Aberrant Modulation of Brain Oscillatory Activity and Attentional Impairment in Attention-Deficit/Hyperactivity Disorder

Analysis of BoDV-1 status, EEG resting-state alpha activity and pro-inflammatory cytokines in adults with and without major depressive disorder

Introduction

In severe cases, an infection with the Borna Disease Virus 1 (BoDV-1), the causative agent of Borna disease in horses, sheep, and other domestic mammals, was reported to be accompanied by cognitive dysfunctions, seizures, deep coma, or severe to fatal encephalitis in humans. In addition, asymptomatic or mild courses of BoDV-1 infection are discussed to act as a co-factor in the etiology of Major Depressive Disorder (MDD). Previously, studies using electroencephalography (EEG) reported BoDV-1-dependent changes in event-related potentials (ERPs), thus indicating the use and added value of non-invasive studies in Borna research.

Methods

Here, we examined possible connections between BoDV-1 status, EEG restingstate alpha activity, and serum levels of pro-inflammatory Interleukin 6 (IL-6) and Interleukin 8 (IL-8) in MDD patients and in a comparison group of adults without MDD diagnosis.

Results

Interestingly, for both groups, we revealed a comparable high number of BoDV-1 positive and BoDV-1 negative participants. Compared to adults without MDD diagnosis, MDD patients showed a decrease in their relative EEG alpha power at posterio-central, but increased values at anterio-central electrode sites. Most important, no group-dependent effect of BoDV-1 status on EEG resting-state activity had been observed. Compared to BoDV-1 positive and negative adults without MDD diagnosis, as well as BoDV-1 positive MDD patients, BoDV-1 negative MDD patients revealed a comparatively weak significant negative correlation between relative fronto-central EEG alpha power and concentrations of pro-inflammatory IL-8.

Discussion

Taken together, our data confirm MDD-dependent alterations in EEG resting-state alpha activity, which, however, were not accompanied by major BoDV-1 dependent neurophysiological or immunological effects. Future - probably more invasive - studies further have to clarify the significance of the observed negative correlation between relative fronto-central EEG alpha power and concentrations of pro-inflammatory IL-8.

Where do neurodevelopmental conditions fit in transdiagnostic psychiatric frameworks? Incorporating a new neurodevelopmental spectrum

Features of autism spectrum disorder, attention-deficit/hyperactivity disorder, learning disorders, intellectual disabilities, and communication and motor disorders usually emerge early in life and are associated with atypical neurodevelopment. These "neurodevelopmental conditions" are grouped together in the DSM-5 and ICD-11 to reflect their shared characteristics. Yet, reliance on categorical diagnoses poses significant challenges in both research and clinical settings (e.g., high co-occurrence, arbitrary diagnostic boundaries, high within-disorder heterogeneity). Taking a transdiagnostic dimensional approach provides a useful alternative for addressing these limitations, accounting for shared underpinnings across neurodevelopmental conditions, and characterizing their common co-occurrence and developmental continuity with other psychiatric conditions. Neurodevelopmental features have not been adequately considered in transdiagnostic psychiatric frameworks, although this would have fundamental implications for research and clinical practices. Growing evidence from studies on the structure of neurodevelopmental and other psychiatric conditions indicates that features of neurodevelopmental conditions cluster together, delineating a "neurodevelopmental spectrum" ranging from normative to impairing profiles. Studies on shared genetic underpinnings, overlapping cognitive and neural profiles, and similar developmental course and efficacy of support/treatment strategies indicate the validity of this neurodevelopmental spectrum. Further, characterizing this spectrum alongside other psychiatric dimensions has clinical utility, as it provides a fuller view of an individual's needs and strengths, and greater prognostic utility than diagnostic categories. Based on this compelling body of evidence, we argue that incorporating a new neurodevelopmental spectrum into transdiagnostic frameworks has considerable potential for transforming our understanding, classification, assessment, and clinical practices around neurodevelopmental and other psychiatric conditions.

