Longitudinal investigation in children and adolescents with ADHD and healthy controls: A 2-year ERP study.

Cross-sectional group comparisons have shown altered neurocognitive and neurophysiological profiles in individuals with attention-deficit/hyperactivity disorder (ADHD). We report a two-year longitudinal observational study of ADHD children and adolescents (N = 239) regarding ADHD symptoms, behavioral metrics, and event-related potentials (ERP) and compared them to healthy controls (N = 91). The participants were assessed up to five times with a cued Go/NoGo task while ERPs were recorded. We fitted the trajectories of our variables of interest with univariate and bivariate latent growth curve models. At baseline, the ADHD group had increased reaction time variability, higher number of omission and commission errors, and attenuated CNV and P3d amplitudes compared to controls. The task performance in terms of behavioral metrics improved in both groups over two years; however, with differential patterns: the decrease in reaction time and omission errors were stronger in the control group, and the reduction of commission errors was more substantial in the ADHD group. The cueP3, CNV, and N2d amplitudes changed slightly over two years, with negligible differences between both groups. Furthermore, the parent-rated symptom burden in the ADHD group decreased by 22 % (DSM-5-based questionnaire). We did not identify any associations between the changes in symptoms and the changes in the behavioral or neurophysiological metrics. The lack of association between the changes in symptoms and the behavioral or ERP metrics supports the trait liability hypothesis, which claims that the neurocognitive deficits are independent of symptom alleviation. Furthermore, the change in symptom burden was substantial, questioning the stability of the reported ADHD symptoms.

Vigilance described by the time-on-task effect in EEG activity during a cued Go/NoGo task.

Vigilance refers to the ability to maintain attention and to remain alert to stimuli in prolonged and monotonous tasks. Vigilance decrement describes the decline in performance in the course of such sustained attention tasks. Time-related alterations in attention have been found to be associated with changes in EEG. We investigated these time-on-task effects on the basis of changes in the conventional EEG spectral bands with the aim of finding a compound measure of vigilance. 148 healthy adults performed a cued Go/NoGo task that lasted approximately 21 min. Behavioural performance was examined by comparing the number of errors in the first and last quarters of the task using paired t-test. EEG data were epoched per trial, and time-on-task effects were modelled by using multiple linear regression, with frequency spectra band power values as independent variables and trial number as the dependent variable. Behavioural performance decreased in terms of omission errors only. Performance of the models, expressed by predicted R-squared, was between 0.10 and 0.27, depending on the particular task condition. The time-on-task EEG spectral changes were characterized by broad changes in the alpha and frontal changes in the beta and gamma bands. We were able to identify a set of EEG spectral features that predict time-on-task. Our output is considered to be a measure of vigilance, reflecting the allocation of mental resources for the maintenance of attention.

Longitudinal Analysis of Self-Reported Symptoms, Behavioral Measures, and Event-Related Potential Components of a Cued Go/NoGo Task in Adults With Attention-Deficit/Hyperactivity Disorder and Controls.

This study characterizes a large sample of adults with attention-deficit/hyperactivity disorder (ADHD) and healthy controls regarding their task performance and neurophysiology; cross-sectionally and longitudinally. Self-reported symptoms, behavioral measures, and event-related potentials from a classical cued Go/NoGo task were used to outline the symptom burden, executive function deficits and neurophysiological features, and the associations between these domains. The study participants (N = 210 ADHD, N = 158 controls, age: 18-62 years) were assessed five (ADHD) or three (controls) times over two years. We describe cross-sectional and longitudinal group differences, and associations between symptom burden, and behavioral and event-related potential (ERP) components variables by latent growth curve models, including random slopes and intercepts. The ADHD group showed increased reaction time variability, increased commission and omission errors, and attenuated cueP3, CNV, N2d, and P3d amplitudes. We observed a decrease in self-reported symptoms in the ADHD group over the two years. The behavioral measures (reaction time variability, number of omission, and commission errors) did not change over time, whereas the cueP3, P3d, and N2d amplitude attenuated in both groups. There was no evidence for a robust association between symptom burden and behavioral or ERP measures. The changes in the ERP components with stable task performance, potentially indicate more efficient neuronal processing over the two years. Whether the lack of association between symptom burden and behavioral or ERP measures might be due to the low reliability of the ADHD assessment criteria, or the inappropriateness of the objective measures cannot be inferred.

