Neural circuitry underlying sustained attention in healthy adolescents and in ADHD symptomatology

Predicting creative behavior using resting-state electroencephalography

Neuroscience research has shown that specific brain patterns can relate to creativity during multiple tasks but also at rest. Nevertheless, the electrophysiological correlates of a highly creative brain remain largely unexplored. This study aims to uncover resting-state networks related to creative behavior using high-density electroencephalography (HD-EEG) and to test whether the strength of functional connectivity within these networks could predict individual creativity in novel subjects. We acquired resting state HD-EEG data from 90 healthy participants who completed a creative behavior inventory. We then employed connectome-based predictive modeling; a machine-learning technique that predicts behavioral measures from brain connectivity features. Using a support vector regression, our results reveal functional connectivity patterns related to high and low creativity, in the gamma frequency band (30-45 Hz). In leave-one-out cross-validation, the combined model of high and low networks predicts individual creativity with very good accuracy (r = 0.36, p = 0.00045). Furthermore, the model's predictive power is established through external validation on an independent dataset (N = 41), showing a statistically significant correlation between observed and predicted creativity scores (r = 0.35, p = 0.02). These findings reveal large-scale networks that could predict creative behavior at rest, providing a crucial foundation for developing HD-EEG-network-based markers of creativity.

A robust brain network for sustained attention from adolescence to adulthood that predicts later substance use

Substance use, including cigarettes and cannabis, is associated with poorer sustained attention in late adolescence and early adulthood. Previous studies were predominantly cross-sectional or under-powered and could not indicate if impairment in sustained attention was a predictor of substance-use or a marker of the inclination to engage in such behaviour. This study explored the relationship between sustained attention and substance use across a longitudinal span from ages 14 to 23 in over 1,000 participants. Behaviours and brain connectivity associated with diminished sustained attention at age 14 predicted subsequent increases in cannabis and cigarette smoking, establishing sustained attention as a robust biomarker for vulnerability to substance use. Individual differences in network strength relevant to sustained attention were preserved across developmental stages and sustained attention networks generalized to participants in an external dataset. In summary, brain networks of sustained attention are robust, consistent, and able to predict aspects of later substance use.

Variability in Cognitive Task Performance in Early Adolescence Is Associated With Stronger Between-Network Anticorrelation and Future Attention Problems

Background

Intraindividual variability (IIV) during cognitive task performance is a key behavioral index of attention and a consistent marker of attention-deficit/hyperactivity disorder. In adults, lower IIV has been associated with anticorrelation between the default mode network (DMN) and dorsal attention network (DAN)-thought to underlie effective allocation of attention. However, whether these behavioral and neural markers of attention are 1) associated with each other and 2) can predict future attention-related deficits has not been examined in a developmental, population-based cohort.

Methods

We examined relationships at the baseline visit between IIV on 3 cognitive tasks, DMN-DAN anticorrelation, and parent-reported attention problems using data from the Adolescent Brain Cognitive Development (ABCD) Study (N = 11,878 participants, ages 9 to 10 years, female = 47.8%). We also investigated whether behavioral and neural markers of attention at baseline predicted attention problems 1, 2, and 3 years later.

Results

At baseline, greater DMN-DAN anticorrelation was associated with lower IIV across all 3 cognitive tasks (B = 0.22 to 0.25). Older age at baseline was associated with stronger DMN-DAN anticorrelation and lower IIV (B = -0.005 to -0.0004). Weaker DMN-DAN anticorrelation and IIV were cross-sectionally associated with attention problems (B = 1.41 to 7.63). Longitudinally, lower IIV at baseline was associated with less severe attention problems 1 to 3 years later, after accounting for baseline attention problems (B = 0.288 to 0.77).

Conclusions

The results suggest that IIV in early adolescence is associated with worsening attention problems in a representative cohort of U.S. youth. Attention deficits in early adolescence may be important for understanding and predicting future cognitive and clinical outcomes.

A preliminary study of white matter correlates of a laboratory measure of attention and motor stability in attention-deficit/hyperactivity disorder

Attention-deficit/hyperactivity disorder (ADHD) is a complex behavioral disorder, often difficult and time consuming to diagnose. Laboratory assessment of ADHD-related constructs of attention and motor activity may be helpful in elucidating neurobiology; however, neuroimaging studies evaluating laboratory measures of ADHD are lacking. In this preliminary study, we assessed the association between fractional anisotropy (FA), a measure of white matter microstructure, and laboratory measures of attention and motor behavior using the QbTest, a widely used measure thought to improve clinician diagnostic confidence. This is the first look at neural correlates of this widely used measure. The sample included adolescents and young adults (ages 12-20, 35% female) with ADHD (n = 31) and without (n = 52). As expected, ADHD status was associated with motor activity, and cognitive inattention and impulsivity in the laboratory. With regard to MRI findings, laboratory observed motor activity and inattention were associated with greater FA in white matter regions of the primary motor cortex. All three laboratory observations were associated with lower FA in regions subserving fronto-striatal-thalamic and frontoparietal (i.e. superior longitudinal fasciculus) circuitry. Further, FA in white matter regions of the prefrontal cortex appeared to mediate the relationship between ADHD status and motor activity on the QbTest. These findings, while preliminary, suggest that performance on certain laboratory tasks is informative with regard to neurobiological correlates of subdomains of the complex ADHD phenotype. In particular, we provide novel evidence for a relationship between an objective measure of motor hyperactivity and white matter microstructure in motor and attentional networks.

