Publications

The understanding and treatment of psychiatric disorders, which are known to be neurobiologically and clinically heterogeneous, could benefit from the data-driven identification of disease subtypes. Here, we report the identification of two clinically relevant subtypes of post-traumatic stress disorder (PTSD) and major depressive disorder (MDD) on the basis of robust and distinct functional connectivity patterns, prominently within the frontoparietal control network and the default mode network. We identified the disease subtypes by analysing, via unsupervised and supervised machine learning, the power-envelope-based connectivity of signals reconstructed from high-density resting-state electroencephalography in four datasets of patients with PTSD and MDD, and show that the subtypes are transferable across independent datasets recorded under different conditions. The subtype whose functional connectivity differed most from those of healthy controls was less responsive to psychotherapy treatment for PTSD and failed to respond to an antidepressant medication for MDD. By contrast, both subtypes responded equally well to two different forms of repetitive transcranial magnetic stimulation therapy for MDD. Our data-driven approach may constitute a generalizable solution for connectome-based diagnosis. Two clinically relevant subtypes of post-traumatic stress disorder and major depressive disorder have been identified via machine learning analyses of functional connectivity patterns in resting-state electroencephalography.

Objective The aim of the current study was to attempt to replicate the finding that the individual alpha frequency (IAF) as well as the absolute difference between IAF and 10 Hz stimulation frequency (IAF-prox) is related to treatment outcome. Methods Correlations were performed to investigate the relationship between IAF-prox and percentage symptom improvement in a sample of 153 patients with major depressive disorder treated with 10 Hz (N = 59) to the left dorsolateral prefrontal cortex (DLPFC) or 1 Hz (N = 94) to the right DLPFC repetitive Transcranial Magnetic Stimulation (rTMS). Results There was a significant negative correlation between IAF-prox and the percentage of symptom improvement only for the 10 Hz group. Curve fitting models revealed that there was a quadratic association between IAF and treatment response in the 10 Hz group, with a peak at 10 Hz IAF. Conclusion The main result of Corlier and colleagues was replicated, and the findings suggest that the distance between 10 Hz stimulation frequency and the IAF may influence clinical outcome in a non-linear manner. Significance rTMS is often administered at a frequency of 10 Hz, which is the center of the EEG alpha frequency band. The results can make a significant contribution to optimizing the clinical application of rTMS.

Background Approaches for determining a functionally meaningful dorsolateral prefrontal cortex (DLPFC) stimulation site is imperative for optimising repetitive transcranial magnetic stimulation (rTMS) response rates for treatment-resistant depression. One approach is neuro-cardiac-guided rTMS (NCG-TMS) in which high frequency rTMS is applied to the DLPFC to determine the site of largest heart rate deceleration. This site is thought to index a frontal-vagal autonomic pathway that intersects a key pathway believed to underlie rTMS response. Objective We aimed to independently replicate previous findings of high-frequency NCG-TMS and extend it to evaluate the use of low-frequency rTMS for NCG-TMS. Methods Twenty healthy participants (13 female; aged 38.6±13.9) underwent NCG-TMS on frontal, fronto-central (active) and central (control) sites. Three 5 sec trains of 10 Hz were provided at each left hemisphere site for high-frequency NCG-TMS. For low-frequency NCG-TMS, 60 sec trains of 1 Hz were applied to left and right hemispheres and heart rate and heart rate variability outcome measures were analysed. Results For high-frequency NCG-TMS, heart rate deceleration was observed at the left frontal compared with the central site. For low-frequency NCG-TMS, accelerated heart rate was found at the right frontal compared with central sites. No other site differences were observed. Conclusion Opposite patterns of heart rate activity were found for low- and high-frequency NCG-TMS. The high-frequency NCG-TMS data replicate previous findings and support further investigations on the clinical utility of NCG-TMS for optimising rTMS site localisation. Further work assessing the value of low-frequency NCG-TMS for rTMS site localisation is warranted.

Stimulant medication and behaviour therapy are the most often applied and accepted treatments for Attention-Deficit/Hyperactivity-Disorder (ADHD). Here we explore where the non-pharmacological clinical intervention known as neurofeedback (NFB), fits on the continuum of empirically supported treatments, using standard protocols. In this quantitative review we utilized an updated and stricter version of the APA guidelines for rating ‘well-established’ treatments and focused on efficacy and effectiveness using effect-sizes (ES) and remission, with a focus on long-term effects. Efficacy and effectiveness are compared to medication and behaviour therapy using benchmark studies. Only recent systematic reviews and meta-analyses as well as multi-centre randomized controlled trials (RCT’s) will be included. Two meta-analyses confirmed significant efficacy of standard neurofeedback protocols for parent and teacher rated symptoms with a medium effect size, and sustained effects after 6–12 months. Four multicenter RCT’s demonstrated significant superiority to semi-active control groups, with medium-large effect sizes end of treatment or follow-up and remission rates of 32–47%. Effectiveness in open-label studies was confirmed, no signs of publication bias were found and no significant neurofeedback-specific side effects have been reported. Standard neurofeedback protocols in the treatment of ADHD can be concluded to be a well-established treatment with medium to large effect sizes and 32–47% remission rates and sustained effects as assessed after 6–12 months.