Applications of OPM-MEG for translational neuroscience: a perspective

Magnetoencephalography (MEG) allows the non-invasive measurement of brain activity at millisecond precision combined with localization of the underlying generators. So far, MEG-systems consisted of superconducting quantum interference devices (SQUIDS), which suffer from several limitations. Recent technological advances, however, have enabled the development of novel MEG-systems based on optically pumped magnetometers (OPMs), offering several advantages over conventional SQUID-MEG systems. Considering potential improvements in the measurement of neuronal signals as well as reduced operating costs, the application of OPM-MEG systems for clinical neuroscience and diagnostic settings is highly promising. Here we provide an overview of the current state-of-the art of OPM-MEG and its unique potential for translational neuroscience. First, we discuss the technological features of OPMs and benchmark OPM-MEG against SQUID-MEG and electroencephalography (EEG), followed by a summary of pioneering studies of OPMs in healthy populations. Key applications of OPM-MEG for the investigation of psychiatric and neurological conditions are then reviewed. Specifically, we suggest novel applications of OPM-MEG for the identification of biomarkers and circuit deficits in schizophrenia, dementias, movement disorders, epilepsy, and neurodevelopmental syndromes (autism spectrum disorder and attention deficit hyperactivity disorder). Finally, we give an outlook of OPM-MEG for translational neuroscience with a focus on remaining methodological and technical challenges.

Role of visual brainwave entrainment on the resting state brainwaves of children with and without attention-deficit/hyperactivity disorder

The relationship between brainwave oscillations and Attention-Deficit/Hyperactivity Disorder (ADHD)-related cognitive challenges is a trending proposition in the field of Cognitive Neuroscience. Studies suggest the role of brainwave oscillations in the symptom expressions of ADHD-diagnosed children. Intervention studies have further suggested the scope of brain stimulation techniques in improving cognition. The current manuscript explored the effect of changes in the brainwaves post-sensory entrainment on cognitive performance of children. We calculated each participant's brainwave difference and ratios of theta, alpha, and beta power after the entrainment sessions. Further, we explored possible correlations between these values and the psychometric scores. The beta resting state showed the strongest association with selective attention performance of all participants. Theta-beta ratio (TBR) showed an inverse correlation with selective attention and working memory performances. The theta frequency was associated with decreased working performance in children without ADHD. Our findings also suggest a predominant role of TBR than the theta-alpha ratio in determining the cognitive performance of children with ADHD. The individual differences in the entrainment reception were attributed to the participant's age, IQ, and their innate baseline frequencies. The implications of our findings can initiate substantiating brainwave-based entrainment sessions as a therapeutic modality to improve cognition among children.

The detect consensus report on Attention Deficit/Hyperactivity Disorder and its management among Turkish children and adolescents (Detect: consensus report on ADHD among Turkish youth)

Attention Deficit/Hyperactivity Disorder (ADHD) is one of the most common and heritable neurodevelopmental disorders which may last through the life-span. A consensus report on diagnosis and management of ADHD among Turkish youth was prepared previously. However, the participants as well as the management options were rather limited and developments in the past decade necessitated a revision and update of the consensus. Therefore, this review aims to summarize the consensus among Child and Adolescent Psychiatrists from Türkiye on the nature and management of pediatric ADHD. For those aims, the etiology of ADHD, diagnostic and evaluation process, epidemiology, developmental presentations, differential diagnoses and comorbidities, course/outcome and pharmacological as well as non-pharmacological management options were reviewed and suggestions for clinical practice are presented. Since ADHD is a chronic disorder with wide-ranging effects on functionality that is frequently accompanied by other mental disorders, a multidimensional therapeutic approach is recommended. However, since the disorder has neurobiological basis, pharmacotherapy represents the mainstay of treatment. Additional therapies may include psychosocial therapy, behavioral therapy, school-based therapeutic approaches, and family education. This review provides recommendations for ADHD at the national and global levels. It contains information about ADHD that will contribute to and facilitate clinicians' decision-making processes. It is advisable to consider this guideline in clinical practice.

Alpha/beta-gamma decoupling in methylphenidate medicated ADHD patients

There is much interest to understand how different neural rhythms function, interact and are regulated. Here, we focus on WM delay gamma to investigate its coupling with alpha/beta rhythms and its neuromodulation by methylphenidate. We address this through the use of human EEG conducted in healthy and ADHD subjects which revealed ADHD-specific electrophysiological deficits and MPH-induced normalization of gamma amplitude and its coupling with alpha/beta rhythms. Decreased alpha/beta-gamma coupling is known to facilitate memory representations via disinhibition of gamma ensembles coding the maintained stimuli. Here, we present EEG evidence which suggests that these dynamics are sensitive to catecholaminergic neuromodulation. MPH decreased alpha/beta-gamma coupling and this was related to the increase in delay-relevant gamma activity evoked by the same drug. These results add further to the neuromodulatory findings that reflect an electrophysiological dimension to the well-known link between WM delay and catecholaminergic transmission.

