated from the EEG recorded in 13 healthy control subjects and in a patient who suffered a small subcortical stroke 2 years prior to the investigation and who was free of neurological symptoms at the time of recording. Compared to that seen in the control group, in the Z-score maps of the scalp distribution of the PD2, a marked asymmetry was seen and the absolute PD2 values showed a low-dimensional area in the parietal region, ipsilateral to the stroke. A relative decrease of the gamma band was found in the frequency power spectra in the same area. It is suggested that the additional information extracted from the EEG by non-linear analysis may increase the sensitivity of electrophysiological methods for detecting brain pathology.

Growth spurts in brain maturation during middle childhood as indexed by EEG power spectra

Developmental changes in background EEG power spectra were examined in 5-12-year-old children. The results confirmed older and more recent studies that reported continuous maturation and more sudden growth spurts in power spectral amplitude. EEG power in the Delta and Theta frequency bands decreased gradually with age, while power in the Alpha and Beta bands changed very little. Changes in spectral power were relatively increased between 6 and 7 years and between 9, 10 and 11 years. Some methodological problems concerning the assessment of cross-sectional age changes in EEG power spectra were addressed. Peak frequency increased with age; between 5 and 12 years the peak in the power spectrum shifted from fast Theta via slow Alpha to fast Alpha. Transformation of absolute power into relative power produced a high degree of interdependency between the broad bands. This interdependency affected the change with age of relative Alpha. Absolute power Alpha only changed in the eldest children, but because of a substantial decrease in Delta and Theta with increasing age, the proportion of Alpha relative to the other three bands increased. Hence, relative Alpha provided a good indication of the general maturational trend.

The reliability of event-related desynchronisation: a generalisability study analysis

The aim of this study was to examine the spatio-temporal reliability of EEG power during the baseline period of an event-related desynchronisation (ERD) experiment. The data were analysed using ideas from generalisability theory. The largest sources of variance were found to be associated with differences between subjects (subject main effect), and to idiosyncratic topographical distributions (subject x electrode interaction). The resulting spatio-temporal reliabilities exceeded 0.7, except in theta and the absolute power values were relatively stable. Overall, this study gives further support for the reliability of quantitative EEG measures in general and for the method of ERD in particular.

A guide for applying principal-components analysis and confirmatory factor analysis to quantitative electroencephalogram data

Principal-components analysis (PCA) has been used in quantitative electroencephalogram (qEEG) research to statistically reduce the dimensionality of the original qEEG measures to a smaller set of theoretically meaningful component variables. However, PCAs involving qEEG have frequently been performed with small sample sizes, producing solutions that are highly unstable. Moreover, solutions have not been independently confirmed using an independent sample and the more rigorous confirmatory factor analysis (CFA) procedure. This paper was intended to illustrate, by way of example, the process of applying PCA and CFA to qEEG data. Explicit decision rules pertaining to the application of PCA and CFA to qEEG are discussed. In the first of two experiments, PCAs were performed on qEEG measures collected from 102 healthy individuals as they performed an auditory continuous performance task. Component solutions were then validated in an independent sample of 106 healthy individuals using the CFA procedure. The results of this experiment confirmed the validity of an oblique, seven component solution. Measures of internal consistency and test-retest reliability for the seven component solution were high. These results support the use of qEEG data as a stable and valid measure of neurophysiological functioning. As measures of these neurophysiological processes are easily derived, they may prove useful in discriminating between and among clinical (neurological) and control populations. Future research directions are highlighted.