The main and best evidence-based indication to date to apply repetitive Transcranial Magnetic Stimulation (rTMS) in psychiatric disorders is major depression. Nevertheless, given that the high occurrence of major depressive disorders poses a major challenge for health systems worldwide, there is an urgent need for improving the clinical efficacy of the existing approved rTMS applications and promoting the development of effective rTMS treatment approaches. Besides providing an overview of the current evidence here, we discuss novel stimulation patterns, targets, and coils; combined treatments and maintenance; personalization and stratification of rTMS parameters; and the treatment of subpopulations.

Neurofeedback is a well-investigated treatment for ADHD and epilepsy, especially when restricted to standard protocols such as theta/beta, slow cortical potentials and sensori-motor rhythm neurofeedback. Advances in any field are welcome and other techniques are being pursued. Manufacturers and clinicians are marketing 'superior' neurofeedback approaches including 19 channel Z-score neurofeedback (ZNFB) and 3-D LORETA neurofeedback (with or without Z-scores; LNFB). We conducted a review of the empirical literature to determine if such claims were warranted. This review included the above search terms in Pubmed, Google scholar and any references that met our criteria from the ZNFB publication list and was restricted to group based studies examining improvement in a clinical population that underwent peer review (book chapters, magazine articles or conference presentations are not included since these are not peer reviewed). Fifteen relevant studies emerged with only six meeting our criterion. Based on review of these studies it was concluded that empirical validation of these approaches is sorely lacking. There is no empirical data that supports the notion that 19-channel z-score neurofeedback is effective or superior. The quality of studies for LNFB was better compared to ZNFB and some suggestion for efficacy was demonstrated for ADHD and Tinnitus distress. However, these findings need to be replicated, extended to other populations and have yet to show any "superiority." Our conclusions continue to emphasize the pervasive lack of evidence supporting these approaches to neurofeedback and the implications of this are discussed.

Since 2017, repetitive transcranial magnetic stimulation (rTMS) has become eligible for reimbursement for the treatment of therapy-resistant depression in the Dutch healthcare system.
AIM: To initiate a guideline in the Netherlands and Belgium for the safe and effective application of rTMS for the treatment of depression.
METHOD: Based on literature review, existing guidelines and consensus among Dutch rTMS experts, recommendations were developed regarding the implementation of rTMS as a treatment of depression. All available evidence was weighed and discussed among all co-authors and recommendations were reached by consensus among the group.
RESULTS: rTMS targeting the dorsolateral prefrontal cortex (DLPFC) should be seen as a first choice in the treatment of depression using high-frequency rTMS (left) or, as an alternative, low-frequency rTMS (right). Stimulation protocols should use more than 1000 pulses per session for an average of 20-30 sessions, offered in 2-5 sessions per week. Contraindications for rTMS include epilepsy, intracranial presence of (magnetisable) metals, pacemaker and cochlear implant.
CONCLUSION: rTMS, performed by competent professionals is an effective and safe treatment for depression.

Prevalence rates of attention-deficit/hyperactivity disorder (ADHD) differ with geographical areas varying in sunlight intensity. Sun- or daylight reaching the retina establishes entrainment of the circadian clock to daylight. Changes herein, hence, alterations in clock alignment, could be reflected indirectly in inattention via sleep duration. We here studied (1) annual variation in inattention at treatment initiation; (2) annual variation in response to ADHD treatment [methylphenidate (MPH)] by day of treatment initiation; and (3) dose dependence. We predicted least baseline inattention during a period of high sunlight intensity implying more room for improvement (i.e., a better treatment response) when sunlight intensity is low. These hypotheses were not confirmed. High-dose treated patients, however, had significantly better attention after treatment than low-dosed treated patients, only when treated in the period from winter to summer solstice. Change in solar irradiance (SI) during low-dosed treatment period was negatively related to attentional improvement. The above described findings were primarily found in inattention ratings and replicated in omission errors on a continuous performance task. Daylight and inattention have been proposed to be related via mediation of the circadian system. One mechanism of MPH may be to enhance sensitivity to the diurnal entrainment to sunlight and the question can be raised whether appropriate lighting could potentiate the effects of stimulants.

Abstract Background Few studies focused on the relationship between psychological measures, major depressive disorder (MDD) and repetitive transcranial magnetic stimulation (rTMS) response. This study investigated several psychological measures as potential predictors for rTMS treatment response. Additionally, this study employed two approaches to evaluate the robustness of our findings by implementing immediate replication and full-sample exploration with strict p -thresholding. Methods This study is an open-label, multi-site study with a total of 196 MDD patients. The sample was subdivided in a Discovery (60% of total sample, n = 119) and Replication sample (40% of total sample, n = 77). Patients were treated with right low frequency (1 Hz) or left high frequency (10 Hz) rTMS at the dorsolateral prefrontal cortex. Clinical variables [Beck Depression Inventory (BDI), Neuroticism, Extraversion, Openness Five-Factor Inventory, and Depression, Anxiety, and Stress Scale, and BDI subscales] were obtained at baseline, post-treatment, and at follow-up. Predictors were analyzed in terms of statistical association, robustness (independent replication), as well as for their clinical relevance [positive predictive value (PPV) and negative predictive value (NPV)]. Results Univariate analyses revealed that non-responders had higher baseline anhedonia scores. Anhedonia scores at baseline correlated negatively with total BDI percentage change over time. This finding was replicated. However, anhedonia scores showed to be marginally predictive of rTMS response, and neither PPV nor NPV reached the levels of clinical relevance. Conclusions This study suggests that non-responders to rTMS treatment have higher baseline anhedonia scores. However, anhedonia was only marginally predictive of rTMS response. Since all other psychological measures did not show predictive value, it is concluded that psychological measures cannot be used as clinically relevant predictors to rTMS response in MDD.