Neuronal Correlates of Task Irrelevant Distractions Enhance the Detection of Attention Deficit/Hyperactivity Disorder

Early diagnosis and treatment can reduce the symptoms of Attention Deficit/Hyperactivity Disorder (ADHD) in children, but medical diagnosis is usually delayed. Hence, it is important to increase the efficiency of early diagnosis. Previous studies used behavioral and neuronal data during GO/NOGO task to help detect ADHD and the accuracy differed considerably from 53% to 92%, depending on the employed methods and the number of electroencephalogram (EEG) channels. It remains unclear whether data from a few EEG channels can still lead to a good accuracy of detecting ADHD. Here, we hypothesize that introducing distractions into a VR-based GO/NOGO task can augment the detection of ADHD using 6-channel EEG because children with ADHD are easily distracted. Forty-nine ADHD children and 32 typically developing children were recruited. We use a clinically applicable system with EEG to record data. Statistical analysis and machine learning methods were employed to analyze the data. The behavioral results revealed significant differences in task performance when there are distractions. The presence of distractions leads to EEG changes in both groups, indicating immaturity in inhibitory control. Importantly, the distractions additionally enhanced the between-group differences in NOGO $\alpha $ and $\gamma $ power, reflecting insufficient inhibition in different neural networks for distraction suppression in the ADHD group. Machine learning methods further confirmed that distractions enhance the detection of ADHD with an accuracy of 85.45%. In conclusion, this system can assist in fast screenings for ADHD and the findings of neuronal correlates of distractions can help design therapeutic strategies.

Dorsal-to-ventral imbalance in the superior longitudinal fasciculus mediates methylphenidate's effect on beta oscillations in ADHD

While pharmacological treatment with methylphenidate (MPH) is a first line intervention for ADHD, its mechanisms of action have yet to be elucidated. We here seek to identify the white matter tracts that mediate MPH's effect on beta oscillations. We implemented a double-blind placebo-controlled crossover design, where boys diagnosed with ADHD underwent behavioral and MEG measurements during a spatial attention task while on and off MPH. The results were compared with an age/IQ-matched control group. Estimates of white matter tracts were obtained using diffusion tensor imaging (DTI). Via a stepwise model selection strategy, we identified the fiber tracts (regressors) significantly predicting values of the dependent variables of interest (i.e., oscillatory power, behavioral performance, and clinical symptoms): the anterior thalamic radiation (ATR), the superior longitudinal fasciculus ("parietal endings") (SLFp), and superior longitudinal fasciculus ("temporal endings") (SLFt). ADHD symptoms severity was associated with lower fractional anisotropy (FA) within the ATR. In addition, individuals with relatively higher FA in SLFp compared to SLFt, led to stronger behavioral effects of MPH in the form of faster and more accurate responses. Furthermore, the same parietotemporal FA gradient explained the effects of MPH on beta modulation: subjects with ADHD exhibiting higher FA in SLFp compared to SLFt also displayed greater effects of MPH on beta power during response preparation. Our data suggest that the behavioral deficits and aberrant oscillatory modulations observed in ADHD depend on a possibly detrimental structural connectivity imbalance within the SLF, caused by a diffusivity gradient in favor of parietal rather than temporal, fiber tracts.

