A novel quantitative electroencephalography subtype with high alpha power in ADHD: ADHD or misdiagnosed ADHD?

Identification of Parkinson's Disease Subtypes from Resting-State Electroencephalography

BACKGROUND

Parkinson's disease (PD) patients present with a heterogeneous clinical phenotype, including motor, cognitive, sleep, and affective disruptions. However, this heterogeneity is often either ignored or assessed using only clinical assessments.

OBJECTIVES

We aimed to identify different PD sub-phenotypes in a longitudinal follow-up analysis and their electrophysiological profile based on resting-state electroencephalography (RS-EEG) and to assess their clinical significance over the course of the disease.

METHODS

Using electrophysiological features obtained from RS-EEG recordings and data-driven methods (similarity network fusion and source-space spectral analysis), we have performed a clustering analysis to identify disease sub-phenotypes and we examined whether their different patterns of disruption are predictive of disease outcome.

RESULTS

We showed that PD patients (n = 44) can be sub-grouped into three phenotypes with distinct electrophysiological profiles. These clusters are characterized by different levels of disruptions in the somatomotor network (Δ and β band), the frontotemporal network (α2 band) and the default mode network (α1 band), which consistently correlate with clinical profiles and disease courses. These clusters are classified into either moderate (only-motor) or mild-to-severe (diffuse) disease. We showed that EEG features can predict cognitive evolution of PD patients from baseline, when the cognitive clinical scores were overlapped.

CONCLUSIONS

The identification of novel PD subtypes based on electrical brain activity signatures may provide a more accurate prognosis in individual patients in clinical practice and help to stratify subgroups in clinical trials. Innovative profiling in PD can also support new therapeutic strategies that are brain-based and designed to modulate brain activity disruption. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Efficacy of aripiprazole as adjunctive therapy in major depressive disorder with somatic symptoms: A randomized, double-blind, placebo-controlled trial with clinical and electroencephalography evidence

BACKGROUND

Somatic symptoms, which are common in major depressive disorder (MDD), are associated with a worse prognosis and increased health costs.

AIMS

This randomized, double-blind, placebo-controlled study evaluated the efficacy of aripiprazole augmentation in MDD patients with somatic symptoms.

METHODS

In all, 41 MDD patients with somatic symptoms completed the study. Participants who had been on a stable dose of antidepressants for at least 1 month were randomly assigned to receive an 8-week adjunctive treatment with either aripiprazole or placebo. The initiation dose of aripiprazole was 2 mg/day, which was later adjusted to 1-10 mg/day. The primary endpoint was the change in the Symptom Checklist-90-Revised-Somatization (SCL-90-R-SOM) score. We collected quantitative electroencephalogram data and performed spectral analyses to obtain the absolute power of frequency bands.

RESULTS/OUTCOMES

The aripiprazole group (n = 20; 2.98 ± 1.75 mg/day) showed a significant improvement in SCL-90-R-SOM scores compared to the placebo group (n = 21; F = 8.56, p = 0.006), without significant differences in changes in depression and anxiety symptoms. Compared to the control, the aripiprazole group showed a greater decrease in total alpha power (F = 7.03, p = 0.01). Changes in frontal alpha power were positively correlated with changes in SCL-90-R-SOM scores in the aripiprazole group (r = 0.53, p = 0.014).

CONCLUSIONS/INTERPRETATION

Aripiprazole adjunctive to antidepressants in patients with MDD and somatic symptoms improved somatic symptom severity without significant safety concerns, and this improvement correlated with a decrease in total and frontal alpha power.Trial Registration: https://cris.nih.go.kr; identifier: KCT0004607.