We spend approximately a third of our lives sleeping, and many DSM-IV and DSM-5 disorders have sleep problems listed as diagnostic features and are often considered "comorbidities." However, very little is known about the role sleep problems play in the etiology of psychiatric disorders such as attention-deficit/hyperactivity disorder (ADHD).

Difficulties in predicting suicidal behavior hamper effective suicide prevention. Therefore, there is a great need for reliable biomarkers, and neuroimaging may help to identify such markers.

Low heart rate variability (HRV) has strongly been associated with an increased risk for cardiovascular disease. With cardiovascular disease being the number one cause of global deaths, factors that influence its development are relevant to understand. Season of birth has been suggested as one of the factors influencing the development of HRV. The current study was set up to replicate the finding that men born in winter have higher HRV later in life compared to those born in other seasons. To this end, we studied a sample of 1,871 healthy participants from the Brain Resource International Database during rest and during task. Furthermore, sex and age differences and associations with personality traits and psychiatric symptoms were explored. We replicated the earlier finding that men born in winter have a lower ratio of low frequency (LF) power to high frequency (HF) power during rest compared to summer and fall, and, although less pronounced, higher HF compared to summer. A difference between summer and winter for LF/HF in men was internally replicated using data recorded during task. Additionally, for both sexes, LF/HF ratio increased with age, and LF and HF both decreased. In general, LF/HF was lower in women, but heart rate was higher. In men, low HRV was associated with depression and the personality trait openness. In conclusion, results from a large multicenter data set covering the entire lifespan demonstrate that HRV changes with age in both sexes and confirm that season of birth influences HRV later in life in men.

Current traditional treatments for ADHD present serious limitations in terms of long-term maintenance of symptom remission and side effects. Here, we provide an overview of the rationale and scientific evidence of the efficacy of neurofeedback in regulating the brain functions in ADHD. We also review the institutional and professional regulation of clinical neurofeedback implementations.

Background MDD patients with abnormal EEG patterns seem more likely to be non-responsive to the antidepressants escitalopram and venlafaxine, but not sertraline, than patients without EEG abnormalities. This finding suggests that patients with both MDD and abnormal EEGs may differentially respond to antidepressant treatment. In the current study, we investigated whether depressed patients with an abnormal EEG show a normalization of the EEG related to antidepressant treatment and response and whether such effect is drug specific, and whether having had early life stress (ELS) increases the chance of abnormal activity. Methods Baseline and week 8 EEGs and depression symptoms were extracted from a large multicenter study (iSPOT-D, n = 1008) where depressed patients were randomized to escitalopram, sertraline, or venlafaxine-XR treatment. We calculated Odds Ratios of EEG normalization and depression response in patients with an abnormal EEG at baseline, comparing sertraline versus other antidepressants. Results Fifty seven patients with abnormal EEGs were included. EEGs did not normalize significantly more with sertraline compared to other antidepressants (OR = 1.9, p = .280). However, patients with a normalized EEG taking sertraline were 5.2 times more likely to respond than subjects taking other antidepressants (p = .019). ELS was not significantly related to abnormal activity. Limitations Neurophysiological recordings were limited in time (two times 2-minute EEGs) and statistical power (n = 57 abnormal EEGs). Conclusions Response rates in patients with normalized EEG taking sertraline were significantly larger than in subjects treated with escitalopram/venlafaxine. This adds to personalized medicine and suggests a possible drug repurposing for sertraline.

Studies have shown that specific networks (default mode network [DMN] and task positive network [TPN]) activate in an anticorrelated manner when sustaining attention. Related EEG studies are scarce and often lack behavioral validation. We performed independent component analysis (ICA) across different frequencies (source-level), using eLORETA-ICA, to extract brain-network activity during resting-state and sustained attention. We applied ICA to the voxel domain, similar to functional magnetic resonance imaging methods of analyses. The obtained components were contrasted and correlated to attentional performance (omission errors) in a large sample of healthy subjects (N = 1397). We identified one component that robustly correlated with inattention and reflected an anticorrelation of delta activity in the anterior cingulate and precuneus, and delta and theta activity in the medial prefrontal cortex and with alpha and gamma activity in medial frontal regions. We then compared this component between optimal and suboptimal attentional performers. For the latter group, we observed a greater change in component loading between resting-state and sustained attention than for the optimal performers. Following the National Institute of Mental Health Research Domain Criteria (RDoC) approach, we prospectively replicated and validated these findings in subjects with attention deficit/hyperactivity disorder. Our results provide further support for the “default mode interference hypothesis.”