Electrophysiological and behavioral correlates of cannabis use disorder

Current research indicates deficits in cognitive function together with widespread changes in brain activity following long-term cannabis use. In particular, cannabis use has been associated with excessive spectral power of the alpha rhythm (8-12 Hz), which is also known to be modulated during attentional states. Recent neuroimaging studies have linked heavy cannabis use with structural and metabolic changes in the brain; however, the functional consequences of these changes are still not fully characterized. This study investigated the electrophysiological and behavioral correlates of cannabis dependence by comparing patients with a cannabis use disorder (CUD; N = 24) with cannabis nonuser controls (N = 24), using resting state electroencephalogram (EEG) source-imaging. In addition to evaluating mean differences between groups, we also explored whether particular EEG patterns were associated with individual cognitive-behavioral measures. First, we replicated historical findings of elevated levels of (relative) alpha rhythm in CUD patients compared with controls and located these abnormalities to mainly prefrontal cortical regions. Importantly, we observed a significant negative correlation between alpha spectral power in several cortical regions and individual attentional performance in the Go/NoGo task. Because such relationship was absent in the nonuser control group, our results suggest that reduced prefrontal cortical activation (indexed by increased relative alpha power) could be partly responsible for the reported cognitive impairments in CUD. Our findings support the use of electroencephalography as a noninvasive and cost-effective tool for biomarker discovery in substance abuse and have the potential of directly informing future intervention strategies.

What Has Been Learned from Using EEG Methods in Research of ADHD?

Electrophysiological recording methods, including electroencephalography (EEG) and magnetoencephalography (MEG), have an unparalleled capacity to provide insights into the timing and frequency (spectral) composition of rapidly changing neural activity associated with various cognitive processes. The current chapter provides an overview of EEG studies examining alterations in brain activity in ADHD, measured both at rest and during cognitive tasks. While EEG resting state studies of ADHD indicate no universal alterations in the disorder, event-related studies reveal consistent deficits in attentional and inhibitory control and consequently inform the proposed cognitive models of ADHD. Similar to other neuroimaging measures, EEG research indicates alterations in multiple neural circuits and cognitive functions. EEG methods - supported by the constant refinement of analytic strategies - have the potential to contribute to improved diagnostics and interventions for ADHD, underlining their clinical utility.

Reduced Power in Fronto-Parietal Theta EEG Linked to Impaired Attention-Sampling in Adult ADHD

Attention-deficit/hyperactivity disorder (ADHD) in adults is understudied, especially regarding neural mechanisms such as oscillatory control of attention sampling. We report an electroencephalography (EEG) study of such cortical mechanisms, in ADHD-diagnosed adults during administration of Test of Variables of Attention (TOVA), a gold-standard continuous performance test for ADHD that measures the ability to sustain attention and inhibit impulsivity. We recorded 53 adults (28 female, 25 male, aged 18-60), and 18 matched healthy controls, using 128-channel EEG. We analyzed sensor-space features established as neural correlates of attention: timing-sensitivity and phase-synchrony of response activations, and event-related (de)synchronization (ERS/D) of α and θ frequency band activity; in frontal and parietal scalp regions. TOVA test performance significantly distinguished ADHD adults from neurotypical controls, in commission errors, response time variability (RTV) and d' (response sensitivity). The ADHD group showed significantly weaker target-locked and response-locked amplitudes, that were strongly right-lateralized at the N2 wave, and weaker phase synchrony (longer reset poststimulus). They also manifested significantly less parietal prestimulus 8-Hz θ ERS, less frontal and parietal poststimulus 4-Hz θ ERS, and more frontal and parietal prestimulus α ERS during correct trials. These differences may reflect excessive modulation of endogenous activity by strong entrainment to stimulus (α), combined with deficient modulation by neural entrainment to task (θ), which in TOVA involves monitoring stimulus spatial location (not predicted occurrence onset which is regular and task-irrelevant). Building on the hypotheses of θ coding for relational structure and rhythmic attention sampling, our results suggest that ADHD adults have impaired attention sampling in relational categorization tasks.

Disrupted Functional Rich-Club Organization of the Brain Networks in Children with Attention-Deficit/Hyperactivity Disorder, a Resting-State EEG Study

Growing evidence indicates that disruptions in the brain's functional connectivity play an important role in the pathophysiology of ADHD. The present study investigates alterations in resting-state EEG source connectivity and rich-club organization in children with inattentive (ADHDI) and combined (ADHDC) ADHD compared with typically developing children (TD) under the eyes-closed condition. EEG source analysis was performed by eLORETA in different frequency bands. The lagged phase synchronization (LPS) and graph theoretical metrics were then used to examine group differences in the topological properties and rich-club organization of functional networks. Compared with the TD children, the ADHDI children were characterized by a widespread significant decrease in delta and beta LPS, as well as increased theta and alpha LPS in the left frontal and right occipital regions. The ADHDC children displayed significant increases in LPS in the central, temporal and posterior areas. Both ADHD groups showed small-worldness properties with significant increases and decreases in the network degree in the θ and β bands, respectively. Both subtypes also displayed reduced levels of network segregation. Group differences in rich-club distribution were found in the central and posterior areas. Our findings suggest that resting-state EEG source connectivity analysis can better characterize alterations in the rich-club organization of functional brain networks in ADHD patients.