White matter and sustained attention in children with attention/deficit-hyperactivity disorder: A longitudinal fixel-based analysis

Sustained attention is a cognitive function with known links to academic success and mental health disorders such as attention/deficit-hyperactivity disorder (ADHD). Several functional networks are critical to sustained attention, however the association between white matter maturation in tracts linking functional nodes and sustained attention in typical and atypical development is unknown. 309 diffusion-weighted imaging scans were acquired from 161 children and adolescents (80 ADHD, 81 control) at up to three timepoints over ages 9-14. A fixel-based analysis approach was used to calculate mean fiber density and fiber-bundle cross section in tracts of interest. Sustained attention was measured using omission errors and response time variability on the out-of-scanner sustained attention to response task. Linear mixed effects models examined associations of age, group and white matter metrics with sustained attention. Greater fiber density in the bilateral superior longitudinal fasciculus (SLF) I and right SLF II was associated with fewer attention errors in the control group only. In ADHD and control groups, greater fiber density in the left ILF and right thalamo-premotor pathway, as well as greater fiber cross-section in the left SLF I and II and right SLF III, was associated with better sustained attention. Relationships were consistent across the age span. Results suggest that greater axon diameter or number in the dorsal and middle SLF may facilitate sustained attention in neurotypical children but does not assist those with ADHD potentially due to disorder-related alterations in this region. Greater capacity for information transfer across the SLF was associated with attention maintenance in 9-14-year-olds regardless of diagnostic status, suggesting white matter macrostructure may also be important for attention maintenance. White matter and sustained attention associations were consistent across the longitudinal study, according with the stability of structural organization over this time. Future studies can investigate modifiability of white matter properties through ADHD medications.

Investigation of white matter functional networks underlying different behavioral profiles in attention-deficit/hyperactivity disorder

Background

Cortical functional network alterations have been widely accepted as the neural basis of attention-deficit/hyperactivity disorder (ADHD). Recently, white matter has also been recognized as a novel neuroimaging marker of psychopathology and has been used as a complement to cortical functional networks to investigate brain-behavior relationships. However, disorder-specific features of white matter functional networks (WMFNs) are less well understood than those of gray matter functional networks. In the current study, we constructed WMFNs using a new strategy to characterize behavior-related network features in ADHD.

Methods

We recruited 46 drug-naïve boys with ADHD and 46 typically developing (TD) boys, and used clustering analysis on resting-state functional magnetic resonance imaging data to generate WMFNs in each group. Intrinsic activity within each network was extracted, and the associations between network activity and behavior measures were assessed using correlation analysis.

Results

Nine WMFNs were identified for both ADHD and TD participants. However, boys with ADHD showed a splitting of the inferior corticospinal-cerebellar network and lacked a cognitive control network. In addition, boys with ADHD showed increased activity in the dorsal attention network and somatomotor network, which correlated positively with attention problems and hyperactivity symptom scores, respectively, while they presented decreased activity in the frontoparietal network and frontostriatal network in association with poorer performance in response inhibition, working memory, and verbal fluency.

Conclusions

We discovered a dual pattern of white matter network activity in drug-naïve ADHD boys, with hyperactive symptom-related networks and hypoactive cognitive networks. These findings characterize two distinct types of WMFN in ADHD psychopathology.

Normierung der Testbatterie COGBAT bei Jugendlichen im Alter von 12 bis 15 Jahren

Zusammenfassung: Das Jugendalter stellt eine wichtige Phase in der Entwicklung der Verarbeitungsgeschwindigkeit, der Aufmerksamkeit, des Gedächtnisses und der exekutiven Funktionen dar. Im Rahmen einer Normierungsstudie der kognitiven Basistestung (COGBAT) für das Jugendalter wurden Testwerte bei n = 269 Jugendlichen im Alter von 12 bis 15 Jahren erhoben und mit den Normen der Altersgruppe der 16- bis 30-Jährigen verglichen. Zusätzlich wurde überprüft, inwiefern sich diese Testergebnisse in der subjektiven Einschätzung zur Leistungsfähigkeit (FLei) und Psychopathologie (SDQ) abbilden lassen. Im Jugendalter zeigte sich ein starker Zuwachs in der kognitiven Flexibilität, der Verarbeitungs- und Reaktionsgeschwindigkeit sowie der Inhibitions- und Planungsfähigkeit. Ein bedeutsamer Geschlechtsunterschied fand sich in der Inhibition, mit stärkeren Leistungen bei Mädchen als bei Jungen. Zwischen den Testergebnissen und den subjektiven Einschätzungen zeigten sich keine Zusammenhänge.

Prenatal cannabis exposure predicts attention problems, without changes on fMRI in adolescents

OBJECTIVES

We hypothesized that prenatal cannabis exposure (PCE) would be associated with increased attention problems and altered neurocognition in young adolescents.

METHODS

Data were obtained from the Adolescent Brain Cognitive Development (ABCD study®), a cohort of approximately 12,000 children. Presence or absence of PCE after knowledge of pregnancy was measured by caregiver report. All participants with PCE (N = 224) were included and compared to two control groups; those matched on tobacco and alcohol exposure and those without prenatal tobacco or alcohol exposures. Outcomes were measured with the ABCD baseline assessment when participants were 9-10 years old and included attention, internalizing, externalizing and total problems scales on the Child Behavior Checklist (CBCL). Teacher reports were used when available. Mixed effects modeling assessed the association between PCE and outcomes controlling for parental psychopathology, prematurity and socioeconomic status. For participants with available data, patterns of brain activity during three fMRI tasks (the Stop Signal Task measuring response inhibition, the Monetary Incentive Delay (MID) task measuring reward processing and the EN-Back task measuring working memory) were analyzed using Permutation Analyses of the Linear Model.