After three decades of clinical research on repetitive transcranial magnetic stimulation (rTMS), major depressive disorder (MDD) has proven to be the primary field of application. MDD poses a major challenge for health systems worldwide, emphasizing the need for improving clinical efficacy of existing rTMS applications and promoting the development of novel evidence-based rTMS treatment approaches.

Transcranial direct current stimulation (tDCS) is a non-invasive brain stimulation technique increasingly used to modulate neural activity in the living brain. In order to establish the neurophysiological, cognitive or clinical effects of tDCS, most studies compare the effects of active tDCS to those observed with a sham tDCS intervention. In most cases, sham tDCS consists in delivering an active stimulation for a few seconds to mimic the sensations observed with active tDCS and keep participants blind to the intervention. However, to date, sham-controlled tDCS studies yield inconsistent results, which might arise in part from sham inconsistencies. Indeed, a multiplicity of sham stimulation protocols is being used in the tDCS research field and might have different biological effects beyond the intended transient sensations. Here, we seek to enlighten the scientific community to this possible confounding factor in order to increase reproducibility of neurophysiological, cognitive and clinical tDCS studies.

Introduction Frontal alpha asymmetry (FAA) is a proposed prognostic biomarker in major depressive disorder (MDD), conventionally acquired with electroencephalography (EEG). Although small studies attributed trait-like properties to FAA, a larger sample is needed to reliably asses this characteristic. Furthermore, to use FAA to predict treatment response, determining its stability, including the potential dependency on depressive state or medication, is essential. Methods In the international Study to Predict Optimized Treatment in Depression (iSPOT-D), a multi-center, randomized, prospective open-label trial, 1008 MDD participants were randomized to treatment with escitalopram, sertraline or venlafaxine-extended release. Treatment response was established eight weeks after treatment initiation and resting state EEG was measured both at baseline and after eight weeks (n = 453). Results FAA did not change significantly after eight weeks of treatment (n = 453, p = .234), nor did we find associations with age, sex, depression severity, or change in depression severity. After randomizing females to escitalopram or sertraline, for whom treatment response could be predicted in an earlier study, FAA after eight weeks resulted in equivalent response prediction as baseline FAA (one tailed p = .028). Conclusion We demonstrate that FAA is a stable trait, robust to time, state and pharmacological status. This confirms FAA stability. Furthermore, as prediction of treatment response is irrespective of moment of measurement and use of medication, FAA can be used as a state-invariant prognostic biomarker with promise to optimize MDD treatments.

Daylight is the strongest synchronizer of human circadian rhythms. The circadian pathway hypothesis posits that synchrony between daylight and the circadian system relates to (in)attention. The dopamine neurotransmitter system is implicated in regulating the circadian system as well as in (attention)-deficit hyperactivity disorder [ADHD]. We studied the role of functional genetic variation in the gene encoding of dopamine-receptor-D4 (DRD4) in the relationship between inattention and seasonal daylight (changes). Gene-by-environment (GxE) mega-analyses were performed across eight studies including 3757 adult participants (with and without ADHD). We tested 1) the Spring-focus hypothesis, in which attention in 7R-carriers normalizes with increasing daylight levels preceding measurement, 2) the Summer-born ADHD hypothesis, in which 7R-carriers report more inattention when born in spring/summer than in autumn/winter, 3) the Winter-born ADHD hypothesis, opposing the second hypothesis. The Spring-focus hypothesis was upheld (1386 ADHD, 760 controls; d=-0.16 between periods); 7R-carriers reported even less inattention than 7R-non-carriers after winter solstice (d=0.27 between genotype-groups). Results were diagnosis-independent. Sensitivity analyses at individual study level confirmed the circannual patterns for 7R-carriers. Incorporating geographic changes into the independent measure, we also calculated changes in sunlight levels. This approach likewise showed that inattention correlated negatively with increasing light levels in 7R-carriers (r=-.135). Results emphasize peripheral effects of dopamine and the effects of (seasonal) daylight changes on cognition.

Attention-deficit/hyperactivity disorder (ADHD) is highly associated with the delayed sleep phase disorder, a circadian rhythm sleep-wake disorder, which is prevalent in 73-78% of children and adults with ADHD. Besides the delayed sleep phase disorder, various other sleep disorders accompany ADHD, both in children and in adults. ADHD is either the cause or the consequence of sleep disturbances, or they may have a shared etiological and genetic background. In this review, we present an overview of the current knowledge on the relationship between the circadian rhythm, sleep disorders, and ADHD. We also discuss the various pathways explaining the connection between ADHD symptoms and delayed sleep, ranging from genetics, behavioral aspects, daylight exposure, to the functioning of the eye. The treatment options discussed are focused on improvement of sleep quality, quantity, and phase-resetting, by means of improving sleep hygiene, chronotherapy, treatment of specific sleep disorders, and by strengthening certain neuronal networks involved in sleep, e.g., by sensorimotor rhythm neurofeedback. Ultimately, the main question is addressed: whether ADHD needs to be redefined. We propose a novel view on ADHD, where a part of the ADHD symptoms are the result of chronic sleep disorders, with most evidence for the delayed circadian rhythm as the underlying mechanism. This substantial subgroup should receive treatment of the sleep disorder in addition to ADHD symptom treatment.