Effects of alcohol, at two times of day, on EEG-derived indices of physiological arousal

Effects of alcohol consumption (0.8 ml/kg) on sleep propensity, spectral characteristics of the EEG and self-rated activation in 16 young male subjects, were investigated during sessions at each of two times of day (08.00 and 16.00). Within-session, time-related changes in the pattern of stage-1 sleep occurrence, and of spectral power in different EEG bands indicated that, irrespective of time of day, physiological arousal increased as estimated blood alcohol concentration (BAC) was rising, and decreased as BAC was falling. Subjective activation was reduced by alcohol during both phases of the BAC curve. A pattern of reduced stage-1 sleep occurrence, higher absolute high alpha power and higher ratings of activation suggested that, irrespective of alcohol condition, physiological and subjective arousal was higher during sessions starting at 16.00 than during those starting at 08.00. There were no significant interactions between alcohol and time of day in respect of any dependent variable. However, the degree to which effects reflecting circadian variation may have been masked by effects of limited sleep restriction prior to morning sessions remains unclear. Subjects reported having slept on only 23.5% of occasions when sleep was scored. Comparison of patterns of statistically significant changes in absolute and relative power in different bands indicated that the two indices do not provide exactly equivalent information about changes in the EEG.

Evaluation of the effectiveness of EEG neurofeedback training for ADHD in a clinical setting as measured by changes in T.O.V.A. scores, behavioral ratings, and WISC-R performance

A study with three component parts was performed to assess the effectiveness of neurofeedback treatment for Attention Deficit/Hyperactivity Disorder (ADHD). The subject pool consisted of 23 children and adolescents ranging in age from 8 to 19 years with a mean of 11.4 years who participated in a 2- to 3-month summer program of intensive neurofeedback training. Feedback was contingent on the production of 16-20 hertz (beta) activity in the absence of 4-8 hertz (theta) activity. Posttraining changes in EEG activity, T.O.V.A. performance, (ADDES) behavior ratings, and WISC-R performance were assessed. Part I indicated that subjects who successfully decreased theta activity showed significant improvement in T.O.V.A. performance; Part II revealed significant improvement in parent ratings following neurofeedback training; and Part III indicated significant increases in WISC-R scores following neurofeedback training. This study is significant in that it examines the effects of neurofeedback training on both objective and subjective measures under relatively controlled conditions. Our findings corroborate and extend previous research, indicating that neurofeedback training can be an appropriate and efficacious treatment for children with ADHD.

The topography of muscle activity in quantitative EEG

Ten normal preadolescent subjects were studied on three occasions with quantitative EEG topography: two sessions recorded EEG that was free of artifact, but during the third the subjects were instructed to clench their teeth and tighten their faces to produce muscle artifact. The sessions were then compared for stability of various frequencies at standard scalp electrode sites. The posterior electrodes were stable among sessions for frequencies up to 24 Hz; the anterior electrodes were less stable, and above 24 Hz there were no stable electrode sites. Muscle artifact contaminates anterior electrode sites more than posterior sites, making the posterior scalp electrodes superior for studying beta activity in quantitative EEG. Frequencies above 24 Hz are contaminated at all sites and therefore cannot be assessed reliably in the presence of muscle artifact.

Visual information processing and cerebral activation in dyslexic boys: Quantitative EEG analysis during discrimination reading tasks

The hypothesis that in developmental dyslexia the integration of visually presented information and language processing is dysfunctional is tested. Results of processing visually presented letter strings during EEG recordings are presented. The task difficulty of the letter strings was standardised individually and automatically by a computer program. EEG was recorded during rest conditions and different levels of reading performance. 30 developmental dyslexic boys who met the Denckla criteria of "dyslexia pure" and 28 matched control subjects were investigated. The main replicated results were: (1) There was a delay in dyslexic children in processing visually presented letter information, (2) there was no deficit in sustained attention in developmental dyslexics, (3) increasing cognitive activation and reading performance resulted in a faster attenuation of relative alpha power in dyslexics compared to controls, and (4) the dyslexic group did not reveal characteristic focal EEG features when task difficulty was standardised individually.

Test-retest reliability in EEG frequency analysis

This study was performed to gain a better understanding of EEG frequency analysis test-retest reliability in normal healthy adults, and to evaluate factors which could influence the measured inter-record differences. Nineteen subjects underwent serial EEG recordings at 5 min and 12-16 week intervals. Records were visually edited using a standardized protocol, and FFT frequency analysis performed on segments of 60, 40, or 20 sec total length. Correlation coefficients for broad band features averaged 0.92 over the 5 min retest interval and 0.84 over the 12-16 week interval. There was essentially no difference between correlation coefficients of absolute and relative power features. Coefficients based on 60 sec records were marginally higher than those of 40 or 20 sec records. On the other hand, test-retest percent differences were typically lower for relative as opposed to absolute power features, and 60 sec records showed consistently lower percent differences than did 40 or particularly 20 sec records. Peak alpha frequency and mean frequency were the most stable EEG features at either interval. Montage had significant effects on test-retest differences at the 12-16 week interval. A significant association between intra-record and inter-record variability could not be demonstrated.