RESULTS

Compared to both control groups, participants with PCE had significantly higher attention problems, externalizing, and total problem scores. PCE did not impact cognitive performance or patterns of brain activation during fMRI tasks.

CONCLUSIONS

There are long-term associations between PCE and early adolescent attention and behavioral problems. These are not reflected in cognitive performance or task fMRI measures, a finding that is consistent with reports that fewer than half of children with ADHD have any specific cognitive deficit (Nigg et al., 2005; Willcutt et al., 2005). The young age of the sample may also relate to this finding and future investigation of neurodevelopmental trajectories of youth with PCE is warranted.

Longitudinal maturation of resting state networks: Relevance to sustained attention and attention deficit/hyperactivity disorder

The transition from childhood to adolescence involves important neural function, cognition, and behavior changes. However, the links between maturing brain function and sustained attention over this period could be better understood. This study examined typical changes in network functional connectivity over childhood to adolescence, developmental differences in attention deficit/hyperactivity disorder (ADHD), and how functional connectivity might underpin variability in sustained attention development in a longitudinal sample. A total of 398 resting state scans were collected from 173 children and adolescents (88 ADHD, 85 control) at up to three timepoints across ages 9-14 years. The effects of age, sex, and diagnostic group on changes in network functional connectivity were assessed, followed by relationships between functional connectivity and sustained attention development using linear mixed effects modelling. The ADHD group displayed greater decreases in functional connectivity between salience and visual networks compared with controls. Lower childhood functional connectivity between the frontoparietal and several brain networks was associated with more rapid sustained attention development, whereas frontoparietal to dorsal attention network connectivity related to attention trajectories in children with ADHD alone. Brain network segregation may increase into adolescence as predicted by key developmental theories; however, participants with ADHD demonstrated altered developmental trajectories between salience and visual networks. The segregation of the frontoparietal network from other brain networks may be a mechanism supporting sustained attention development. Frontoparietal to dorsal attention connectivity can be a focus for further work in ADHD.

Identification of Brain Regions with Enhanced Functional Connectivity with the Cerebellum Region in Children with Attention Deficit Hyperactivity Disorder: A Resting-State fMRI Study

Background

To explore the brain regions with higher functional connectivity with the cerebellum at resting state and the brain functions related to cognitive function in children with attention-deficit hyperactivity disorder (ADHD).

Methods

Thirty children with ADHD and 33 typically developing children (TDC) were examined using resting-state functional magnetic resonance imaging (fMRI) scans. Seed-based functional connectivity (FC) analysis was performed.

Results

Four brain areas with higher FC values were identified in ADHD children. These four areas were the left middle frontal gyrus, right middle frontal gyrus, right superior temporal gyrus and left parahippocampal gyrus (P < 0.05). The results of the CPT show that the number of omission errors was significantly higher in the children with ADHD than in the TD group (5.13±5.12 vs 2.18±2.36, P = 0.000). The commission number in the ADHD group was also significantly higher than that of the TD group (4.03±6.56 vs 2.00±2.85, P = 0.002). However, no statistically significant difference was observed in the correct reaction time between the two groups (641.54±146.79 ms vs 584.81±145.82 ms, P = 0.835).

Conclusion

The dysfunction of cerebellar functional connectivity in specific brain regions may be one of the pathological and physiological causes of cognitive impairment of ADHD.

Delineating visual, auditory and motor regions in the human brain with functional neuroimaging: a BrainMap-based meta-analytic synthesis

Most everyday behaviors and laboratory tasks rely on visual, auditory and/or motor-related processes. Yet, to date, there has been no large-scale quantitative synthesis of functional neuroimaging studies mapping the brain regions consistently recruited during such perceptuo-motor processing. We therefore performed three coordinate-based meta-analyses, sampling the results of neuroimaging experiments on visual (n = 114), auditory (n = 122), or motor-related (n = 251) processing, respectively, from the BrainMap database. Our analyses yielded both regions known to be recruited for basic perceptual or motor processes and additional regions in posterior frontal cortex. Comparing our results with data-driven network definitions based on resting-state functional connectivity revealed good overlap in expected regions but also showed that perceptual and motor task-related activations consistently involve additional frontal, cerebellar, and subcortical areas associated with "higher-order" cognitive functions, extending beyond what is captured when the brain is at "rest." Our resulting sets of domain-typical brain regions can be used by the neuroimaging community as robust functional definitions or masks of regions of interest when investigating brain correlates of perceptual or motor processes and their interplay with other mental functions such as cognitive control or affective processing. The maps are made publicly available via the ANIMA database.

Cerebellar-cerebral dynamic functional connectivity alterations in major depressive disorder

BACKGROUND

The cerebellum plays an important role in the neural mechanism of depression and its static functional connectivity (FC) with the cerebrum is disrupted in patients with major depressive disorder (MDD). However, cerebellar-cerebral dynamic FC alterations in MDD remain largely unknown.

METHODS

50 patients with MDD and 36 well-matched healthy controls underwent resting-state functional magnetic resonance imaging. Cerebellar-cerebral dynamic FC analyses were performed using the cerebellar seeds previously identified as being involved in the executive, default-mode, affective-limbic, and motor networks. Inter-group differences in the cerebellar dynamic FC and their associations with clinical and cognitive variables were examined.