Recent evidence points to the increasingly important role of sleep disturbance in ADHD. Circadian phase delay, resulting in delayed sleep onset, has been consistently described with causality implied for a largesubgroup with Attention Deficit Hyperactivity Disorder (ADHD).The likelihood of varied and numerous causations in ADHD, the high prevalence of sleep disorders and the likely etiological/pathogenetic role of sleep disorders for a large subgroup with ADHD encourages a personalizedmedicine approach, particularly by assessing sleep and identifying biomarkers to assist in identifying subgroups which can enable a more personalizedtreatment.Psychostimulants are the mainstay of pharmacological treatment of ADHD, but do not assist sleep problems and can in fact exacerbate them. In a large subgroup with ADHD, psycho-education and sleep hygiene, CBTi and chronotherapy also have an important role to play in treating ADHD symptoms associated with sleep disturbance. Neurofeedback (operant conditioning of EEG), may have specific and lasting effects on sleep, and in turn ADHD symptoms, with the effect shown to be mediated via the normalizationof sleep.This review article summariesand reports on some of the accumulating evidence for the role of sleep in ADHD and outlines various methods for assessment and intervention.

Traditionele behandelingen voor ADHD hebben be­perkingen op het gebied van effectiviteit, langetermijneffecten en bij­werkingen. In dit artikel geven we een overzicht van belangrijke as­pecten van neurofeedback bij ADHD en illustreren de huidige evidentie van neurofeedback als behandelingsoptie. Behandelingen met standaardneurofeedbackprotocollen kunnen op basis van ver­schillende meta­analyses als werkzaam en specifiek worden be­schouwd. Verder bespreken we de huidige ongereguleerde praktische implementatie van neurofeedback en benadrukken de behoefte aan gedegen opleidingen voor beoefenaars, bindende standaarden voor protocollen en regulering van neurofeedbacktoepassingen. We con­cluderen dat standaardneurofeedbackprotocollen bij ADHD als een effectief behandelingsalternatief kunnen worden beschouwd met gunstige langetermijneffecten en dat verdere studies zich kunnen richten op het onderzoeken van de specifieke werkingsmechanismen van deze standaardprotocollen.

Using deep learning in clinical practice is a big step towards personalized, improved treatment. As a proof of concept, we previously succesfully classi ed resting-state electro-encepalograpies (EEG’s) as belonging to female or male participants using a convolutional neural network (CNN) model in a ground truth scenario1 with 83% accuracy. Such a network usually needs a generous amount of data to perform well. We investigated the minimal amount of data needed to achieve an optimal sex classi cation result with this CNN model. Additionally, we investigated the performance a CNN model on clinically more relevant (EEG) brain activity. In a previous study, it was observed that ~10-30% of our ADHD patient population shows frontal beta-spindles in resting-state EEG, which is associated with insomnia (sleep-main- tenance) and impulse control problems2. SInce this is a contraindication for theta/beta neurofeedback therapy, a classi cation algorithm could help de ne for each in- dividual patient if such a therapy is suitable.

EEG biomarkers have shown promise in predicting non-response to stimulant medication in ADHD and could serve as translational biomarkers. This study aimed to replicate and extend previous EEG biomarkers. The international Study to Predict Optimized Treatment for ADHD (iSPOT-A), a multi-center, international, prospective open-label trial, enrolled 336 children and adolescents with ADHD (11.9 yrs; 245 males; prescribed methylphenidate) and 158 healthy children. Treatment response was established after six weeks using the clinician rated ADHD-Rating Scale-IV. Theta/Beta ratio (TBR) and alpha peak frequency (APF) were assessed at baseline as predictors for treatment outcome. No differences between ADHD and controls were found for TBR and APF. 62% of the ADHD group was classified as a responder. Responders did not differ from non-responders in age, medication dosage, and baseline severity of ADHD symptoms. Male-adolescent non-responders exhibited a low frontal APF (Fz: R = 9.2 Hz vs. NR = 8.1 Hz; ES = 0.83), whereas no effects were found for TBR. A low APF in male adolescents was associated with non-response to methylphenidate, replicating earlier work. Our data suggest that the typical maturational EEG changes observed in ADHD responders and controls are absent in non-responders to methylphenidate and these typical changes start emerging in adolescence. Clinical trials registration: www.clinicaltrials.gov; NCT00863499 (https://clinicaltrials.gov/ct2/show/NCT00863499).

We have excellent skills to extract sex from visual assessment of human faces, but assessing sex from human brain rhythms seems impossible. Using deep convolutional neural networks, with unique potential to find subtle differences in apparent similar patterns, we explore if brain rhythms from either sex contain sex specific information. Here we show, in a ground truth scenario, that a deep neural net can predict sex from scalp electroencephalograms with an accuracy of >80% (p < 10-5), revealing that brain rhythms are sex specific. Further, we extracted sex-specific features from the deep net filter layers, showing that fast beta activity (20-25 Hz) and its spatial distribution is a main distinctive attribute. This demonstrates the ability of deep nets to detect features in spatiotemporal data unnoticed by visual assessment, and to assist in knowledge discovery. We anticipate that this approach may also be successfully applied to other specialties where spatiotemporal data is abundant, including neurology, cardiology and neuropsychology.

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.