Behavioral and Neurophysiological Markers of ADHD in Children, Adolescents, and Adults: A Large-Scale Clinical Study.

This study aimed to re-evaluate the possible differences between attention-deficit/hyperactivity disorder (ADHD) subjects and healthy controls in the context of a standard Go/NoGo task (visual continuous performance test [VCPT]), frequently used to measure executive functions. In contrast to many previous studies, our sample comprises children, adolescents, and adults. We analyzed data from 447 ADHD patients and 227 healthy controls. By applying multivariate linear regression analyses, we controlled the group differences between ADHD patients and controls for age and sex. As dependent variables we used behavioral (number of omission and commission errors, reaction time, and reaction time variability) and neurophysiological measures (event-related potentials [ERPs]). In summary, we successfully replicated the deviations of ADHD subjects from healthy controls. The differences are small to moderate when expressed as effect size measures (number of omission errors: d = 0.60, reaction time variability: d = 0.56, contingent negative variation (CNV) and P3 amplitudes: -0.35 < d < -0.47, ERP latencies: 0.21 < d < 0.29). Further analyses revealed no substantial differences between ADHD subtypes (combined, inattentive, and hyperactive/impulsive presentation), subgroups according to high- and low-symptomatic burden or methylphenidate intake for their daily routine. We successfully replicated known differences between ADHD subjects and controls for the behavioral and neurophysiological variables. However, the small-to-moderate effect sizes limit their utility as biomarkers in the diagnostic procedure. The incongruence of self-reported symptomatic burden and clinical diagnosis emphasizes the challenges of the present clinical diagnosis with low reliability, which partially accounts for the low degree of discrimination between ADHD subjects and controls.

EEG/ERP-based biomarker/neuroalgorithms in adults with ADHD: Development, reliability, and application in clinical practice.

Objectives: The electrophysiological characteristics of attention-deficit/hyperactivity disorder (ADHD) and recent machine-learning methods promise easy-to-use approaches that can complement existing diagnostic tools when sufficiently large samples are used. Neuroalgorithms are models of multidimensional brain networks by means of which ADHD patient data can be separated from healthy control data.Methods: Spontaneous electroencephalographic and event-related potential (ERP) data were collected three times over the course of 2 years from a multicentre sample of adults comprising 181 patients with ADHD and 147 healthy controls. Spectral power and ERP amplitude and latency measures were used as input data for a semi-automatic machine-learning framework.Results: ADHD patients and healthy controls could be classified with a sensitivity ranging from 75% to 83% and specificity values of 71% to 77%. In the analysis of the repeated measurements, sensitivity values of the selected logistic regression model remained high (72% and 76%), while specificity values slightly decreased over time (64% and 67%).Conclusions: Implementation of the system in clinical practice requires facilities to track affected networks, as well as expertise in neuropathophysiology. Therefore, the use of neuroalgorithms can enhance the diagnostic process by making it less subjective and more reliable and linking it to the underlying pathology.

Longitudinal study of a NoGo-P3 event-related potential component following mild traumatic brain injury in adults.

