Hyperactive behavior and EEG arousal reactions in children

Neurological and EEG findings were studied in 113 children diagnosed as adjustment reaction, behavior disorder, and minimal brain dysfunction (MBD). The MBD patients were subdivided into MBD behavior and MBD learning groups, thus yielding four patient groups in all. The presence of soft neurological signs and abnormal EEG examinations increased in stepwise fashion from the adjustment reaction group to the behavior disorder group, to the MBD behavior group, to the MBD learning group. The EEG records were rated on 16 variables, including amounts and frequencies of a variety of normal EEG features as well as abnormal features. The EEG ratings were then subject to a discriminant analysis. Three discriminant functions were found to be necessary to describe the relation of the four groups. The functions were identified as cortical maturity, cortical abnormality, and cortical reactivity. This implies that the groups do not just differ along one dimension, but along three dimensions. The discriminant program correctly classified 53% of the patients.

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“…This finding agrees with many previous papers reporting that posterior slowing is the most common abnormality in MBD patients (2,7,10,15).…”

Section: Discussionsupporting

confidence: 83%

“…0-Amount has been found to be an important EEG variable in previous studies of MBD patients. Grunewald-Zuberbier et al (7) found that a group of hyperactive children had a smaller amount of p than a group of nonhyperactive children. They argue that this indicates a lower state of EEG arousal in hyperactive children.…”

Section: Discussionmentioning

confidence: 99%

Discriminant Analysis of EEG in Children with Situational, Learning and Impulse Disorders

Nahas

Krynicki

1978

Neuropsychobiology

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“…Diagnosis not fully described 23. Grunewald-Zuberbier et al, 1975 Decreased beta activity *Diagnosis of hyperactivity by observation in standard situations 24. Murdoch, 1974 Excess slow wave most common abnormality *Diagnosis of minimal cerebral dysfunction conducted for studies reporting sensitivity and specificity of ADHD behavior rating scales.…”

Section: Sensitivity and Specificity For Adhd Versus Normal Controlsmentioning

confidence: 99%

A Meta-analysis of Quantitative EEG Power Associated With Attention-Deficit Hyperactivity Disorder

Snyder

Hall

2006

Journal of Clinical Neurophysiology

297

238

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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.

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“…During the 1970s several laboratories used a combination of visual inspection and quantitative EEG, and reported differences between the EEGs of hyperactive, learning-disabled (LD), and normal children [50][51][52][53]. Among the differences discovered were: an association of excessive delta and theta activity in ADHD subjects than in controls [54]; more relative power contributed by frequencies below 8 Hz in ADHD, primarily hyperactive children as compared to normal controls [55]; less power in the 10 Hz range for ADHD, primarily hyperactive children than controls [56]; and less beta and weaker stimulus-locked alpha attenuation in hyperactive children than those with non-hyperactive ADHD [57]. The authors do not specify, but it is assumed that this "nonhyperactive ADHD" subgroup is what we would term ADHD, primarily inattentive type.…”

Section: Eeg and Adhd Diagnosis: Pastmentioning

confidence: 99%

Electroencephalographic Profiles of Children with Symptoms of Attention Deficit Hyperactivity Disorder: A Review of the Literature

Penberthy¹,

Kalbfleisch²,

Quigg³

et al. 2006

CPR

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This article will review the use of electroencephalographic (EEG) data in children with Attention Deficit/Hyperactivity Disorder (ADHD) or symptoms indicative of ADHD, both in research directed at determining the pathophysiology of ADHD, as well as research attempting to use the EEG as a diagnostic tool. In addition, we briefly review concepts important in quantitative analysis of EEG data. Overall, although some studies show enhancement of certain frequency bands relative to others within groups of ADHD children compared to normal controls, to date neither traditional nor quantitative EEG has revealed pervasive or consistent patterns of EEG abnormalities with sufficient specificity or sensitivity to separate children with ADHD from normal subjects. An exciting and promising recent development in this area of research involves advanced quantitative EEG analysis that has revealed an index shown, in small preliminary studies, to clearly and reliably differentiate ADHD from non-ADHD males. The use of EEG as a diagnostic tool for ADHD warrants further study, including additional large studies to help determine and clarify the specificity and sensitivity of the multiple EEG measures in differentiating ADHD and its subtypes from non-ADHD and other medical and psychiatric disorders.

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Hyperactive behavior and EEG arousal reactions in children

Cited by 41 publications

References 20 publications

Discriminant Analysis of EEG in Children with Situational, Learning and Impulse Disorders

Discriminant Analysis of EEG in Children with Situational, Learning and Impulse Disorders

A Meta-analysis of Quantitative EEG Power Associated With Attention-Deficit Hyperactivity Disorder

Electroencephalographic Profiles of Children with Symptoms of Attention Deficit Hyperactivity Disorder: A Review of the Literature

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