Individual-Specific Characterization of Event-Related Hemodynamic Responses during an Auditory Task: An Exploratory Study

Functional near-infrared spectroscopy (fNIRS) has been established as an informative modality for understanding the hemodynamic-metabolic correlates of cortical auditory processing. To date, such knowledge has shown broad clinical applications in the diagnosis, treatment, and intervention procedures in disorders affecting auditory processing; however, exploration of the hemodynamic response to auditory tasks is yet incomplete. This holds particularly true in the context of auditory event-related fNIRS experiments, where preliminary work has shown the presence of valid responses while leaving the need for more comprehensive explorations of the hemodynamic correlates of event-related auditory processing. In this study, we apply an individual-specific approach to characterize fNIRS-based hemodynamic changes during an auditory task in healthy adults. Oxygenated hemoglobin (HbO₂) concentration change time courses were acquired from eight participants. Independent component analysis (ICA) was then applied to isolate individual-specific class discriminative spatial filters, which were then applied to HbO₂ time courses to extract auditory-related hemodynamic features. While six of eight participants produced significant class discriminative features before ICA-based spatial filtering, the proposed method identified significant auditory hemodynamic features in all participants. Furthermore, ICA-based filtering improved correlation between trial labels and extracted features in every participant. For the first time, this study demonstrates hemodynamic features important in experiments exploring auditory processing as well as the utility of individual-specific ICA-based spatial filtering in fNIRS-based feature extraction techniques in auditory experiments. These outcomes provide insights for future studies exploring auditory hemodynamic characteristics and may eventually provide a baseline framework for better understanding auditory response dysfunctions in clinical populations.

A randomized controlled study of remote computerized cognitive, neurofeedback, and combined training in the treatment of children with attention-deficit/hyperactivity disorder

There is an increasing interest in non-pharmacological treatments for children with attention-deficit/hyperactivity disorder (AD/HD), especially digital techniques that can be remotely delivered, such as neurofeedback (NFT) and computerized cognitive training (CCT). In this study, a randomized controlled design was used to compare training outcomes between remotely delivered NFT, CCT, and combined NFT/CCT training approaches. A total of 121 children with AD/HD were randomly assigned to the NFT, CCT, or NFT/CCT training groups, with 80 children completing the training program. Pre- and post-training symptoms (primary outcome), executive and daily functions were measured using questionnaires as well as resting EEG during eyes-closed (EC) and eyes-open (EO) conditions. After 3 months of training, the inattentive and hyperactive/impulsive symptoms, inhibition, working memory, learning and life skills of the three groups of children were significantly improved. The objective EEG activity showed a consistent increase in the relative alpha power in the EO condition among the three training groups. Training differences were not observed between groups. There was a positive correlation between pre-training EO relative alpha power and symptom improvement scores of inattention and hyperactivity/impulsivity, as well as a negative correlation between pre-training inattention scores and change in EO relative alpha. This study verified the training effects of NFT, CCT, and combined NFT/CCT training in children with AD/HD and revealed an objective therapeutic role for individual relative alpha activity. The verified feasibility and effectiveness of home-based digital training support promotion and application of digital remote training.

Pilot study of a mobile application-based intervention to induce changes in neural activity in the frontal region and behaviors in children with attention deficit hyperactivity disorder and/or intellectual disability

Children with neurodevelopmental disorders, such as attention deficit hyperactivity disorder (ADHD) and intellectual disability (ID), need early intervention and continuous treatment. We aimed to investigate the feasibility and acceptability of mobile application-based interventions in children with ADHD and ID in supporting attention and cognitive function. Twenty-six children with ADHD and/or ID with attention and cognition difficulties were recruited. Participants completed a 12-week mobile application-based intervention. To assess whether digital intervention improved attention and cognitive function, we used the Comprehensive Attention Test (CAT), Cambridge Neuropsychological Tests Automated Battery (CANTAB), and electroencephalography (EEG) to examine direct changes in children's behavior and neural activity. Clinicians and parents assessed changes using the Behavior Rating Inventory of Executive Function, Second Edition (BRIEF-2), Korean version of the ADHD Rating Scale (K-ARS), Clinical Global Impression-Improvement Scale, and parental questionnaires. The intervention induced changes in neural activities on EEG and behavior but there were no significant changes in CAT and CANTAB results. Relative theta and alpha power were significantly lower post-intervention in the eyes-open (EO) condition of EEG recording and these changes were mainly observed in the frontal regions of the brain. Parental reports using the BRIEF-2 and K-ARS noted significant improvements in executive function, attention, and hyperactivity-impulsivity. In addition, the clinical impression improved in 60% of participants. These results provide evidence that a mobile application-based intervention has the benefit of supporting children with ADHD and/or ID. Digital intervention could change neural activity and improve children's attention and cognitive function. Given our findings, we suggested that mobile application-based digital therapeutics may have great potential for helping children with neurodevelopmental disorders who need continuous treatment.