BACKGROUND: Event-related potentials have repeatedly revealed electrophysiological markers of cognitive dysfunction associated with Mild Traumatic Brain Injury (MTBI) and may represent a sensitive tool to guide cognitive rehabilitative interventions. We previously found patients with symptomatic MTBI characterized by smaller P300 (or P3) wave amplitudes in a NoGo-P3 subcomponent in the acute phase of the injury. The goal of this longitudinal study was to investigate whether this early NoGo-P3 subcomponent differs over time in symptomatic MTBI patients and healthy controls. METHODS: We included adults with a diagnosis of MTBI and individually matched healthy controls tested at 1 week, 3 months, and 1 year after the MTBI. Symptoms were assessed by the Rivermead Post-Concussion Symptoms Questionnaire. NoGo-P3 was collected by using a cued Go/NoGo task and the relevant subcomponent was extracted by independent component analysis. RESULTS: Among 53 adults with a diagnosis of MTBI and 53 controls, we included 35 with symptomatic MTBI and 35 matched healthy controls (18 females each group; mean age 34.06±13.15 and 34.26±12.98 years). Amplitudes for the early NoGo-P3 subcomponent were lower for symptomatic MTBI patients than controls (P<0.05) at 1 week post-injury. Furthermore, mixed ANOVA revealed a significant time by group interaction (P<0.05), so the effect of time differed for symptomatic MTBI patients and healthy controls. The amplitudes for MTBI patients normalized from 1 week to 3 months post-injury and were comparable to those of controls from 3 months to 1 year post-injury. However, amplitudes for 3 MTBI patients with particularly severe complaints 1 year post-injury did not normalize and were lower than those for the remaining MTBI sample (P<0.05). CONCLUSIONS: Selected event-related potentials can be used as a sensitive and objective tool to illustrate the cognitive consequences of and recovery after MTBI.

Facial emotion recognition deficits in children with and without attention deficit hyperactivity disorder: a behavioral and neurophysiological approach.

The current study examined the facial emotion recognition ability with a simultaneous assessment of behavioral and neurophysiological data in children with and without attention deficit hyperactivity disorder (ADHD) aged 7-17 years using a facial emotion matching task and event-related potential measurements (event-related potential components N170 and N250 at T5 and T6) in an emotional continuous performance task. Group differences and interaction effects of children's performance (both behavioral and neurophysiological) were evaluated between children with ADHD and children without ADHD as well as between younger and older children. No deficit in facial emotion recognition was found for children with ADHD compared with children without ADHD even with neurophysiological parameters. However, in terms of developmental differences, the younger children differentiated in their behavioral and neurophysiological performance from the older children. No interaction was detected between the experimental groups and the age groups, indicating that developmental progression in terms of emotional processes did not differ between children with and without ADHD. This study indicates that the facial emotion recognition is above all an age-dependent function with later processing of facial emotion expressions in younger compared with older children and suggests that a facial emotion recognition deficit is secondary in children with ADHD and might occur only with specific emotions or ADHD subtypes, but not in the whole ADHD population.

Test-retest reliability of ERP components: A short-term replication of a visual Go/NoGo task in ADHD subjects.

Event-related potentials (ERPs) have been widely used to investigate brain functioning in children with Attention Deficit Hyperactivity Disorder (ADHD) in both research and diagnostic settings. To ensure the efficiency of ERP techniques in ADHD diagnosis and in longitudinal observational studies, the test-retest reliability of the affected population must be validated. Thus, the present article assesses the short-term test-retest reliability of certain early and late ERPs (i.e., P1, N1, N2, P2, P3), as well as independent components (ICs) decomposed from the above mentioned ERPs (IC P3 Go, IC P3 NoGo early, IC P3 NoGo late) relevant to ADHD, through the Intraclass Correlation Coefficient (ICC). More specifically, we employ a cued visual Go/NoGo paradigm for recording ERPs from 22 children with ADHD (mean age 12.2), twice within 30 min. Amplitudes and latencies are calculated by the 'peak amplitude' method and by a variation of the fractional area. Results for amplitudes lie mostly within the 'good' and 'excellent' range for both measurement methods, while ICC for latencies is more variable ranging from 'poor' to 'excellent' results. Crucially, the ICs, which are associated with distinct functionally independent processes of the executive attentional system have shown a comparable test-retest reliability with the raw ERPs. Our results are consistent with other reliability studies of neurotypical population in the literature, and as such, consist initial evidence that ERPs could be reliable neurophysiological markers for the ADHD population.

