BACKGROUND:Psychiatric disorders are traditionally classified within diagnostic categories, but this approach has limitations. The Research Domain Criteria (RDoC) constitute a research classification system for psychiatric disorders based on dimensions within domains that cut across these psychiatric diagnoses. The overall aim of RDoC is to better understand mental illness in terms of dysfunction in fundamental neurobiological and behavioral systems, leading to better diagnosis, prevention, and treatment. METHODS:A unique electroencephalographic feature, referred to as spindling excessive beta, has been studied in relation to impulse control and sleep as part of the arousal/regulatory system RDoC domain. Here, we studied electroencephalographic frontal beta activity as a potential transdiagnostic biomarker capable of diagnosing and predicting impulse control and sleep problems. RESULTS:We showed in the first dataset (n = 3279) that the probability of having spindling excessive beta, classified by a deep learning algorithm, was associated with poor sleep maintenance and low daytime impulse control. Furthermore, in 2 additional, independent datasets (iSPOT-A [International Study to Predict Optimized Treatment in ADHD], n = 336; iSPOT-D [International Study to Predict Optimized Treatment in Depression], n = 1008), we revealed that conventional frontocentral beta power and/or spindling excessive beta probability, referred to as Brainmarker-III, is associated with a diagnosis of attention-deficit/hyperactivity disorder, with remission to methylphenidate in children with attention-deficit/hyperactivity disorder in a sex-specific manner, and with remission to antidepressant medication in adults with major depressive disorder in a drug-specific manner. CONCLUSION:Our results demonstrate the value of the RDoC approach in psychiatry research for the discovery of biomarkers with diagnostic and treatment prediction capacities.

BACKGROUND:Attention-deficit/hyperactivity disorder is characterized by neurobiological heterogeneity, possibly explaining why not all patients benefit from a given treatment. As a means to select the right treatment (stratification), biomarkers may aid in personalizing treatment prescription, thereby increasing remission rates.METHODS:The biomarker in this study was developed in a heterogeneous clinical sample (N = 4249) and first applied to two large transfer datasets, a priori stratifying young males (<18 years) with a higher individual alpha peak frequency (iAPF) to methylphenidate (N = 336) and those with a lower iAPF to multimodal neurofeedback complemented with sleep coaching (N = 136). Blinded, out-of-sample validations were conducted in two independent samples. In addition, the association between iAPF and response to guanfacine and atomoxetine was explored.RESULTS:Retrospective stratification in the transfer datasets resulted in a predicted gain in normalized remission of 17% to 30%. Blinded out-of-sample validations for methylphenidate (n = 41) and multimodal neurofeedback (n = 71) corroborated these findings, yielding a predicted gain in stratified normalized remission of 36% and 29%, respectively.CONCLUSIONS:This study introduces a clinically interpretable and actionable biomarker based on the iAPF assessed during resting-state electroencephalography. Our findings suggest that acknowledging neurobiological heterogeneity can inform stratification of patients to their individual best treatment and enhance remission rates.

Attention-deficit/hyperactivity disorder (ADHD) is characterized by neurobiological heterogeneity, possibly explaining why not all patients benefit from a given treatment. As a means to select the right treatment (stratification), biomarkers may aid in personalizing treatment prescription, thereby increasing remission rates.The present study introduces a clinically interpretable and actionable, age- and sex-standardized biomarker based on individual alpha peak frequency (iAPF) assessed during resting-state electroencephalography (EEG). The biomarker was developed in a heterogeneous sample (N=4249), and stratifies patients with a higher iAPF to Methylphenidate (MPH; N=336) and those with a lower iAPF to Neurofeedback (NFB; N=136), resulting in a predicted gain in normalized remission of 17-30%. Blinded out-of-sample validation studies for MPH (N=58) and NFB (N=96) corroborated these findings, yielding a predicted gain in stratified normalized remission of 36% and 29%, respectively.These findings suggest that acknowledging neurobiological heterogeneity can inform stratification of patients to their individual best treatment and enhance remission rates.

Despite a variety of different treatment options for major depressive disorder (MDD), many patients do not experience adequate symptom relief.Moving from the standard one-size-fits-all treatment prescription towards stratifying patients to different interventions by means of biomarkers, could aid in increasing clinical remission.We recently developed a clinically implementable and easily interpretable biomarker (Brainmarker-I) based on the individual alpha peak frequency (iAPF) measured during resting-state electroencephalography (EEG) in a large heterogeneous dataset (N¼4249), and conducted blinded out-ofsample validations in two independent samples, successfully predicting remission to different pharmaceutical and non-pharmaceutical interventions of attention-deficit/hyperactivity-disorder.Next, we applied Brainmarker-I to several datasets to predict remission to different MDD treatments including rTMS (10Hz left DLPFC and 1Hz right DLPFC) and pharmaceutical interventions (sertraline, escitalopram, venlafaxine).Positive predictive values (PPVs) were employed to indicate the direction of treatment stratification.Normalized PPVs were calculated to improve comparability of predicted increase in remission rates across datasets.As demonstrated in earlier work, an iAPF close to the stimulation frequency of 10Hz at the site of stimulation best predicted remission to 10Hz rTMS, with an increase in predicted normalized remission rate (normalized PPV) of 24%.A relatively lower iAPF suggested an increased likelihood of remission to sertraline, while individuals with a relatively higher iAPF were more likely to remit to 1Hz rTMS.Escitalopram and venlafaxine were exploratively examined in the same way, and results are discussed.Here we present a transdiagnostic treatment stratification biomarker that is capable of predicting differential treatment outcome in patient subgroups, and that is ready for implementation in clinical practice.Brainmarker-I represents a first step from a one-size-fits-all treatment approach towards personalized psychiatry in depression treatment.

