Attention network hypoconnectivity with default and affective network hyperconnectivity in adults diagnosed with attention-deficit/hyperactivity disorder in childhood

Corticostriatal causality analysis in children and adolescents with attention-deficit/hyperactivity disorder

AIM

The effective connectivity between the striatum and cerebral cortex has not been fully investigated in attention-deficit/hyperactivity disorder (ADHD). Our objective was to explore the interaction effects between diagnosis and age on disrupted corticostriatal effective connectivity and to represent the modulation function of altered connectivity pathways in children and adolescents with ADHD.

METHODS

We performed Granger causality analysis on 300 participants from a publicly available Attention-Deficit/Hyperactivity Disorder-200 dataset. By computing the correlation coefficients between causal connections between striatal subregions and other cortical regions, we estimated the striatal inflow and outflow connection to represent intermodulation mechanisms in corticostriatal pathways.

RESULTS

Interactions between diagnosis and age were detected in the superior occipital gyrus within the visual network, medial prefrontal cortex, posterior cingulate gyrus, and inferior parietal lobule within the default mode network, which is positively correlated with hyperactivity/impulsivity severity in ADHD. Main effect of diagnosis exhibited a general higher cortico-striatal causal connectivity involving default mode network, frontoparietal network and somatomotor network in ADHD compared with comparisons. Results from high-order effective connectivity exhibited a disrupted information pathway involving the default mode-striatum-somatomotor-striatum-frontoparietal networks in ADHD.

CONCLUSION

The interactions detected in the visual-striatum-default mode networks pathway appears to be related to the potential distraction caused by long-term abnormal information input from the retina in ADHD. Higher causal connectivity and weakened intermodulation may indicate the pathophysiological process that distractions lead to the impairment of motion planning function and the inhibition/control of this unplanned motion signals in ADHD.

Resting-state brain network connectivity is an independent predictor of responsiveness to language therapy in chronic post-stroke aphasia

Post-stroke aphasia recovery, especially in the chronic phase, is challenging to predict. Functional integrity of the brain and brain network topology have been suggested as biomarkers of language recovery. This study sought to investigate functional connectivity in four predefined brain networks (i.e., language, default mode, dorsal attention, and salience networks), in relation to aphasia severity and response to language therapy. Thirty patients with chronic post-stroke aphasia were recruited and received a treatment targeting word finding. Structural and functional brain scans were acquired at baseline and resting state functional connectivity for each network was calculated. Additionally, graph measures quantifying network properties were calculated for each network. These included global efficiency for all networks and average strength and clustering coefficient for the language network. Linear mixed effects models showed that mean functional connectivity in the default mode, dorsal attention, and salience networks as well as graph measures of all four networks are independent predictors of response to therapy. While greater mean functional connectivity and global efficiency of the dorsal attention and salience networks predicted greater treatment response, greater mean functional connectivity and global efficiency in the default mode network predicted poorer treatment response. Results for the language network were more nuanced with more efficient network configurations (as reflected in graph measures), but not mean functional connectivity, predicting greater treatment response. These findings highlight the prognostic value of resting-state functional connectivity in chronic treatment-induced aphasia recovery.

Brain functional changes across mood states in bipolar disorder: from a large-scale network perspective

BACKGROUND

Exploring the neural basis related to different mood states is a critical issue for understanding the pathophysiology underlying mood switching in bipolar disorder (BD), but research has been scarce and inconsistent.

METHODS

Resting-state functional magnetic resonance imaging data were acquired from 162 patients with BD: 33 (hypo)manic, 64 euthymic, and 65 depressive, and 80 healthy controls (HCs). The differences of large-scale brain network functional connectivity (FC) between the four groups were compared and correlated with clinical characteristics. To validate the generalizability of our findings, we recruited a small longitudinal independent sample of BD patients (n = 11). In addition, we examined topological nodal properties across four groups as exploratory analysis.

RESULTS

A specific strengthened pattern of network FC, predominantly involving the default mode network (DMN), was observed in (hypo)manic patients when compared with HCs and bipolar patients in other mood states. Longitudinal observation revealed an increase in several network FCs in patients during (hypo)manic episode. Both samples evidenced an increase in the FC between the DMN and ventral attention network, and between the DMN and limbic network (LN) related to (hypo)mania. The altered network connections were correlated with mania severity and positive affect. Bipolar depressive patients exhibited decreased FC within the LN compared with HCs. The exploratory analysis also revealed an increase in degree in (hypo)manic patients.