Altered cognitive processes in the acute phase of mTBI: an analysis of independent components of event-related potentials.

Mild traumatic brain injuries (mTBI) generate acute disruptions of brain function and a subset of patients shows persisting cognitive, affective, and somatic symptoms. Deficits in the executive function domain are among the more frequent cognitive impairments reported by mTBI patients. By means of independent component analysis, event-related potential components from a visual cued go/nogo task, namely contingent negative variation (CNV) and NoGo-P3, were decomposed into distinct independent components that have been shown to be associated with the executive processes of energization, monitoring, and task setting. A group of symptomatic mTBI patients was compared with a group of controls matched for sex, age, and education. Patients showed reduced amplitudes in the late CNV as well as in the early NoGo-P3 subcomponents. Whereas the decreased CNVlate component indicates an impaired ability to generate representations of stimulus-response associations and to energize the maintenance of response patterns, the reduced P3NOGOearly component suggests a deficient ability to invest attentional effort in the initiation of response patterns in mTBI patients. Besides indicating the effects of mTBI on cognitive brain processing, the results may open up the possibility for assessing individual mTBI profiles and facilitate personalized rehabilitative measures.

Predicting the clinical outcome of stimulant medication in pediatric attention-deficit/hyperactivity disorder: data from quantitative electroencephalography, event-related potentials, and a go/no-go test.

BACKGROUND: We searched for predictors of the clinical outcome of stimulant medication in pediatric attention-deficit/hyperactivity disorder (ADHD), emphasizing variables from quantitative electroencephalography, event-related potentials (ERPs), and behavioral data from a visual go/no-go test. METHODS: Nineteen-channel electroencephalography (EEG) was recorded during the resting state in eyes-open and eyes-closed conditions and during performance of the cued go/no-go task in 98 medication-naïve ADHD patients aged 7-17 years and in 90 controls with the same age and sex distribution as the patients. For patients, the recording was followed by a systematic trial on stimulant medication lasting at least 4 weeks. Based on data from rating scales and interviews, two psychologists who were blind to the electrophysiological results independently rated the patients as responders (REs) (N=74) or non-responders (non-REs) (N=24). Using a logistic regression model, comparisons were made between REs and non-REs on the EEG spectra, ERPs (cue P3, contingent negative variation, and P3 no-go of the ERP waves and independent components [ICs] extracted from these waves), reaction time, reaction time variability, number of commission and omission errors, intelligence quotient, age, sex, ADHD subtype, and comorbidities. RESULTS: The two groups differed significantly on eight of the variables, with effect sizes (Cohen's d) ranging from 0.49 to 0.76. In the multivariate logistic regression analysis, only three of these variables were significantly associated with clinical outcome. The amplitude of the IC cue P3, which has a parietal-occipital distribution, was normal in REs but significantly smaller in non-REs, whereas the centrally distributed IC P3 no-go early was smaller in REs than in non-REs and controls. In addition, the REs had more power in the EEG theta band. A quartile-based index was calculated using these three variables. The group with the lowest scores comprised only 36% REs; response rates in the three other groups were 83%, 86%, and 89%. CONCLUSION: The clinical outcome of stimulant medication was best predicted by electrophysiological parameters. The brain dysfunctions of the REs appear to be primarily associated with prefrontal lobe hypoactivation. The non-REs were deviant from the controls in parietal-occipital functions.

Machine learning approach for classification of ADHD adults.

Machine learning techniques that combine multiple classifiers are introduced for classifying adult attention deficit hyperactivity disorder (ADHD) subtypes based on power spectra of EEG measurements. The analyzed sample includes 117 adults (67 ADHD, 50 controls). The measurements are taken for four different conditions: two resting conditions (eyes open and eyes closed) and two neuropsychological tasks (visual continuous performance test and emotional continuous performance test). We divide the sample into four data sets, one for each condition. Each data set is used for training of four different support vector machine classifiers, while the output of classifiers is combined using logical expression derived from the Karnaugh map. The results show that this approach improves the discrimination between ADHD and control groups, as well as between ADHD subtypes.