Reliability of topographic quantitative EEG amplitude in healthy late-middle-aged and elderly subjects

Reliabilities of quantitative measures of absolute and relative EEG amplitudes were assessed in healthy older adults under the eyes closed (n = 46) and eyes opened (n = 45) conditions. For the theta, alpha, beta 1, and beta 2 bands, reliabilities of 28 scalp derivations were stable over the 4.5 month test interval. Reliabilities of delta were lower. When appropriate transformations were applied, the reliabilities of absolute EEG amplitude measures tended to exceed those of relative measures. There were not, however, striking differences in reliabilities under the eyes closed, as compared to eyes opened condition. We concluded that when coupled with the criterion of interpretability, the generally higher reliabilities of absolute, as opposed to relative, amplitude measures render them preferable in clinical research.

EEG amplitudes in healthy, late-middle-aged and elderly adults: normality of the distributions and correlations with age

The interindividual distributions of EEG amplitudes were evaluated in 60 healthy subjects, aged 56-76. Skew and kurtosis were used to assess the normality of the amplitude distributions in 5 frequency bands (delta, theta, alpha and 2 beta ranges) and 28 scalp derivations while the subjects were awake and rested with their eyes closed and opened. Most of the interindividual EEG amplitude distributions were not normally distributed. Two transformations were applied to the EEG amplitudes: the square root and the natural logarithm. Evaluation of skew and kurtosis indicated that the natural logarithmic transformation was more effective than the square root in reducing the positive skew and leptokurtosis that characterized the untransformed interindividual EEG amplitude distributions. For all frequency bands except theta, the log transformation rendered the distributions approximately normal in form. Correlations between log transformed EEG amplitudes and age were not statistically significant. These findings are discussed in the context of previous research, aging, and methodological features.

Quantitative, waking EEG research on depression

Research published in the past decade that used quantitative indices to evaluate the waking EEG characteristics of depressed patients is reviewed. Methodological problems that make results of different research laboratories difficult to compare include diagnostic heterogeneity of depressed groups, lack of inclusion of control subjects, and differences in the EEG techniques. Despite interpretive problems that arise from such substantial variation, consistencies nevertheless emerge. Unmedicated, actively depressed patients appear to exhibit elevated EEG alpha and beta compared to control subjects. Delta and theta distinguished depressed patients from controls in some single studies, but variation in age, specific diagnostic depression categories, and EEG acquisition and analysis techniques rendered these results less definitive. Quantitative EEG differences that may distinguish depressed subject samples from those with other psychiatric disorders are considered. Factors that limit comparability of the findings are discussed in conjunction with strategies that deserve systematic study in future research.

Neurophysiological heterogeneity and the definition of dyslexia: preliminary evidence for plasticity

Developments in the field of quantified electroencephalography have enhanced visualization of brain function in the learning disabilities. Optimal utilization of these techniques requires that populations under study be unambiguously defined. Evidence from the literature demonstrates that brain electrical activity of children with reading disability is more extensive and differs from that seen in children with "dyslexia-pure". Preliminary data are presented demonstrating that electrophysiological change seen in children with dyslexia-plus (dyslexia and attentional deficit disorder) could not be predicted by knowledge of electrophysiologic change in children with dyslexia-pure alone and attentional deficit disorder alone. Data from our laboratory are summarized to show that within dyslexia-pure the anomic, dysphonemic and global Denckla subtypes differ electrophysiologically from one another. Of particular interest is the demonstration that regions of electrophysiological difference among these subtypes may reflect compensatory mechanisms rather than pathological change. Finally, a case study is presented demonstrating advantageous effects of remediation upon brain electrical function. As both spontaneous and environmentally induced change in brain function can be documented, developmental dyslexia in its broadest terms appears to represent a more dynamic or plastic process than previously appreciated.