Electroconvulsive therapy (ECT) is an effective treatment for severe depression. Electroencephalogram (EEG) measures between ECT sessions seem to be related to the antidepressant efficacy of ECT. In this naturalistic cohort study, we examine longitudinal effects of ECT on interhemispheric EEG coherence measures during seizure activity and its relation to the antidepressant efficacy.

The causal influence of cortico-subcortical connectivity by means of brain stimulation seems to be an effective biological treatment in psychiatric patients.

The event-related P3 potential, as elicited in auditory signal detection tasks, originates from neural activity of multiple cortical structures and presumably reflects an overlap of several cognitive processes. The fact that the P3 is affected by aging makes it a potential metric for age-related cognitive change. The P3 in older participants is thought to encompass frontal compensatory activity in addition to task-related processes. The current study investigates this by decomposing the P3 using group independent component analysis (ICA). Independent components (IC) of young and old participants were compared in order to investigate the effects of aging. Exact low-resolution tomography analysis (eLORETA) was used to compare current source densities between young and old participants for the P3-ICs to localize differences in cortical source activity for every IC. One of the P3-related ICs reflected a different constellation of cortical generators in older participants compared to younger participants, suggesting that this P3-IC reflects shifts in neural activations and compensatory processes with aging. This P3-IC was localized to the orbitofrontal/temporal, and the medio-parietal regions. For this IC, older participants showed more frontal activation and less parietal activation as measured on the scalp. The differences in cortical sources were localized in the precentral gyrus and the parahippocampal gyrus. This finding might reflect compensatory activity recruited from these cortical sources during a signal detection task.

Rationale. Limited research is available on electrophysiological abnormalities such as epileptiform EEG or EEG slowing in depression and its association with antidepressant treatment response. Objectives. We investigated the association between EEG abnormalities and antidepressant treatment response in the international Study to Predict Optimized Treatment in Depression (iSPOT-D). Methods. Of 1008 participants with major depressive disorder randomized to escitalopram, sertraline, or venlafaxine-XR, 622 completed 8 weeks of treatment per protocol. The study also recruited 336 healthy controls. Treatment response was established after 8 weeks using the 17-item Hamilton Rating Scale for Depression (HRSD17). The resting-state EEG was assessed at baseline with eyes closed. EEG abnormalities including epileptiform activity, EEG slowing, and alpha peak frequency (APF) were scored for all subjects, blind to treatment outcome. Results. Patients and controls did not differ in the occurrence of EEG abnormalities. Furthermore, in the per protocol sample the occurrence of epileptiform EEG and EEG slowing (as a combined marker) were associated with a reduced likelihood of responding to escitalopram (P = .019; odds ratio [OR] = 3.56) and venlafaxine-XR (P = .043; OR = 2.76), but not sertraline (OR = 0.73). The response rates for this “any EEG abnormality” groups versus the “no-abnormality” group were 33% and 64% for escitalopram and 41% and 66% for venlafaxine-XR, respectively. A slow APF was associated with treatment response only in the sertraline group (P = .21; d = .027). Conclusions. EEG abnormalities are associated with nonresponse to escitalopram and venlafaxine-XR, but not sertraline, whereas a slow APF is associated to response for sertraline only.

Antidepressant medication is the most common treatment for major depressive disorder (MDD), however, the precise working mechanism underlying these treatments remains unclear. Recent neuromodulation treatments demonstrate that direct stimulation of the dorsolateral prefrontal cortex (DLPFC), dorsomedial prefrontal cortex (DMPFC), and subgenual anterior cingulate (sgACC) relate to clinical improvement, suggesting connectivity alterations of the DLPFC-DMPFC-sgACC network to mediate antidepressant response. The international Study to Predict Optimized Treatment in Depression (iSPOT-D) is an international multicentre study that collected EEG data for 1008 MDD patients, randomized to 3 different antidepressant medications (N=447 MDD with complete pre- and post-treatment data and N=336 non-MDD). Treatment response was defined by a decline of >50% on the Hamilton Rating Score for Depression (HRSD17). We investigated whether connectivity in alpha and theta frequencies of the DLPFC-DMPFC-sgACC network changed from pre- to post-treatment between: (i) patients and controls, and (ii) responders (R) and non-responders (NR). Women exhibited higher alpha and theta connectivity compared to males, both pre- and post-treatment. Furthermore, theta, but not alpha, hypo-connectivity was found for MDD patients. A decreased alpha connectivity after treatment was found only for male responders, while non-responders and females exhibited no changes in alpha connectivity. Decreasing alpha connectivity could potentially serve as a treatment emergent biomarker, in males only. Furthermore, it could be useful to a priori stratify by gender for future MDD studies.

Frontal alpha asymmetry (FAA) has frequently been reported as potential discriminator between depressed and healthy individuals, although contradicting results have been published. The aim of the current study was to provide an up to date meta-analysis on the diagnostic value of FAA in major depressive disorder (MDD) and to further investigate discrepancies in a large cross-sectional dataset.

Given that many studies suggest a role of DLPFC-sgACC connectivity in depression and prior research demonstrating that neuromodulation of either of these nodes modulates parasympathetic activity and results in a heart rate deceleration, a new method is proposed to individualize localization of the DLPFC. This can, among others, be useful for rTMS treatment of depression.