Group Independent Component Analysis (gICA) and Current Source Density (CSD) in the study of EEG in ADHD adults.

OBJECTIVE: To investigate the performance of the spectral analysis of resting EEG, Current Source Density (CSD) and group independent components (gIC) in diagnosing ADHD adults. METHODS: Power spectra of resting EEG, CSD and gIC (19 channels, linked ears reference, eyes open/closed) from 96 ADHD and 376 healthy adults were compared between eyes open and eyes closed conditions, and between groups of subjects. RESULTS: Pattern of differences in gIC and CSD spectral power between conditions was approximately similar, whereas it was more widely spatially distributed for EEG. Size effect (Cohen's d) of differences in gIC and CSD spectral power between groups of subjects was considerably greater than in the case of EEG. Significant reduction of gIC and CSD spectral power depending on conditions was found in ADHD patients. Reducing power in a wide frequency range in the fronto-central areas is a common phenomenon regardless of whether the eyes were open or closed. CONCLUSIONS: Spectral power of local EEG activity isolated by gICA or CSD in the fronto-central areas may be a suitable marker for discrimination of ADHD and healthy adults. SIGNIFICANCE: Spectral analysis of gIC and CSD provides better sensitivity to discriminate ADHD and healthy adults.

Discriminating between ADHD adults and controls using independent ERP components and a support vector machine: a validation study.

BACKGROUND: There are numerous event-related potential (ERP) studies in relation to attention-deficit hyperactivity disorder (ADHD), and a substantial number of ERP correlates of the disorder have been identified. However, most of the studies are limited to group differences in children. Independent component analysis (ICA) separates a set of mixed event-related potentials into a corresponding set of statistically independent source signals, which are likely to represent different functional processes. Using a support vector machine (SVM), a classification method originating from machine learning, this study aimed at investigating the use of such independent ERP components in differentiating adult ADHD patients from non-clinical controls by selecting a most informative feature set. A second aim was to validate the predictive power of the SVM classifier by means of an independent ADHD sample recruited at a different laboratory. METHODS: Two groups of age-matched adults (75 ADHD, 75 controls) performed a visual two stimulus go/no-go task. ERP responses were decomposed into independent components, and a selected set of independent ERP component features was used for SVM classification. RESULTS: Using a 10-fold cross-validation approach, classification accuracy was 91%. Predictive power of the SVM classifier was verified on the basis of the independent ADHD sample (17 ADHD patients), resulting in a classification accuracy of 94%. The latency and amplitude measures which in combination differentiated best between ADHD patients and non-clinical subjects primarily originated from independent components associated with inhibitory and other executive operations. CONCLUSIONS: This study shows that ERPs can substantially contribute to the diagnosis of ADHD when combined with up-to-date methods.

Classification of ADHD patients on the basis of independent ERP components using a machine learning system.

BACKGROUND: In the context of sensory and cognitive-processing deficits in ADHD patients, there is considerable evidence of altered event related potentials (ERP). Most of the studies, however, were done on ADHD children. Using the independent component analysis (ICA) method, ERPs can be decomposed into functionally different components. Using the classification method of support vector machine, this study investigated whether features of independent ERP components can be used for discrimination of ADHD adults from healthy subjects. METHODS: Two groups of age- and sex-matched adults (74 ADHD, 74 controls) performed a visual two stimulus GO/NOGO task. ERP responses were decomposed into independent components by means of ICA. A feature selection algorithm defined a set of independent component features which was entered into a support vector machine. RESULTS: The feature set consisted of five latency measures in specific time windows, which were collected from four different independent components. The independent components involved were a novelty component, a sensory related and two executive function related components. Using a 10-fold cross-validation approach, classification accuracy was 92%. CONCLUSIONS: This study was a first attempt to classify ADHD adults by means of support vector machine which indicates that classification by means of non-linear methods is feasible in the context of clinical groups. Further, independent ERP components have been shown to provide features that can be used for characterizing clinical populations.