Event-related potentials in children with specific visual cognitive disability

Event-related potentials (ERPs) elicited by novel and well memorized non-verbal visual patterns were recorded over the right and left hemispheres from ten children with Specific Visual Cognitive Disability (SVCD) and ten matched Control subjects (C). ERPs of SVCD children were generally longer in latency (particularly N2) and decreased in amplitude (particularly P3) relative to the ERPs of Cs. No hemisphere differences were observed in the SVCD group, while the latency of N2 in the C group tended to be slightly shorter and the amplitude of P3 was significantly larger over the right than over the left hemisphere. The results are discussed in terms of deficits in visual learning and visual pattern analysis. The different hemispheric pattern in SVCD children as compared to Cs is suggested to be a symptom secondary to basic visual cognitive deficits.

Short-term variability in EEG frequency analysis

Knowledge of short-term EEG variability in computerized analysis is important before interpreting spectral EEGs or assessing changes that may be due to inherent variability and not necessarily related to a task (e.g., listening to a story), therapy or changes in underlying disease. Eighty to 120 sec of 14-channel, edited, bipolar EEG were recorded in normal subjects and analyzed using an FFT. Absolute and relative power in 5 standard frequency bands, and median and peak power frequencies were obtained for each 4 sec epoch, and the mean and standard deviation calculated for each parameter. The average variation of the mean power, absolute and relative, in the frequency bands was less than 10% although some parameters varied by up to 50% in an individual subject. Median and peak power had the least variability, about 3%. Changes in total power correlated positively with relative alpha power, but negatively or not at all with the other relative power measures. This suggests that interpretation of relative measures of delta, theta and beta in individual spectra may be dependent on total power or absolute alpha power. In addition, mathematical transformations were necessary to normalize the epoch data, suggesting that the mean and standard deviation of data from a series of epochs may not have maximal value unless a transformation is used. These results also indicate that caution is needed in interpreting changes in EEG frequency analysis data that are of the same magnitude as spontaneous EEG variability.

Neurometrics: computer-assisted differential diagnosis of brain dysfunctions

Normative developmental equations provide reliable descriptors of brain electrical activity in people 6 to 90 years old. Healthy persons display only chance deviations beyond predicted ranges. Patients with neurological impairment, subtle cognitive dysfunctions, or psychiatric disorders (including dementia and primary depression) show a high incidence of abnormal values. The magnitude of the deviations increases with clinical severity. Different disorders are characterized by distinctive profiles of abnormal values of brain electrical features. Computerized differential classification of some of these disorders can be achieved with high accuracy. Such classification, providing objective corroboration of brain dysfunctions, may be a useful adjunct to psychiatric diagnosis, which relies primarily on subjective clinical impressions. These methods may provide independent criteria for diagnostic validity, evaluations of treatment efficacy, and more individualized therapy.

Reading comprehension performance and laterality: evidence for concurrent validity of dichotic, dichhaptic and EEG laterality measures

EEGs were recorded while 55 boys read and answered questions about passages. Concurrent validity between parietal alpha ratios obtained from these recordings and dichotic/dichhaptic scores supports their utility as measures of lateral processing. The evidence was particularly strong between right hand advantage for dichhaptically presented sequential patterns and left hemispheric activity while answering. Results also indicate that coefficients for dichotically presented digits and alpha ratios during silent reading are indices of receptive laterality and measure the deployment of lateral structures rather than degree of structural laterality. This supports a dynamic rather than static model of lateral processing during receptive language.

Narrative speech deficits in dyslexics

Narrative speech of 31 dyslexics and 33 good readers was studied. Subjects were 10- to 12-year-old right-handed boys of normal intelligence, and with normal neurological status, vision, and hearing. The dyslexics used shorter communication units (independent clauses with all their modifiers), and a higher percentage of their words were noncommunications (words which are extraneous to the speaker's intended meaning). Rate of speech was the same in both groups. These findings were replicated in an independent second cohort of 21 dyslexics and 21 controls, aged 9 to 13. Our findings support theories of a general language deficit in dyslexia, and demonstrate the involvement of the previously unexamined area of narrative speech.