RESULTS

Compared to healthy controls, patients with MDD had decreased cerebellar-cerebral dynamic FC of the cerebellar subregions connecting with the executive, default-mode and affective-limbic networks. The dynamic FC of the cerebellar subregion connecting with the affective-limbic network was related to severity of depression and anxiety symptoms in MDD patients. The dynamic FC of the cerebellar subregions connecting with the default-mode and affective-limbic networks were related to sustained attention and prospective memory in controls, while the correlations were inverse or non-significant in patients.

LIMITATIONS

The fairly modest sample size and potential medication effect may increase the instability of the results.

CONCLUSIONS

Our findings provide further evidence for the pivotal role of the cerebellum in the neuropathology of depression, pointing to potential targets of cerebellar-cerebral pathways for alternative intervention or monitoring therapeutic responses.

MRI Insights Into Adolescent Neurocircuitry-A Vision for the Future

Adolescence is the time of onset of many psychiatric disorders. Half of pediatric patients present with comorbid psychiatric disorders that complicate both their medical and psychiatric care. Currently, diagnosis and treatment decisions are based on symptoms. The field urgently needs brain-based diagnosis and personalized care. Neuroimaging can shed light on how aberrations in brain circuits might underlie psychiatric disorders and their development in adolescents. In this perspective article, we summarize recent MRI literature that provides insights into development of psychiatric disorders in adolescents. We specifically focus on studies of brain structural and functional connectivity. Ninety-six included studies demonstrate the potential of MRI to assess psychiatrically relevant constructs, diagnose psychiatric disorders, predict their development or predict response to treatment. Limitations of the included studies are discussed, and recommendations for future research are offered. We also present a vision for the role that neuroimaging may play in pediatrics and primary care in the future: a routine neuropsychological and neuropsychiatric imaging (NPPI) protocol for adolescent patients, which would include a 30-min brain scan, a quality control and safety read of the scan, followed by computer-based calculation of the structural and functional brain network metrics that can be compared to the normative data by the pediatrician. We also perform a cost-benefit analysis to support this vision and provide a roadmap of the steps required for this vision to be implemented.

Exploring white matter functional networks in children with attention-deficit/hyperactivity disorder

Attention-deficit/hyperactivity disorder has been identified to involve the impairment of large-scale functional networks within grey matter, and recent studies have suggested that white matter, which also encodes neural activity, can manifest intrinsic functional organization similar to that of grey matter. However, the alterations in white matter functional networks in attention-deficit/hyperactivity disorder remain unknown. We recruited a total of 99 children, including 66 drug-naive patients and 33 typically developing controls aged from 6 to 14, to characterize the alterations in functional networks within white matter in drug-naive children with attention-deficit/hyperactivity disorder. Using clustering analysis, resting-state functional MRI data in the white matter were parsed into different networks. Intrinsic activity within each network and connectivity between networks and the associations between network activity strength and clinical symptoms were assessed. We identified eight distinct white matter functional networks: the default mode network, the somatomotor network, the dorsal attention network, the ventral attention network, the visual network, the deep frontoparietal network, the deep frontal network and the inferior corticospinal-posterior cerebellum network. The default mode, somatomotor, dorsal attention and ventral attention networks showed lower spontaneous neural activity in patients. In particular, the default mode network and the somatomotor network largely showed higher connectivity with other networks, which correlated with more severe hyperactive behaviour, while the dorsal and ventral attention networks mainly had lower connectivity with other networks, which correlated with poor attention performance. In conclusion, there are two distinct patterns of white matter functional networks in children with attention-deficit/hyperactivity disorder, with one being the hyperactivity-related hot networks including default mode network and somatomotor network and the other being inattention-related cold networks including dorsal attention and ventral attention network. These results extended upon our understanding of brain functional networks in attention-deficit/hyperactivity disorder from the perspective of white matter dysfunction.

The Low-Frequency Fluctuation of Trial-by-Trial Frontal Theta Activity and Its Correlation With Reaction-Time Variability in Sustained Attention

Reaction-time variability is a critical index of sustained attention. However, researchers still lack effective measures to establish the association between neurophysiological activity and this behavioral variability. Here, the present study recorded reaction time (RT) and cortical electroencephalogram (EEG) in healthy subjects when they continuously performed an alternative responding task. The frontal theta activity and reaction-time variability were examined trial by trial using the measures of standard deviation (SD) in the time domain and amplitude of low-frequency fluctuation (ALFF) in the frequency domain. Our results showed that the SD of reaction-time variability did not have any correlation with the SD of trial-by-trial frontal theta activity, and the ALFF of reaction-time variability has a significant correlation with the ALFF of trial-by-trial frontal theta activity in 0.01–0.027 Hz. These results suggested the methodological significance of ALFF in establishing the association between neurophysiological activity and reaction-time variability. Furthermore, these findings also support the low-frequency fluctuation as a potential feature of sustained attention.