Characteristics of Attention-Deficit/Hyperactivity Disorder Subtypes in Children Classified Using Quantitative Electroencephalography

PURPOSE

This study used quantitative electroencephalography (QEEG) to investigate the characteristics of attention-deficit/hyperactivity disorder (ADHD) subtypes in children.

PATIENTS AND METHODS

There were 69 subjects (42 with ADHD and 27 neurotypical (NT)) in this study. A semi-structured interview was conducted with each participant for psychiatric diagnostic evaluation. We measured the absolute and relative power in 19 channels and analyzed QEEG using the following frequency ranges: delta (1-4 Hz), theta (4-8 Hz), alpha 1 (8-10 Hz), alpha 2 (10-12 Hz), beta 1 (12-15 Hz), beta 2 (15-20 Hz), beta 3 (20-30 Hz), and gamma (30-45 Hz). Group analyses and EEG noise preprocessing were conducted using iSyncBrain, a cloud-based, artificial intelligence EEG analysis platform. Analysis of covariance adjusted for IQ, age, and sex was used.

RESULTS

QEEG analysis revealed three ADHD subtypes, characterized by (A) elevated relative fast alpha and beta power, (B) elevated absolute slow frequency (delta and theta power), or (C) elevated absolute and relative beta power. A significant difference was found in the Korean ADHD Rating Scale (K-ARS) among the four groups (df=3, F=8.004, p<0.001); group C had the highest score (25.31±11.16), followed by group A (21.67±13.18). The score of group B (12.64±7.84) was similar to that of the NT group (11.07±6.12) and did not reach the cut-off point of the K-ARS. In the Wender-Utah Rating Scale (WURS), group B score (55.82±23.17) was significantly higher than the NT group score (42.81±13.26).

CONCLUSION

These results indicate that children with ADHD do not constitute a neurophysiologically homogenous group. Children with QEEG subtype B (elevated slow frequency) may be difficult to distinguish from normal children using the K-ARS, which is the most common screening tool for ADHD. Moreover, parents of children with this subtype may be less sensitive to observing ADHD symptoms.

Clinical Applications of Functional Near-Infrared Spectroscopy in Children and Adolescents with Psychiatric Disorders

The purpose of this review is to examine the clinical use of functional near-infrared spectroscopy (fNIRS) in children and adolescents with psychiatric disorders. Many studies have been conducted using objective evaluation tools for psychiatric evaluation, such as predicting psychiatric symptoms and treatment responses. Compared to other tools, fNIRS has the advantage of being a noninvasive, inexpensive, and portable method and can be used with patients in the awake state. This study mainly focused on its use in patients with attention-deficit/hyperactivity disorder and autism spectrum disorder. We hope that research involving fNIRS will be actively conducted in various diseases in the future.

The Role of Quantitative Electroencephalogram in the Diagnosis and Subgrouping of Attention-Deficit/Hyperactivity Disorder

Attention-deficit/hyperactivity disorder (ADHD) leads to functional decline in academic performance, interpersonal relationships, and development in school-aged children. Early diagnosis and appropriate intervention can significantly reduce the functional decline caused by ADHD. Currently, there is no established biological marker for ADHD. Some studies have suggested that various indicators from the quantitative electroencephalogram (QEEG) may be useful biological markers for the diagnosis of ADHD. Until the 2010s, theta/beta ratio (TBR) was a biomarker candidate for ADHD that consistently showed high diagnostic value. However, limitations of TBR have recently been reported. Studies have demonstrated that phase-amplitude coupling, especially theta phase-gamma amplitude coupling, are related to cognitive dysfunction and may assist in the diagnosis of ADHD. As yet, the underlying mechanism is not clearly established, and the clinical efficacy of these biomarkers needs to be proven through well-controlled studies. Based on the heterogeneous characteristics of ADHD, subgrouping through QEEG plays a key role in diagnosis and treatment planning. Sophisticated, well-designed studies and meta-analyses are necessary to confirm these findings.