Electroencephalographic and psychometric differences between boys with and without attention-deficit/Hyperactivity disorder (ADHD): a pilot study

A Systematic Review on Feature Extraction in Electroencephalography-Based Diagnostics and Therapy in Attention Deficit Hyperactivity Disorder

A systematic review on electroencephalographic (EEG)-based feature extraction strategies to diagnosis and therapy of attention deficit hyperactivity disorder (ADHD) in children is presented. The analysis is realized at an executive function level to improve the research of neurocorrelates of heterogeneous disorders such as ADHD. The Quality Assessment Tool for Quantitative Studies (QATQS) and field-weighted citation impact metric (Scopus) were used to assess the methodological rigor of the studies and their impact on the scientific community, respectively. One hundred and one articles, concerning the diagnostics and therapy of ADHD children aged from 8 to 14, were collected. Event-related potential components were mainly exploited for executive functions related to the cluster inhibition, whereas band power spectral density is the most considered EEG feature for executive functions related to the cluster working memory. This review identifies the most used (also by rigorous and relevant articles) EEG signal processing strategies for executive function assessment in ADHD.

Measuring Implicit Cognitive and Emotional Engagement to Better Understand Learners’ Performance in Problem Solving

Abstract. Novel data collection methods and analysis algorithms developed in the field of neuroergonomics have opened new possibilities for research in education. Psychophysiological data can characterize the cognitive and emotional dimensions of engagement. This paper aims to describe the application of this research methodology to synchronously measure emotional and cognitive engagement during learning tasks.

Electroencephalography and externalizing behavior: a meta-analysis

Electroencephalography (EEG) has been used to examine the possibility of dysfunctional brain activity in externalizing behavior, but findings across studies have been inconsistent. Furthermore, studies of attention-deficit/hyperactivity disorder (ADHD) versus other externalizing behaviors, such as disruptive behavior disorders or antisocial behavior, have developed parallel literatures. The purpose of the present study was to reconcile these two literatures. A meta-analysis of 62 studies of EEG power at rest in relationship to externalizing behaviors was performed. Results of the meta-analyses showed significantly higher delta (Hedges's g=0.25) and theta power (g=0.40) and lower beta power (g=-0.22) in externalizing participants compared to controls. Alpha (g=-0.26) and gamma power (g=-0.26) were marginally lower in externalizing samples. Results were not moderated by type of externalizing behavior. Overall, the results of the meta-analyses were consistent with the hypoarousal theory of externalizing behavior.

Combining electrodermal responses and cardiovascular measures for probing adaptive automation during simulated flight

Adaptive automation increases the operator's workload in case of hypovigilance and takes over more responsibility if workload becomes too high. Two consecutive studies were conducted to construct a biocybernetic adaptive system for a professional flight simulator, based on autonomic measures. Workload was varied through different stages of turbulences. In a first study with 18 participants, electrodermal responses of experimental subjects oscillated very close to the individual set point, demonstrating that workload level was adjusted as a result of adaptive control, which was not the case in yoked control subjects without adaptive automation. Combining electrodermal responses with heart rate variability in a second study with 48 participants further enhanced the adaptive power which was seen in even smaller set point deviations for the experimental compared to the yoked control group. We conclude that the level of arousal can be adjusted to avoid hypovigilance by combining autonomic measures in a closed loop.

Calibration of ADHD Assessments Across Studies: A Meta-Analysis Tool

When analyzed separately, data from small studies provide only limited information with limited clinical generalizability, due to small sample size, differing assessments, and limited scope. In this methodological paper we outline a theoretical framework for performing meta-analysis of data obtained from disparate studies using disparate tests, based on calibration of the data from such studies and tests into a unified probability scale. We apply this method to combine the data from five studies examining the diagnostic abilities of different assessments of Attention Deficit/Hyperactivity Disorder (ADHD), including behavioral rating scales and EEG assessments. The studies enrolled a total of 111 subjects, 56 ADHD and 55 controls. Each individual study had a small sample focused on a specific age/gender group, for example 8 boys ages 6-10, and generally had insufficient power to detect statistically significant differences. No gender, or age comparisons were possible within any single study. However, when calibrated and combined, the data resulted in a clear separation between ADHD versus non-ADHD groups in males below the age of 16 (p < 0.001), males above the age of 16, (p = 0.015), females below the age of 16, (p = 0.0014), and females above the age of 16, (p = 0.0022). We conclude that if data from various studies using various tests are made comparable, the resulting combined sample size and the increased diversity of the combined sample lead to increased significance of the statistical tests and allow for cross-sectional comparisons, which are not possible within each individual study.