Inhibitory-control event-related potentials correlate with individual differences in alcohol use

Impulsivity is a multidimensional construct that is related to different aspects of alcohol use, abuse, and dependence. Inhibitory control, one facet of impulsivity, can be assayed using the stop-signal task (SST) and quantified behaviorally via the stop-signal reaction time (SSRT) and electrophysiologically using event-related potentials (ERPs). Research on the relationship between alcohol use and SSRTs, and between alcohol use and inhibitory-control ERPs, is mixed. Here, adult alcohol users (n = 79), with a wide range of scores on the Alcohol Use Disorders Identification Test (AUDIT), completed the SST under electroencephalography (EEG) (70% of participants had AUDIT total scores greater than or equal to 8). Other measures, including demographic, self-report, and task-based measures of impulsivity, personality, and psychological factors, were also recorded. A machine-learning method with penalized linear regression was used to correlate individual differences in alcohol use with impulsivity measures. Four separate models were tested, with out-of-sample validation used to quantify performance. ERPs alone statistically predicted alcohol use (cross-validated r = 0.28), with both early and late ERP components contributing to the model (larger N2, but smaller P3, amplitude). Behavioral data from a wide range of impulsivity measures were also associated with alcohol use (r = 0.37). SSRT was a relatively weak statistical predictor, whereas the Stroop interference effect was relatively strong. The addition of nonimpulsivity behavioral measures did not improve the correlation (r = 0.34) and was similar when ERPs were combined with non-ERP data (r = 0.29). These findings show that inhibitory control ERPs are robustly correlated individual differences in alcohol use.

Functional connectivity predicts changes in attention observed across minutes, days, and months

The ability to sustain attention differs across people and changes within a single person over time. Although recent work has demonstrated that patterns of functional brain connectivity predict individual differences in sustained attention, whether these same patterns capture fluctuations in attention within individuals remains unclear. Here, across five independent studies, we demonstrate that the sustained attention connectome-based predictive model (CPM), a validated model of sustained attention function, generalizes to predict attentional state from data collected across minutes, days, weeks, and months. Furthermore, the sustained attention CPM is sensitive to within-subject state changes induced by propofol as well as sevoflurane, such that individuals show functional connectivity signatures of stronger attentional states when awake than when under deep sedation and light anesthesia. Together, these results demonstrate that fluctuations in attentional state reflect variability in the same functional connectivity patterns that predict individual differences in sustained attention.

EEG spectral power, but not theta/beta ratio, is a neuromarker for adult ADHD

Adults with attention-deficit/hyperactivity disorder (ADHD) have been described as having altered resting-state electroencephalographic (EEG) spectral power and theta/beta ratio (TBR). However, a recent review (Pulini et al. 2018) identified methodological errors in neuroimaging, including EEG, ADHD classification studies. Therefore, the specific EEG neuromarkers of adult ADHD remain to be identified, as do the EEG characteristics that mediate between genes and behaviour (mediational endophenotypes). Resting-state eyes-open and eyes-closed EEG was measured from 38 adults with ADHD, 45 first-degree relatives of people with ADHD and 51 unrelated controls. A machine learning classification analysis using penalized logistic regression (Elastic Net) examined if EEG spectral power (1-45 Hz) and TBR could classify participants into ADHD, first-degree relatives and/or control groups. Random-label permutation was used to quantify any bias in the analysis. Eyes-open absolute and relative EEG power distinguished ADHD from control participants (area under receiver operating characteristic = 0.71-0.77). The best predictors of ADHD status were increased power in delta, theta and low-alpha over centro-parietal regions, and in frontal low-beta and parietal mid-beta. TBR did not successfully classify ADHD status. Elevated eyes-open power in delta, theta, low-alpha and low-beta distinguished first-degree relatives from controls (area under receiver operating characteristic = 0.68-0.72), suggesting that these features may be a mediational endophenotype for adult ADHD. Resting-state EEG spectral power may be a neuromarker and mediational endophenotype of adult ADHD. These results did not support TBR as a diagnostic neuromarker for ADHD. It is possible that TBR is a characteristic of childhood ADHD.

Fronto-parietal engagement in response inhibition is inversely scaled with attention-deficit/hyperactivity disorder symptom severity

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A novel Go/No-go task points to a critical role for the IPS in response inhibition.

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IPS engagement in response inhibition is scaled back with ADHD symptom severity.

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Fronto-parietal connectivity increases when response inhibition is challenging.

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Connectivity modulation is also scaled back with ADHD symptom severity.

Background

Impaired response inhibition is one of the most consistent findings in attention deficit hyperactivity disorder (ADHD). However, the underlying brain mechanisms are not clear. This study aimed to underpin atypical inhibition-related brain activation and connectivity patterns in ADHD using a novel Go/No-go task design, and to determine its association with clinical symptoms of the disorder.

Methods

Forty-eight adults with ADHD performed a Go/No-go task in which target frequency was manipulated during functional MRI. Specific inhibition-related brain activation was correlated with ADHD symptom severity, to assess the relationship of individual differences in engagement of inhibition-related brain circuits with the magnitude of every-day functioning impairments. Finally, generalized psychophysical interaction analyses were carried out to examine whether not only engagement but also functional connectivity between regions implicated in response inhibition is related to symptom severity.

Results

We found no evidence for the expected parietal modulation by increased demand for inhibition at the group-level results. However, this lack of modulation was mediated by individual differences in ADHD symptom severity – increased engagement of the intraparietal sulcus (IPS) in inhibition-demanding events was evident in individuals with less severe symptoms but dissipated with increase in symptomatology. Similarly, functional connectivity between the IPS and the right inferior frontal gyrus (rIFG) was elevated under high inhibitory demand conditions, but this effect diminished with increased symptom severity.