Effects of context on the neural correlates of attention in a college classroom

Activities that are effective in supporting attention have the potential to increase opportunities for student learning. However, little is known about the impact of instructional contexts on student attention, in part due to limitations in our ability to measure attention in the classroom, typically based on behavioral observation and self-reports. To address this issue, we used portable electroencephalography (EEG) measurements of neural oscillations to evaluate the effects of learning context on student attention. The results suggest that attention, as indexed by lower alpha power as well as higher beta and gamma power, is stronger during student-initiated activities than teacher-initiated activities. EEG data revealed different patterns in student attention as compared to standardized coding of attentional behaviors. We conclude that EEG signals offer a powerful tool for understanding differences in student cognitive states as a function of classroom instruction that are unobservable from behavior alone.

Neurocognitive subprocesses of working memory performance

Working memory (WM) has been defined as the active maintenance and flexible updating of goal-relevant information in a form that has limited capacity and resists interference. Complex measures of WM recruit multiple subprocesses, making it difficult to isolate specific contributions of putatively independent subsystems. The present study was designed to determine whether neurophysiological indicators of proposed subprocesses of WM predict WM performance. We recruited 200 individuals defined by care-seeking status and measured neural responses using electroencephalography (EEG), while participants performed four WM tasks. We extracted spectral and time-domain EEG features from each task to quantify each of the hypothesized WM subprocesses: maintenance (storage of content), goal maintenance, and updating. We then used EEG measures of each subprocess as predictors of task performance to evaluate their contribution to WM. Significant predictors of WM capacity included contralateral delay activity and frontal theta, features typically associated with maintenance (storage of content) processes. In contrast, significant predictors of reaction time and its variability included contingent negative variation and the P3b, features typically associated with goal maintenance and updating. Broadly, these results suggest two principal dimensions that contribute to WM performance, tonic processes during maintenance contributing to capacity, and phasic processes during stimulus processing that contribute to response speed and variability. The analyses additionally highlight that reliability of features across tasks was greater (and comparable to that of WM performance) for features associated with stimulus processing (P3b and alpha), than with maintenance (gamma, theta and cross-frequency coupling).

m.3243A > G-Induced Mitochondrial Dysfunction Impairs Human Neuronal Development and Reduces Neuronal Network Activity and Synchronicity

Epilepsy, intellectual and cortical sensory deficits, and psychiatric manifestations are the most frequent manifestations of mitochondrial diseases. How mitochondrial dysfunction affects neural structure and function remains elusive, mostly because of a lack of proper in vitro neuronal model systems with mitochondrial dysfunction. Leveraging induced pluripotent stem cell technology, we differentiated excitatory cortical neurons (iNeurons) with normal (low heteroplasmy) and impaired (high heteroplasmy) mitochondrial function on an isogenic nuclear DNA background from patients with the common pathogenic m.3243A > G variant of mitochondrial encephalomyopathy, lactic acidosis, and stroke-like episodes (MELAS). iNeurons with high heteroplasmy exhibited mitochondrial dysfunction, delayed neural maturation, reduced dendritic complexity, and fewer excitatory synapses. Micro-electrode array recordings of neuronal networks displayed reduced network activity and decreased synchronous network bursting. Impaired neuronal energy metabolism and compromised structural and functional integrity of neurons and neural networks could be the primary drivers of increased susceptibility to neuropsychiatric manifestations of mitochondrial disease.