There is a growing interest in the application of psychophysiological signals in more applied settings. Unidirectional sensory motor rhythm-training (SMR) has demonstrated consistent effects on sleep. In this study the main aim was to analyze to what extent participants could gain voluntary control over sleep-related parameters and secondarily to assess possible influences of this training on sleep metrics. Bidirectional training of SMR as well as heart rate variability (HRV) was used to assess the feasibility of training these parameters as possible brain computer interfaces (BCI) signals, and assess effects normally associated with unidirectional SMR training such as the influence on objective and subjective sleep parameters. Participants (n = 26) received between 11 and 21 training sessions during 7 weeks in which they received feedback on their personalized threshold for either SMR or HRV activity, for both up- and down regulation. During a pre- and post-test a sleep log was kept and participants used a wrist actigraph. Participants were asked to take an afternoon nap on the first day at the testing facility. During napping, sleep spindles were assessed as well as self-reported sleep measures of the nap. Although the training demonstrated successful learning to increase and decrease SMR and HRV activity, no effects were found of bidirectional training on sleep spindles, actigraphy, sleep diaries, and self-reported sleep quality. As such it is concluded that bidirectional SMR and HRV training can be safely used as a BCI and participants were able to improve their control over physiological signals with bidirectional training, whereas the application of bidirectional SMR and HRV training did not lead to significant changes of sleep quality in this healthy population.

Nonlinear analysis of EEG recordings allows detection of characteristics that would probably be neglected by linear methods. This study aimed to determine a suitable epoch length for nonlinear analysis of EEG data based on its recurrence rate in EEG alpha activity (electrodes Fz, Oz, and Pz) from 28 healthy and 64 major depressive disorder subjects. Two nonlinear metrics, Lempel-Ziv complexity and scaling index, were applied in sliding windows of 20 seconds shifted every 1 second and in nonoverlapping windows of 1 minute. In addition, linear spectral analysis was carried out for comparison with the nonlinear results. The analysis with sliding windows showed that the cortical dynamics underlying alpha activity had a recurrence period of around 40 seconds in both groups. In the analysis with nonoverlapping windows, long-term nonstationarities entailed changes over time in the nonlinear dynamics that became significantly different between epochs across time, which was not detected with the linear spectral analysis. Findings suggest that epoch lengths shorter than 40 seconds neglect information in EEG nonlinear studies. In turn, linear analysis did not detect characteristics from long-term nonstationarities in EEG alpha waves of control subjects and patients with major depressive disorder patients. We recommend that application of nonlinear metrics in EEG time series, particularly of alpha activity, should be carried out with epochs around 60 seconds. In addition, this study aimed to demonstrate that long-term nonlinearities are inherent to the cortical brain dynamics regardless of the presence or absence of a mental disorder.

Repetitive transcranial magnetic stimulation (rTMS) is considered an efficacious non-invasive neuromodulation treatment for major depressive disorder (MDD). However, little is known about the clinical outcome of combined rTMS and psychotherapy (rTMS + PT). Through common neurobiological brain mechanisms, rTMS + PT may exert enhanced antidepressant effects compared to the respective monotherapies.

Background Repetitive transcranial magnetic stimulation (rTMS) is a promising augmentation strategy for treatment-refractory OCD. However, a substantial group still fails to respond. Sleep disorders, e.g. circadian rhythm sleep disorders (CRSD), are highly prevalent in OCD and might mediate treatment response. The aims of the current study were to compare sleep disturbances between OCD patients and healthy subjects as well as between rTMS responders and non-responders, and most importantly to determine sleep-related predictors of rTMS non-response. Methods 22 OCD patients received at least 10 sessions rTMS combined with psychotherapy. Sleep disturbances were measured using questionnaires and actigraphy. Sleep in patients was compared to healthy subjects. Treatment response was defined as >35% reduction on YBOCS. Treatment response prediction models were based on measures of CRSD and insomnia. Results Sleep disturbances were more prevalent in OCD patients than healthy subjects. The OCD group consisted of 12 responders and 10 non-responders. The CRSD model could accurately predict non-response with 83% sensitivity and 63% specificity, whereas the insomnia model could not. Conclusions CRSD is more prevalent in OCD patients than healthy subjects, specifically in rTMS non-responders. Therefore, CRSD may serve as a biomarker for different subtypes of OCD corresponding with response to specific treatment approaches.

Arousal systems are one of the recently announced NIMH Research Domain Criteria to inform future diagnostics and treatment prediction. In major depressive disorder (MDD), altered central nervous system (CNS) wakefulness regulation and an increased sympathetic autonomic nervous system (ANS) activity have been identified as biomarkers with possible discriminative value for prediction of antidepressant treatment response. Therefore, the hypothesis of a more pronounced decline of CNS and ANS-arousal being predictive for a positive treatment outcome to selective-serotonin-reuptake-inhibitor (SSRI) treatment was derived from a small, independent exploratory dataset (N = 25) and replicated using data from the randomized international Study to Predict Optimized Treatment Response in Depression (iSPOT-D). There, 1008 MDD participants were randomized to either a SSRI (escitalopram or sertraline) or a serotonin-norepinephrine-reuptake-inhibitor (SNRI-venlafaxine) arm. Treatment response was established after eight weeks using the 17-item Hamilton Rating Scale for Depression. CNS-arousal (i.e. electroencephalogram-vigilance), ANS-arousal (heart rate) and their change across time were assessed during rest. Responders and remitters to SSRI treatment were characterized by a faster decline of CNS-arousal during rest whereas SNRI responders showed a significant increase of ANS-arousal. Furthermore, SSRI responders/remitters showed an association between ANS- and CNS-arousal regulation in comparison to non-responders/non-remitters while this was not the case for SNRI treatment arm. Since positive treatment outcome to SSRI and SNRI was linked to distinct CNS and ANS-arousal profiles, these predictive markers probably are not disorder specific alterations but reflect the responsiveness of the nervous system to specific drugs.