Conclusions

The results highlight the importance of IPS engagement in response inhibition and suggest that IPS modulation may be driven by top-down control from the IFG. Moreover, the current findings force the point of treating ADHD as a continuum whereby brain correlates are scaled with severity of the disorder, and point to the potential use of individual differences in the modulation of IPS activation and connectivity as a neuromarker of ADHD.

Dopaminergic gene analysis indicates influence of inattention but not IQ in executive dysfunction of Indian ADHD probands

Organizational inefficiency and inattention are speculated to be the reason for executive deficit (ED) of ADHD probands. Even with average IQ, probands often perform poorly due to higher inattention. Pharmacotherapy, cognitive behavioural therapy, and counselling provide only symptomatic relief. Several candidate genes showed involvement with ADHD; the most consistent are dopamine receptor 4 (DRD4) and solute carrier family 6 member 3 (SLC6A3). We analyzed association of rarely investigated DRD4 and SLC6A3 variants with ADHD core traits in Indo-Caucasoid probands. ED, inattention, organizational efficiency, and IQ were measured by Barkley Deficit in Executive Functioning-Child & Adolescent scale, DSM-IV-TR, Conners' Parent Rating Scale-revised, and WISC respectively. Target sites were analyzed by PCR, RFLP, and/or Sanger sequencing of genomic DNA. DRD4 variants mostly affected inattention while SLC6A3 variants showed association with IQ. Few DRD4 and SLC6A3 variants showed dichotomous association with IQ and inattention. DRD4 Exon3 VNTR >4R showed negative impact on all traits excepting IQ. Inattention showed correlation with attention span, organizational efficiency, and ED, while IQ failed to do so. We infer that IQ and attention could be differentially regulated by dopaminergic gene variants affecting functional efficiency in ADHD and the two traits should be considered together for providing better rehabilitation.

Selective sustained attention: a developmental foundation for cognition

Higher-order cognition, particularly in real-life settings, often requires that parts of the sensory input be processed at the exclusion of others over a period of time. Consequently, this review focuses on the development of attention that is both selective (which entails processing parts of the sensory input at the exclusion of others) and sustained (which entails maintaining sensitivity to incoming stimuli for a period of time). Recent findings from four distinct areas of research reviewed here suggest that: (1) the underlying neural circuitry of selective sustained attention involves multiple cortical and subcortical brain regions; (2) selective sustained attention in infancy provides a developmental foundation for the emergence of executive function later in life; (3) suppression-based mechanisms of attentional selection that begin to emerge during the first year of life are important for memory and learning; and (4) selective sustained attention appears to be malleable through pre-natal and post-natal nutritional supplementation and interactions with mature social partners.

Effects of Exercise on Cognitive Performance in Children and Adolescents with ADHD: Potential Mechanisms and Evidence-based Recommendations

Attention Deficit Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder with a complex symptomatology, and core symptoms as well as functional impairment often persist into adulthood. Recent investigations estimate the worldwide prevalence of ADHD in children and adolescents to be ~7%, which is a substantial increase compared to a decade ago. Conventional treatment most often includes pharmacotherapy with central nervous stimulants, but the number of non-responders and adverse effects call for treatment alternatives. Exercise has been suggested as a safe and low-cost adjunctive therapy for ADHD and is reported to be accompanied by positive effects on several aspects of cognitive functions in the general child population. Here we review existing evidence that exercise affects cognitive functions in children with and without ADHD and present likely neurophysiological mechanisms of action. We find well-described associations between physical activity and ADHD, as well as causal evidence in the form of small to moderate beneficial effects following acute aerobic exercise on executive functions in children with ADHD. Despite large heterogeneity, meta-analyses find small positive effects of exercise in population-based control (PBC) children, and our extracted effect sizes from long-term interventions suggest consistent positive effects in children and adolescents with ADHD. Paucity of studies probing the effect of different exercise parameters impedes finite conclusions in this regard. Large-scale clinical trials with appropriately timed exercise are needed. In summary, the existing preliminary evidence suggests that exercise can improve cognitive performance intimately linked to ADHD presentations in children with and without an ADHD diagnosis. Based on the findings from both PBC and ADHD children, we cautiously provide recommendations for parameters of exercise.

Functional connectivity changes associated with fMRI neurofeedback of right inferior frontal cortex in adolescents with ADHD

Attention Deficit Hyperactivity Disorder (ADHD) is associated with poor self-control, underpinned by inferior fronto-striatal deficits. We showed previously that 18 ADHD adolescents over 11 runs of 8.5 min of real-time functional magnetic resonance neurofeedback of the right inferior frontal cortex (rIFC) progressively increased activation in 2 regions of the rIFC which was associated with clinical symptom improvement. In this study, we used functional connectivity analyses to investigate whether fMRI-Neurofeedback of rIFC resulted in dynamic functional connectivity changes in underlying neural networks. Whole-brain seed-based functional connectivity analyses were conducted using the two clusters showing progressively increased activation in rIFC as seed regions to test for changes in functional connectivity before and after 11 fMRI-Neurofeedback runs. Furthermore, we tested whether the resulting functional connectivity changes were associated with clinical symptom improvements and whether they were specific to fMRI-Neurofeedback of rIFC when compared to a control group who had to self-regulate another region. rIFC showed increased positive functional connectivity after relative to before fMRI-Neurofeedback with dorsal caudate and anterior cingulate and increased negative functional connectivity with regions of the default mode network (DMN) such as posterior cingulate and precuneus. Furthermore, the functional connectivity changes were correlated with clinical improvements and the functional connectivity and correlation findings were specific to the rIFC-Neurofeedback group. The findings show for the first time that fMRI-Neurofeedback of a typically dysfunctional frontal region in ADHD adolescents leads to strengthening within fronto-cingulo-striatal networks and to weakening of functional connectivity with posterior DMN regions and that this may be underlying clinical improvement.

