Neurofeedback (NF) has gained increasing interest in the treatment of attention-deficit/hyperactivity disorder (ADHD). Given learning principles underlie NF, lasting clinical treatment effects may be ...expected. This systematic review and meta-analysis addresses the sustainability of neurofeedback and control treatment effects by considering randomized controlled studies that conducted follow-up (FU; 2–12 months) assessments among children with ADHD. PubMed and Scopus databases were searched through November 2017. Within-group and between-group standardized mean differences (SMD) of parent behavior ratings were calculated and analyzed. Ten studies met inclusion criteria (NF: ten studies,
N
= 256; control: nine studies,
N
= 250). Within-group NF effects on inattention were of medium effect size (ES) (SMD = 0.64) at post-treatment and increased to a large ES (SMD = 0.80) at FU. Regarding hyperactivity/impulsivity, NF ES were medium at post-treatment (SMD = 0.50) and FU (SMD = 0.61). Non-active control conditions yielded a small significant ES on inattention at post-treatment (SMD = 0.28) but no significant ES at FU. Active treatments (mainly methylphenidate), had large ES for inattention (post: SMD = 1.08; FU: SMD = 1.06) and medium ES for hyperactivity/impulsivity (post: SMD = 0.74; FU: SMD = 0.67). Between-group analyses also revealed an advantage of NF over non-active controls inattention (post: SMD = 0.38; FU: SMD = 0.57); hyperactivity–impulsivity (post: SMD = 0.25; FU: SMD = 0.39), and favored active controls for inattention only at pre-post (SMD = − 0.44). Compared to non-active control treatments, NF appears to have more durable treatment effects, for at least 6 months following treatment. More studies are needed for a properly powered comparison of follow-up effects between NF and active treatments and to further control for non-specific effects.
Summary
Psychiatric research applications of electroencephalography (EEG), the earliest approach to imaging human cortical brain activity, are attracting increasing scientific and clinical interest. ...For more than 40 years, EEG research has attempted to characterize and quantify the neurophysiology of attention-deficit/hyperactivity disorder (ADHD), most consistently associating it with increased frontocentral theta band activity and increased theta to beta (θ/β) power ratio during rest compared to non-ADHD controls. Recent reports suggest that while these EEG measures demonstrate strong discriminant validity for ADHD, significant EEG heterogeneity also exists across ADHD-diagnosed individuals. In particular, additional studies validating the use of the θ/β power ratio measure appear to be needed before it can be used for clinical diagnosis. In recent years, the number and the scientific quality of research reports on EEG-based neurofeedback (NF) for ADHD have grown considerably, although the studies reviewed here do not yet support NF training as a first-line, stand-alone treatment modality. In particular, more research is needed comparing NF to placebo control and other effective treatments for ADHD. Currently, after a long period of relative stasis, the neurophysiological specificity of measures used in EEG research is rapidly increasing. It is likely, therefore, that new EEG studies of ADHD using higher density recordings and new measures drawn from viewing EEG as a 3-dimensional functional imaging modality, as well as intensive re-analyses of existing EEG study data, can better characterize the neurophysiological differences between and within ADHD and non-ADHD subjects, and lead to more precise diagnostic measures and effective NF approaches.
Use of EEG to Diagnose ADHD Lenartowicz, Agatha; Loo, Sandra K.
Current psychiatry reports,
11/2014, Letnik:
16, Številka:
11
Journal Article
Recenzirano
Odprti dostop
Electroencephalography (EEG) has, historically, played a focal role in the assessment of neural function in children with attention deficit hyperactivity disorder (ADHD). We review here the most ...recent developments in the utility of EEG in the diagnosis of ADHD, with emphasis on the most commonly used and emerging EEG metrics and their reliability in diagnostic classification. Considering the clinical heterogeneity of ADHD and the complexity of information available from the EEG signals, we suggest that considerable benefits are to be gained from multivariate analyses and a focus towards understanding of the neural generators of EEG. We conclude that while EEG cannot currently be used as a diagnostic tool, vast developments in analytical and technological tools in its domain anticipate future progress in its utility in the clinical setting.
Brain connectivity in autism spectrum disorder Mohammad-Rezazadeh, Iman; Frohlich, Joel; Loo, Sandra K ...