Electrophysiological correlates of spontaneous mind wandering in attention-deficit/hyperactivity disorder

We recently hypothesised that increased spontaneous mind wandering (MW-S) reflects a core process underlying attention-deficit/hyperactivity disorder (ADHD). Previous studies show that individuals with ADHD and neurotypical individuals with increased MW-S display similar cognitive-performance and electrophysiological (EEG) impairments in attentional processes. However, the cognitive-EEG markers associated with increased MW-S in ADHD remain poorly understood. We therefore investigated such markers in a sample of 69 sex- and age-matched adults with ADHD and 29 controls during the Sustained Attention to Response Task. We compared task performance and EEG measures (P3, time-frequency brain-oscillations) of attentional processes between groups, and examined their association with a validated self-report questionnaire of MW-S. Finally, we tested the hypothesis that MW-S and ADHD diagnosis relate to the same cognitive-EEG impairments using a hierarchical regression model. Compared to controls, adults with ADHD showed attenuations in P3, event-related alpha and beta suppression during response inhibition (No-Go trials), and theta power activations during response execution (Go trials), as well as increased reaction time variability and more commission/omission errors. MW-S was also continuously associated with most cognitive-EEG measures related to ADHD. The hierarchical regressions on measures associated with both ADHD diagnosis and MW-S showed that MW-S did not explain additional variance in the cognitive-EEG markers (except for beta suppression) beyond ADHD diagnosis, and vice versa. These findings are consistent with our hypothesis that ADHD diagnosis and MW-S share common neural deficits, and that MW-S may reflect a core symptom of the disorder.

Towards a Pragmatic Approach to a Psychophysiological Unit of Analysis for Mental and Brain Disorders: An EEG-Copeia for Neurofeedback

This article proposes what we call an "EEG-Copeia" for neurofeedback, like the "Pharmacopeia" for psychopharmacology. This paper proposes to define an "EEG-Copeia" as an organized list of scientifically validated EEG markers, characterized by a specific association with an identified cognitive process, that define a psychophysiological unit of analysis useful for mental or brain disorder evaluation and treatment. A characteristic of EEG neurofeedback for mental and brain disorders is that it targets a EEG markers related to a supposed cognitive process, whereas conventional treatments target clinical manifestations. This could explain why EEG neurofeedback studies encounter difficulty in achieving reproducibility and validation. The present paper suggests that a first step to optimize EEG neurofeedback protocols and future research is to target a valid EEG marker. The specificity of the cognitive skills trained and learned during real time feedback of the EEG marker could be enhanced and both the reliability of neurofeedback training and the therapeutic impact optimized. However, several of the most well-known EEG markers have seldom been applied for neurofeedback. Moreover, we lack a reliable and valid EEG targets library for further RCT to evaluate the efficacy of neurofeedback in mental and brain disorders. With the present manuscript, our aim is to foster dialogues between cognitive neuroscience and EEG neurofeedback according to a psychophysiological perspective. The primary objective of this review was to identify the most robust EEG target. EEG markers linked with one or several clearly identified cognitive-related processes will be identified. The secondary objective was to organize these EEG markers and related cognitive process in a psychophysiological unit of analysis matrix inspired by the Research Domain Criteria (RDoC) project.

Modulation of Multiunit Spike Activity by Transcranial AC Stimulation (tACS) in the Rat Cerebellar Cortex

Transcranial electrical stimulation (tES) techniques have garnered significant interest due to their non-invasiveness and potential to offer a treatment option in a wide variety of brain disorders. Among several modulation techniques, transcranial alternating current stimulation (tACS) is favored for its ability to entrain the neural oscillations. The cerebellum is one of the targeted sites because of its involvement in motor and cognitive functions. However, animal studies are lacking in the literature looking into the mechanism of action in cerebellar tACS. In this study, we used a rat model and monitored the activity of the cerebellar cortex, which sculpts the cerebellar output by adjusting the firing rate and timing of the neurons in the deep cerebellar nuclei (DCN). For neural recording, a tungsten electrode was inserted into the cerebellar cortex through a craniotomy hole located over the right paramedian lobule (PML). A helical Ag/AgCl wire electrode was placed atop the skull near the caudal edge to inject a 1 Hz biphasic sinusoidal current. Our results showed that the multiunit activity (MUA) of the cerebellar cortex was strongly modulated by tACS. The negative phase of the electric current enhanced the neural firing rate while the positive phase suppressed the activity. Furthermore, the spike rate showed modulation by the instantaneous strength of the injected current within the sinusoidal cycle. This warrants research to further look into the mechanism of tACS acting on the cerebellar cortex at the cellular level.