Classification Accuracy of Neuroimaging Biomarkers in Attention-Deficit/Hyperactivity Disorder: Effects of Sample Size and Circular Analysis

BACKGROUND

Motivated by an inconsistency between reports of high diagnosis-classification accuracies and known heterogeneity in attention-deficit/hyperactivity disorder (ADHD), this study assessed classification accuracy in studies of ADHD as a function of methodological factors that can bias results. We hypothesized that high classification results in ADHD diagnosis are inflated by methodological factors.

METHODS

We reviewed 69 studies (of 95 studies identified) that used neuroimaging features to predict ADHD diagnosis. Based on reported methods, we assessed the prevalence of circular analysis, which inflates classification accuracy, and evaluated the relationship between sample size and accuracy to test if small-sample models tend to report higher classification accuracy, also an indicator of bias.

RESULTS

Circular analysis was detected in 15.9% of ADHD classification studies, lack of independent test set was noted in 13%, and insufficient methodological detail to establish its presence was noted in another 11.6%. Accuracy of classification ranged from 60% to 80% in the 59.4% of reviewed studies that met criteria for independence of feature selection, model construction, and test datasets. Moreover, there was a negative relationship between accuracy and sample size, implying additional bias contributing to reported accuracies at lower sample sizes.

CONCLUSIONS

High classification accuracies in neuroimaging studies of ADHD appear to be inflated by circular analysis and small sample size. Accuracies on independent datasets were consistent with known heterogeneity of the disorder. Steps to resolve these issues, and a shift toward accounting for sample heterogeneity and prediction of future outcomes, will be crucial in future classification studies in ADHD.

Acute Effects of Aerobic Exercise on Executive Function and Attention in Adult Patients With ADHD

Aerobic exercise can improve cognitive functions in healthy individuals and in various clinical groups, which might be particularly relevant for patients with ADHD. This study investigated the effects of a single bout of aerobic exercise on attention and executive functions in adult patients with ADHD, including functional MRI to examine the underlying neural mechanisms. On two different days, 23 adult patients with ADHD and 23 matched healthy controls performed in a flanker task, while functional MR images were collected, following 30 min of continuous stationary cycling with moderate intensity as well as after a control condition (watching a movie). Behavioral performance and brain activation were tested for differences between groups and conditions and for interactions to investigate whether exercise improves executive function to a greater extent in patients compared to healthy controls. Exercise significantly improved reaction times in congruent and incongruent trials of the flanker task in patients with ADHD but not in healthy controls. We found no changes in brain activation between the two conditions for either group. However, a subgroup analysis of ADHD patients with a higher degree of cardiorespiratory fitness revealed decreased activation in premotor areas during congruent trials and in premotor and medial frontal cortex during incongruent trials in the exercise compared to the control condition. Our results indicate exercise-induced improvements in attention and processing speed in patients with ADHD, demonstrating that adult patients with ADHD may benefit from an acute bout of exercise. These findings could be of high relevance for developing alternative treatment approaches for ADHD. In addition, results of the current study contribute to elucidate the neurophysiological mechanisms underlying the beneficial effects of exercise on cognition and to better understand the role of cardiorespiratory fitness on these effects.

A prediction model of working memory across health and psychiatric disease using whole-brain functional connectivity

Working memory deficits are present in many neuropsychiatric diseases with diagnosis-related severity. However, it is unknown whether this common behavioral abnormality is a continuum explained by a neural mechanism shared across diseases or a set of discrete dysfunctions. Here, we performed predictive modeling to examine working memory ability (WMA) as a function of normative whole-brain connectivity across psychiatric diseases. We built a quantitative model for letter three-back task performance in healthy participants, using resting state functional magnetic resonance imaging (rs-fMRI). This normative model was applied to independent participants (N = 965) including four psychiatric diagnoses. Individual’s predicted WMA significantly correlated with a measured WMA in both healthy population and schizophrenia. Our predicted effect size estimates on WMA impairment were comparable to previous meta-analysis results. These results suggest a general association between brain connectivity and working memory ability applicable commonly to health and psychiatric diseases.

Dynamic functional connectivity during task performance and rest predicts individual differences in attention across studies

Dynamic functional connectivity (DFC) aims to maximize resolvable information from functional brain scans by considering temporal changes in network structure. Recent work has demonstrated that static, i.e. time-invariant resting-state and task-based FC predicts individual differences in behavior, including attention. Here, we show that DFC predicts attention performance across individuals. Sliding-window FC matrices were generated from fMRI data collected during rest and attention task performance by calculating Pearson's r between every pair of nodes of a whole-brain atlas within overlapping 10-60s time segments. Next, variance in r values across windows was taken to quantify temporal variability in the strength of each connection, resulting in a DFC connectome for each individual. In a leave-one-subject-out-cross-validation approach, partial-least-square-regression (PLSR) models were then trained to predict attention task performance from DFC matrices. Predicted and observed attention scores were significantly correlated, indicating successful out-of-sample predictions across rest and task conditions. Combining DFC and static FC features numerically improves predictions over either model alone, but the improvement was not statistically significant. Moreover, dynamic and combined models generalized to two independent data sets (participants performing the Attention Network Task and the stop-signal task). Edges with significant PLSR coefficients concentrated in visual, motor, and executive-control brain networks; moreover, most of these coefficients were negative. Thus, better attention may rely on more stable, i.e. less variable, information flow between brain regions.