Neurofeedback (NFB) research has reported improved concentration and attention in children with attention deficit/hyperactivity disorder (ADHD) and progress maintained over time.Would that also apply to children with an IQ between 50 and 70 (mild mental retardation [MMR]) and an IQ between 70 and 85 (borderline retardation [BR]) with characteristics of ADHD?To our knowledge this is the first NFB treatment study with long-term follow-up in this particular group.Ten adolescents with MMR and BR and ADHD received 30 sessions of quantitative electroencephalogram (QEEG)-based NFB.QEEG differences with a gender-and age-matched group without mental handicap and ADHD (data provided by BRAINnet) were investigated, at pre-and posttreatment and at 6-month follow-up.Neuropsychological functioning was tested administering the Bourdon-Vos, and the Amsterdam Neuropsychological Testing Program subscales SA DOTS and SSV.Pretreatment eyes-closed EEGs were not statistically different in the children with MMR compared to the controls.With eyes open higher amplitudes were found in the lower frequencies in the children with MMR, normalizing over time.The neuropsychological tests improved for reaction times and errors.On the complex tasks in the SSV a number of errors remained.The subjects perceived an improvement in ADHD and increasingly enjoyed the study.After NFB treatment, attention and concentration in children with MMR and BR have improved.Task span and effort also increased, although impulse control remained weak.This may be explained by a limited working memory capacity.The subjective reports may have been affected by situational factors and should be interpreted with caution.This study is limited by its nonrandomized design.

ABSTRACT Background. Operant conditioning of one's slow cortical potential (SCP) or sensorimotor rhythm (SMR) can be used to control epilepsy or to manipulate external devices, as applied in BCI (Brain-Computer Interface). A commonly accepted view that both SCP and SMR are reflections of central arousal suggests a functional relationship between SCP and SMR networks. Method. The operant conditioning of SCP or SMR was tested with a single electroencephalographic (EEG) channel wireless biofeedback system. A series of trainings taught 19 participants to control SCP or SMR over vertex during 20 neurofeedback sessions. Each session consisted of 96 trials to decrease cortical arousal (SCP positivity/SMR enhancement) and 64 trials to increase cortical arousal (SCP negativity/SMR suppression). In each trial, participants were required to exceed an individual threshold level of the feedback parameter relative to a 500-msec prefeedback baseline and to hold this level for 2 sec (SCP) or 0.5 sec (SMR) to obtain reinf...

AIMS:QEEG and neuropsychological tests were used to investigate the underlying neural processes in dyslexia.METHODS:A group of dyslexic children were compared with a matched control group from the Brain Resource International Database on measures of cognition and brain function (EEG and coherence).RESULTS:The dyslexic group showed increased slow activity (Delta and Theta) in the frontal and right temporal regions of the brain. Beta-1 was specifically increased at F7. EEG coherence was increased in the frontal, central and temporal regions for all frequency bands. There was a symmetric increase in coherence for the lower frequency bands (Delta and Theta) and a specific right-temporocentral increase in coherence for the higher frequency bands (Alpha and Beta). Significant correlations were observed between subtests such as Rapid Naming Letters, Articulation, Spelling and Phoneme Deletion and EEG coherence profiles.DISCUSSION:The results support the double-deficit theory of dyslexia and demonstrate that the differences between the dyslexia and control group might reflect compensatory mechanisms.INTEGRATIVE SIGNIFICANCE:These findings point to a potential compensatory mechanism of brain function in dyslexia and helps to separate real dysfunction in dyslexia from acquired compensatory mechanisms.

New treatments for Alzheimer's disease require early detection of cognitive decline. Most studies seeking to identify markers of early cognitive decline have focused on a limited number of measures. We sought to establish the profile of brain function measures which best define early neuropsychological decline. We compared subjects with subjective memory complaints to normative controls on a wide range of EEG derived measures, including a new measure of event-related spatio-temporal waves and biophysical modeling, which derives anatomical and physiological parameters based on subject's EEG measurements. Measures that distinguished the groups were then related to cognitive performance on a variety of learning and executive function tasks. The EEG measures include standard power measures, peak alpha frequency, EEG desynchronization to eyes-opening, and global phase synchrony. The most prominent differences in subjective memory complaint subjects were elevated alpha power and an increased number of spatio-temporal wave events. Higher alpha power and changes in wave activity related most strongly to a decline in verbal memory performance in subjects with subjective memory complaints, and also declines in maze performance and working memory reaction time. Interestingly, higher alpha power and wave activity were correlated with improved performance in reverse digit span in the subjective memory complaint group. The modeling results suggest that differences in the subjective memory complaint subjects were due to a decrease in cortical and thalamic inhibitory gains and slowed dendritic time-constants. The complementary profile that emerges from the variety of measures and analyses points to a nonlinear progression in electrophysiological changes from early neuropsychological decline to late-stage dementia, and electrophysiological changes in subjective memory complaint that vary in their relationships to a range of memory-related tasks.