Deep Learning Convolutional Neural Networks Discriminate Adult ADHD From Healthy Individuals on the Basis of Event-Related Spectral EEG

Attention deficit hyperactivity disorder (ADHD) is a heterogeneous neurodevelopmental disorder that affects 5% of the pediatric and adult population worldwide. The diagnosis remains essentially clinical, based on history and exam, with no available biomarkers. In this paper, we describe a convolutional neural network (CNN) with a four-layer architecture combining filtering and pooling, which we train using stacked multi-channel EEG time-frequency decompositions (spectrograms) of electroencephalography data (EEG), particularly of event-related potentials (ERP) from ADHD patients (n = 20) and healthy controls (n = 20) collected during the Flanker Task, with 2800 samples for each group. We treat the data as in audio or image classification approaches, where deep networks have proven successful by exploiting invariances and compositional features in the data. The model reaches a classification accuracy of 88% ± 1.12%, outperforming the Recurrent Neural Network and the Shallow Neural Network used for comparison, and with the key advantage, compared with other machine learning approaches, of avoiding the need for manual selection of EEG spectral or channel features. The event-related spectrograms also provide greater accuracy compared to resting state EEG spectrograms. Finally, through the use of feature visualization techniques such as DeepDream, we show that the main features exciting the CNN nodes are a decreased power in the alpha band and an increased power in the delta-theta band around 100 ms for ADHD patients compared to healthy controls, suggestive of attentional and inhibition deficits, which have been previously suggested as pathophyisiological signatures of ADHD. While confirmation with larger clinical samples is necessary, these results suggest that deep networks may provide a useful tool for the analysis of EEG dynamics even from relatively small datasets, highlighting the potential of this methodology to develop biomarkers of practical clinical utility.

Alpha modulation during working memory encoding predicts neurocognitive impairment in ADHD

BACKGROUND

Attention-deficit/hyperactivity disorder (ADHD) is associated with working memory (WM) deficits. However, WM is a multiprocess construct that can be impaired through several pathways, leaving the source of WM impairments in ADHD unresolved. In this study, we aim to replicate, in an independent sample, previously reported deficits in component processes of WM deficits in ADHD and expand to consider their implications for neurocognitive outcomes.

METHODS

In 119 children (7-14 years old, 85 with ADHD), we used electroencephalography measures to quantify component processes during performance of a spatial working memory task. We quantified stimulus encoding using alpha range (8-12 Hz) power; vigilance by the P2 event-related potential to cues; and WMmaintenance by occipital-alpha and frontal-theta (4-7 Hz) power. These measures were evaluated against metrics of executive function, ADHD symptoms, and academic achievement.

RESULTS

Encoding alpha-power decreases and cue P2 amplitude were attenuated in ADHD, whereas occipital-alpha power during maintenance was significantly greater in ADHD, consistent with a compensatory response to weak encoding. Weak alpha modulation during encoding was associated with poorer reading comprehension and executive function, as well as enhanced ADHD symptoms. Previously reported effects in frontal-theta power failed to replicate.

CONCLUSIONS

Stimulus encoding, a component process of WM coupled to alpha modulation, is impaired in ADHD, and, unlike WM maintenance or vigilance processes, has implications outside of the laboratory via a relationship with executive function, and, to a weaker extent, reading comprehension.

A Low-Level Perceptual Correlate of Behavioral and Clinical Deficits in ADHD

In many studies of attention-deficit hyperactivity disorder (ADHD), stimulus encoding and processing (perceptual function) and response selection (executive function) have been intertwined. To dissociate deficits in these functions, we introduced a task that parametrically varied low-level stimulus features (orientation and color) for fine-grained analysis of perceptual function. It also required participants to switch their attention between feature dimensions on a trial-by-trial basis, thus taxing executive processes. Furthermore, we used a response paradigm that captured task-irrelevant motor output (TIMO), reflecting failures to use the correct stimulus-response rule. ADHD participants had substantially higher perceptual variability than controls, especially for orientation, as well as higher TIMO. In both ADHD and controls, TIMO was strongly affected by the switch manipulation. Across participants, the perceptual variability parameter was correlated with TIMO, suggesting that perceptual deficits are associated with executive function deficits. Based on perceptual variability alone, we were able to classify participants into ADHD and controls with a mean accuracy of about 77%. Participants' self-reported General Executive Composite score correlated not only with TIMO but also with the perceptual variability parameter. Our results highlight the role of perceptual deficits in ADHD and the usefulness of computational modeling of behavior in dissociating perceptual from executive processes.