Current opinion in neurology,
04/2016, Letnik:
29, Številka:
2
Journal Article
Recenzirano
Odprti dostop
Many studies have reported that individuals with autism spectrum disorder (ASD) have different brain connectivity patterns compared with typically developing individuals. However, the results of more ...recent studies do not unanimously support the traditional view in which individuals with ASD have lower connectivity between distant brain regions and increased connectivity within local brain regions. In this review, we discuss different methods for measuring brain connectivity and how the use of different metrics may contribute to the lack of convergence of investigations of connectivity in ASD.
The discrepancy in brain connectivity results across studies may be due to important methodological factors, such as the connectivity measure applied, the age of patients studied, the brain region(s) examined, and the time interval and frequency band(s) in which connectivity was analyzed.
We conclude that more sophisticated electroencephalography analytic approaches should be utilized to more accurately infer causation and directionality of information transfer between brain regions, which may show dynamic changes of functional connectivity in the brain. Moreover, further investigations of connectivity with respect to behavior and clinical phenotype are needed to probe underlying brain networks implicated in core deficits of ASD.
Background
Electroencephalography (EEG) and related measures have a long and productive history in child psychopathology research and are currently experiencing a renaissance in interest, ...particularly for use as putative biomarkers.
Method and Scope
First, the recent history leading to the use of EEG measures as endophenotypes and biomarkers for disease and treatment response are reviewed. Two key controversies within the area of noninvasive human electrophysiology research are discussed, and problems that currently either function as barriers or provide gateways to progress. First, the differences between the main types of EEG measurements (event‐related potentials, quantitative EEG, and time–frequency measures) and how they can contribute collectively to better understanding of cortical dynamics underlying cognition and behavior are highlighted. Second, we focus on the ongoing shift in analytic focus to specific cortical sources and source networks whose dynamics are relevant to the clinical and experimental focus of the study, and the effective increase in source signal‐to‐noise ratio (SNR) that may be obtained in the process.
Conclusions
Understanding of these issues informs any discussion of current trends in EEG research. We highlight possible ways to evolve our understanding of brain dynamics beyond the apparent contradictions in understanding and modeling EEG activity highlighted by these controversies. Finally, we summarize some promising future directions of EEG biomarker research in child psychopathology.
The heterogeneity in clinical presentation and outcome in neurodevelopmental disorders such as attention deficit hyperactivity disorder (ADHD) autism spectrum disorder (ASD) necessitates the ...identification and validation of biomarkers that can guide diagnosis, predict developmental outcomes, and monitor treatment response. Electrophysiology holds both practical and theoretical advantages as a clinical biomarker in neurodevelopmental disorders, and considerable effort has been invested in the search for electroencephalography (EEG) biomarkers in ADHD and ASD.
Here, we discuss the major themes in the evaluation of biomarkers and then review studies that have applied EEG to better inform diagnosis, focusing on the controversy surrounding the theta:beta ratio in ADHD; prediction of risk, highlighting recent studies of infants at high risk for ASD; and treatment monitoring, presenting new efforts in the redefinition of outcome measures in clinical trials of ASD treatment.
We conclude that insights gained from EEG studies will contribute significantly to a more mechanistic understanding of these disorders and to the development of biomarkers that can assist with diagnosis, prognosis, and intervention. There is a need, however, to utilize approaches that accommodate, rather than ignore, diagnostic heterogeneity and individual differences.
Background
Attention‐deficit/hyperactivity disorder (ADHD) is a heterogeneous condition for which multiple efforts to characterize brain state differences are underway. The objective of this study ...was to identify distinct subgroups of resting electroencephalography (EEG) profiles among children with and without ADHD and subsequently provide extensive clinical characterization of the subgroups.
Methods
Latent class analysis was used with resting state EEG recorded from a large sample of 781 children with and without ADHD (N = 620 ADHD, N = 161 Control), aged 6–18 years old. Behavioral and cognitive characteristics of the latent classes were derived from semistructured diagnostic interviews, parent completed behavior rating scales, and cognitive test performance.
Results
A five‐class solution was the best fit for the data, of which four classes had a defining spectral power elevation. The distribution of ADHD and control subjects was similar across classes suggesting there is no one resting state EEG profile for children with or without ADHD. Specific latent classes demonstrated distinct behavioral and cognitive profiles. Those with elevated slow‐wave activity (i.e. delta and theta band) had higher levels of externalizing behaviors and cognitive deficits. Latent subgroups with elevated alpha and beta power had higher levels of internalizing behaviors, emotion dysregulation, and intact cognitive functioning.