Neuropsychiatric EEG-Based ADHD Assessment Aid (NEBA) is an EEG-based device designed to aid in the diagnostic process for ADHD by identifying individuals less likely to have ADHD by virtue of a lower theta/beta ratio. In using NEBA as an example, the Arns et al. commentary misstates the purpose of NEBA, which is to widen the differential rather than to make the diagnosis. Arns et al. caution about missing an ADHD diagnosis, but fail to mention the impact of overdiagnosis. If we are to advance our knowledge of the etiology and pathophysiology of ADHD, as well as develop tailored treatments and ultimately improve outcomes for ADHD, then biomarkers and objective assessment aids such as NEBA are needed to improve and refine diagnostic accuracy beyond symptom description and clinical history.

Recently several new tests have received US Federal Drug Administration (FDA) marketing approval as aids in the diagnostic process for attention deficit hyperactivity disorder (ADHD), including the Neuropsychiatric electroencephalogram (EEG)-Based ADHD Assessment Aid (NEBA) Health test. The NEBA test relies upon an EEG-based measure, called the theta to beta ratio (TBR). Although this measure has yielded large differences between ADHD and non-ADHD groups in studies prior to 2009, recent studies and a meta-analysis could not replicate these findings. In this article, we have used the NEBA device as an exemplar for a discussion that distinguishes between FDA de novo marketing approval for a device and any claims that that device is empirically supported, scientifically validated with replicated findings. It is understood that the aims of each differ; however, for many, including the lay public as well as some mental health professionals, these terms may be confused and treated as though they are synonymous. With regard to the TBR measure, there is no reliable association or replication for its clinical usage in the ADHD diagnostic process. The recommendation for potential consumers of the NEBA Health test (as well as perhaps for other existing FDA-approved diagnostic tests) is caveat emptor (let the buyer beware!).

Objective: To determine whether EEG occipital alpha and frontal alpha asymmetry (FAA) distinguishes outpatients with major depression (MDD) from controls, predicts antidepressant treatment outcome, and to explore the role of gender. Methods: In the international Study to Predict Optimized Treatment in Depression (iSPOT-D), a multi-center, randomized, prospective open-label trial, 1008 MDD participants were randomized to esc-italopram, sertraline or venlafaxine-extended release. The study also recruited 336 healthy controls. Treatment response was established after eight weeks and resting EEG was measured at baseline (two minutes eyes open and eyes closed). Results: No differences in EEG alpha for occipital and frontal cortex, or for FAA, were found in MDD par-ticipants compared to controls. Alpha in the occipital and frontal cortex was not associated with treat-ment outcome. However, a gender and drug-class interaction effect was found for FAA. Relatively greater right frontal alpha (less cortical activity) in women only was associated with a favorable response to the Selective Serotonin Reuptake Inhibitors escitalopram and sertraline. No such effect was found for venlafaxine-extended release.

Objective We performed meta-analyses of randomized controlled trials to examine the effects of neurofeedback on attention-deficit/hyperactivity disorder (ADHD) symptoms and neuropsychological deficits in children and adolescents with ADHD. Method We searched PubMed, Ovid, Web of Science, ERIC, and CINAHAL through August 30, 2015. Random-effects models were employed. Studies were evaluated with the Cochrane Risk of Bias tool. Results We included 13 trials (520 participants with ADHD). Significant effects were found on ADHD symptoms rated by assessors most proximal to the treatment setting, that is, the least blinded outcome measure (standardized mean difference [SMD]: ADHD total symptoms = 0.35, 95% CI = 0.11−0.59; inattention = 0.36, 95% CI = 0.09−0.63; hyperactivity/impulsivity = 0.26, 95% CI = 0.08−0.43). Effects were not significant when probably blinded ratings were the outcome or in trials with active/sham controls. Results were similar when only frequency band training trials, the most common neurofeedback approach, were analyzed separately. Effects on laboratory measures of inhibition (SMD = 0.30, 95% CI = −0.10 to 0.70) and attention (SMD = 0.13, 95% CI = −0.09 to 0.36) were not significant. Only 4 studies directly assessed whether learning occurred after neurofeedback training. The risk of bias was unclear for many Cochrane Risk of Bias domains in most studies. Conclusion Evidence from well-controlled trials with probably blinded outcomes currently fails to support neurofeedback as an effective treatment for ADHD. Future efforts should focus on implementing standard neurofeedback protocols, ensuring learning, and optimizing clinically relevant transfer.