Attention profiles in autism spectrum disorder and subtypes of attention-deficit/hyperactivity disorder

Attention problems are observed in attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD). Most neuropsychological studies that compared both disorders focused on complex executive functions (EF), but missed to contrast basic attention functions, as well as ASD- and ADHD subtypes. The present study compared EF as well as basic attention functioning of children with the combined subtype (ADHD-C), the predominantly inattentive subtype (ADHD-I), and autism spectrum disorder without ADHD (ASD-) with typically developing controls (TD). Basic attention functions and EF profiles were analysed by testing the comprehensive attention function model of van Zomeren and Brouwer using profile analysis. Additionally, neurocognitive impairments in ASD- and ADHD were regressed on dimensional measures of attention- and hyperactive-impulsive symptoms across and within groups. ADHD-C revealed a strong impairment across measures of EF compared to ASD- and TD. The ADHD-C profile furthermore showed disorder specific impairments in interference control, whereas the ASD- profile showed a disorder specific impairment in basic attention component divided attention. Attention- and hyperactive-impulsive symptom severity did not predict neurocognitive impairments across- or within groups. Study findings thus support disorder and subtype specific attention/EF profiles, which refute the idea of a continuum of ADHD-I, ADHD-C, and ASD with increasing neurocognitive impairments.

Motor dysfunction as research domain across bipolar, obsessive-compulsive and neurodevelopmental disorders

Although genuine motor abnormalities (GMA) are frequently found in schizophrenia, they are also considered as an intrinsic feature of bipolar, obsessive-compulsive, and neurodevelopmental disorders with early onset such as autism, ADHD, and Tourette syndrome. Such transnosological observations strongly suggest a common neural pathophysiology. This systematic review highlights the evidence on GMA and their neuroanatomical substrates in bipolar, obsessive-compulsive, and neurodevelopmental disorders. The data lends support for a common pattern contributing to GMA expression in these diseases that seems to be related to cerebello-thalamo-cortical, fronto-parietal, and cortico-subcortical motor circuit dysfunction. The identified studies provide first evidence for a motor network dysfunction as a correlate of early neurodevelopmental deviance prior to clinical symptom expression. There are also first hints for a developmental risk factor model of these mental disorders. An in-depth analysis of motor networks and related patho-(physiological) mechanisms will not only help promoting Research Domain Criteria (RDoC) Motor System construct, but also facilitate the development of novel psychopharmacological models, as well as the identification of neurobiologically plausible target sites for non-invasive brain stimulation.

A Combination of Impulsivity Subdomains Predict Alcohol Intoxication Frequency

BACKGROUND

Impulsivity, broadly characterized as the tendency to act prematurely without foresight, is linked to alcohol misuse in college students. However, impulsivity is a multidimensional construct and different subdomains likely underlie different patterns of alcohol misuse. Here, we quantified the association between alcohol intoxication frequency and alcohol consumption frequency and choice, action, cognitive, and trait domains of impulsivity.

METHODS

University student drinkers (n = 106) completed a battery of demographic and alcohol-related items, as well as self-report and task-based measures indexing different facets of impulsivity. Two orthogonal latent factors, intoxication frequency and alcohol consumption frequency, were generated. Their validity was demonstrated with respect to adverse consequences of alcohol use. Machine learning with penalized regression and feature selection was then utilized to predict intoxication and alcohol consumption frequency using all impulsivity subdomains. Out-of-sample validation was used to quantify model performance.

RESULTS

Impulsivity measures alone were significant predictors of intoxication frequency, but not consumption frequency. Propensity for increased intoxication frequency was characterized by increased trait impulsivity, including the Disinhibition subscale of the Sensation Seeking Scale, Attentional and Non-planning subscales of the Barratt Impulsiveness Scale, increased task-based cognitive impulsivity (response time variability), and increased choice impulsivity (steeper delay discounting on a delay discounting questionnaire). A model combining impulsivity domains with other risk factors (gender; nicotine, cannabis, and other drug use; executive functioning; and learning processes) was also significant but did not outperform the model comprising of impulsivity alone.

CONCLUSIONS

Intoxication frequency, but not consumption frequency, was characterized by a number of impulsivity subdomains.

Genetic Insights Into ADHD Biology

ADHD is a neurobiological disorder with a large worldwide prevalence causing significant impairment in children, adolescents, and adults. While there is general agreement about genetic contributions toward the disorder, progress in leveraging genetics to learn more about the biology and risk factors for ADHD has been limited. In this perspective, we identified 105 genes from the literature showing at least nominal statistical significance in association with ADHD. We analyzed these genes for enrichment in biological pathways and in known interacting biological networks. We also analyzed the expression patterns of candidate genes across brain regions and across periods of human development. From our analysis, we identify 14 genes that cluster within an interactive gene network, with enrichment in nitric oxide synthase and alpha-1 adrenergic pathways. Furthermore, these genes show enrichment for expression in the cerebellum during childhood through young adulthood, and in the cortex in adolescence and young adulthood. Gene discovery holds great potential for elucidating the unknown biological underpinnings of ADHD. Genome-wide sequencing efforts are underway and are likely to provide important insights that can be leveraged for new treatments and interventions.