Conclusions
There is population‐level heterogeneity in resting state EEG subgroups, which are associated with distinct behavioral and cognitive profiles. EEG measures may be more useful biomarkers of ADHD outcome or treatment response rather than diagnosis.
We investigated the value of transcriptome sequencing (RNAseq) in ascertaining the consequence of DNA variants on RNA transcripts to improve the diagnostic rate from exome or genome sequencing for ...undiagnosed Mendelian diseases spanning a wide spectrum of clinical indications.
From 234 subjects referred to the Undiagnosed Diseases Network, University of California–Los Angeles clinical site between July 2014 and August 2018, 113 were enrolled for high likelihood of having rare undiagnosed, suspected genetic conditions despite thorough prior clinical evaluation. Exome or genome sequencing and RNAseq were performed, and RNAseq data was integrated with genome sequencing data for DNA variant interpretation genome-wide.
The molecular diagnostic rate by exome or genome sequencing was 31%. Integration of RNAseq with genome sequencing resulted in an additional seven cases with clear diagnosis of a known genetic disease. Thus, the overall molecular diagnostic rate was 38%, and 18% of all genetic diagnoses returned required RNAseq to determine variant causality.
In this rare disease cohort with a wide spectrum of undiagnosed, suspected genetic conditions, RNAseq analysis increased the molecular diagnostic rate above that possible with genome sequencing analysis alone even without availability of the most appropriate tissue type to assess.
Most interventions for childhood mental health problems require significant parental involvement, and treatment programs are increasingly incorporating components aimed at enhancing parents’ own ...self-regulation in the context of potentially stressful parent-child interactions. This paper discusses the promise of EEG in examining the rapidly unfolding perceptual, cognitive, emotional, and regulatory processes that occur in parenting, in hopes of ultimately informing child and family interventions. First, we review two separate bodies of work that have used EEG with parents: one examining event-related potential (ERP) measures, and the other examining frontal alpha asymmetry (FAA). We discuss benefits of each within the study of parenting, and also suggest other EEG metrics (such as event-related time-frequency analyses) that can be leveraged to fill current gaps in our knowledge. Finally, we discuss the potential for these findings to inform clinical work with children and families, such as identifying biomarkers that could aid in assessment, treatment recommendations, and monitoring response to interventions.
•Child and adolescent mental health interventions are increasingly incorporating components targeting parent self-regulation.•EEG may be useful in studying perceptual, cognitive, and emotional processes that occur during parent-child interactions.•Event-related potential and frontal alpha asymmetry research have provided important information about parenting processes.•Future parenting research may benefit from novel EEG metrics, such as event-related time frequency analyses.•Findings from EEG research with parents have potential to ultimately inform clinical work with children and families.
In the current study we sought to dissociate the component processes of working memory (WM) (vigilance, encoding and maintenance) that may be differentially impaired in attention-deficit/ ...hyperactivity disorder (ADHD). We collected electroencephalographic (EEG) data from 52 children with ADHD and 47 typically developing (TD) children, ages 7-14 years, while they performed a spatial Sternberg working memory task. We used independent component analysis and time-frequency analysis to identify midoccipital alpha (8-12 Hz) to evaluate encoding processes and frontal midline theta (4-7 Hz) to evaluate maintenance processes. We tested for effects of task difficulty and cue processing to evaluate vigilance. Children with ADHD showed attenuated alpha band event-related desynchronization (ERD) during encoding. This effect was more pronounced when task difficulty was low (consistent with impaired vigilance) and was predictive of memory task performance and symptom severity. Correlated with alpha ERD during encoding were alpha power increases during the maintenance period (relative to baseline), suggesting a compensatory effort. Consistent with this interpretation, midfrontal theta power increases during maintenance were stronger in ADHD and in high-load memory conditions. Furthermore, children with ADHD exhibited a maturational lag in development of posterior alpha power whereas age-related changes in frontal theta power deviated from the TD pattern. Last, subjects with ADHD showed age-independent attenuation of evoked responses to warning cues, suggesting low vigilance. Combined, these three EEG measures predicted diagnosis with 70% accuracy. We conclude that the interplay of impaired vigilance and encoding in ADHD may compromise maintenance and lead to impaired WM performance in this group.
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