EEG spectra in dyslexic and control boys during resting conditions

We studied the resting eyes open and eyes closed EEG in carefully screened samples of 9-13-year-old dyslexic and control boys within a 2-cohort cross-validation design with repeat testing 1-3 years later. We found: no difference between groups in delta or theta activity in either cohort or in repeat testing 1-3 years later; in the dyslexics, decreased beta (19-24 c/sec) activity at bilateral central, parietal and mid-temporal leads referenced to vertex; inconsistent group differences in the alpha band: the first cohort dyslexics had lower alpha power than did the controls, but there was no group difference in the second cohort; and significant relative delta differences between groups in the first cohort, which were shown to be a statistical artifact of the use of relative power. We conclude that: dyslexia per se is not associated with increased absolute power in the delta and theta bands; lower power in the high beta band is reliably found in these samples of dyslexics without other disorders; and alpha power levels are not consistently lower in the dyslexic group.

EEG spectra in 9-13-year-old boys are stable over 1-3 years

Good reliability was found in EEG spectra recorded during resting conditions in two studies 1-3 years apart in groups of adolescent dyslexic and control boys who were well screened for neurological, sensory and emotional disabilities. The studies used different equipment and analysis (FFT in study 1 vs. iterative digital bandpass filters in study 2). The central leads (C3 and C4) referenced to vertex were recorded in both studies. Pearson correlation coefficients were computed as reliability estimates for each spectral band separately for each group, for absolute and relative power and for eyes open and eyes closed recording conditions. For both groups and for all conditions, the absolute power reliabilities were above 0.71 for all bands except delta for which they were above 0.54. Reliabilities were more variable for relative power measures.

Temporal stability of multichannel, multimodal ERP recordings

Personnel assessment applications of event related brain potentials (ERP) require temporal stability. Visual, auditory and bimodal ERP records were obtained about two hours apart for a group of young adult males. Similar records were obtained from a group of older adults about two months apart. No ERP amplitude or temporal stability differences were found between the two groups. Age was positively correlated with visual stability measures and negatively correlated with auditory stability measures. No correlation of age with bimodal stability measures was found. Large individual subject differences were found for the ERP analog waveform and temporal stability. The ERPs were highly stable within subjects from session to session, whether recorded hours or months apart. Greatest stability was obtained for bimodal presentation, less for visual and least for the auditory records. Differences in patterns of waveform stability were found for site and modality conditions across individuals.

How to select epochs of the EEG at rest for quantitative analysis

Before performing a quantitative analysis of the EEG at rest, it has to be specified how many seconds are to be used later on, and a criterion has to be set down according to which data are selected for further analysis. In this paper it is investigated which duration is appropriate for an analysis of background, non-transient activity. Furthermore, different criteria for automatically selecting such epochs for quantitative analysis are compared with respect to broad-band parameters of a sample of 42 children. A length of 20 sec turned out to be sufficient, since using 40 sec or 60 sec did not improve the statistical variability. Moreover, a criterion based on minimizing EOG power from 1.5 to 7.5 Hz was mildly superior to other criteria considered. The particular choice of epoch was, however, less crucial than anticipated.

Regional brain activity in dyslexic and control children during reading tasks: visual probe event-related potentials

Event-related potentials (ERPs) elicited by task-irrelevant visual stimuli were recorded from 34 control and 32 dyslexic 10- to 12-year-old boys while they performed silent and oral reading at two levels of difficulty. All subjects were extensively screened for neurological problems, IQ, and sensory acuity. Specific features of the ERPs were affected in amplitude and latency by the experimental variables: group membership, oral vs. silent reading, difficulty level, and recording site (within and between hemispheres). A specific effect of difficulty on the central and parietal ERP was seen in the dyslexics but not the controls. Different patterns of asymmetry were found for the two groups in silent vs. oral reading at midtemporal placements. A marked asymmetry (R greater than L) was found at the midtemporal region for both groups.