CONCLUSIONS

Our findings identify a distributed pattern of large-scale network disturbances in the unique context of (hypo)mania and thus provide new evidence for our understanding of the neural mechanism of BD.

Visual stimulation by extensive visual media consumption can be beneficial for motor learning

In this randomized controlled intervention trial, we investigated whether intense visual stimulation through television watching can enhance visual information processing and motor learning performance. 74 healthy young adults were trained in a motor skill with visual information processing demands while being accommodated in a controlled environment for five days. The experimental manipulation (n = 37) consisted of prolonged television watching (i.e., 8 h/day, + 62.5% on average) to induce intense exposure to visual stimulation. The control group (n = 37) did not consume visual media. The groups were compared by motor learning performance throughout the study as well as pre/post visual attention parameters and resting-state network connectivity in functional MRI. We found that the intervention group performed significantly better in the motor learning task (+ 8.21% (95%-CI[12.04, 4.31], t(70) = 4.23, p < 0.001) while showing an increased capacity of visual short-term memory (+ 0.254, t(58) = - 3.19, p = 0.002) and increased connectivity between visual and motor-learning associated resting-state networks. Our findings suggest that the human brain might enter a state of accentuated visuomotor integration to support the implementation of motor learning with visual information processing demands if challenged by ample input of visual stimulation. Further investigation is needed to evaluate the persistence of this effect regarding participants exposed to accustomed amounts of visual media consumption.Clinical Trials Registration: This trial was registered in the German Clinical Trials Register/Deutsches Register klinischer Studien (DRKS): DRKS00019955.

Selectively predicting the onset of ADHD, oppositional defiant disorder, and conduct disorder in early adolescence with high accuracy

Introduction

The externalizing disorders of attention deficit hyperactivity disorder (ADHD), oppositional defiant disorder (ODD), and conduct disorder (CD) are common in adolescence and are strong predictors of adult psychopathology. While treatable, substantial diagnostic overlap complicates intervention planning. Understanding which factors predict the onset of each disorder and disambiguating their different predictors is of substantial translational interest.

Materials and methods

We analyzed 5,777 multimodal candidate predictors from children aged 9-10 years and their parents in the ABCD cohort to predict the future onset of ADHD, ODD, and CD at 2-year follow-up. We used deep learning optimized with an innovative AI algorithm to jointly optimize model training, perform automated feature selection, and construct individual-level predictions of illness onset and all prevailing cases at 11-12 years and examined relative predictive performance when candidate predictors were restricted to only neural metrics.

Results

Multimodal models achieved ~86-97% accuracy, 0.919-0.996 AUROC, and ~82-97% precision and recall in testing in held-out, unseen data. In neural-only models, predictive performance dropped substantially but nonetheless achieved accuracy and AUROC of ~80%. Parent aggressive and externalizing traits uniquely differentiated the onset of ODD, while structural MRI metrics in the limbic system were specific to CD. Psychosocial measures of sleep disorders, parent mental health and behavioral traits, and school performance proved valuable across all disorders. In neural-only models, structural and functional MRI metrics in subcortical regions and cortical-subcortical connectivity were emphasized. Overall, we identified a strong correlation between accuracy and final predictor importance.

Conclusion

Deep learning optimized with AI can generate highly accurate individual-level predictions of the onset of early adolescent externalizing disorders using multimodal features. While externalizing disorders are frequently co-morbid in adolescents, certain predictors were specific to the onset of ODD or CD vs. ADHD. To our knowledge, this is the first machine learning study to predict the onset of all three major adolescent externalizing disorders with the same design and participant cohort to enable direct comparisons, analyze >200 multimodal features, and include many types of neuroimaging metrics. Future study to test our observations in external validation data will help further test the generalizability of these findings.

Resting state correlates of picture description informativeness in left vs. right hemisphere chronic stroke

Introduction

Despite a growing emphasis on discourse processing in clinical neuroscience, relatively little is known about the neurobiology of discourse production impairments. Individuals with a history of left or right hemisphere stroke can exhibit difficulty with communicating meaningful discourse content, which implies both cerebral hemispheres play a role in this skill. However, the extent to which successful production of discourse content relies on network connections within domain-specific vs. domain-general networks in either hemisphere is unknown.

Methods

In this study, 45 individuals with a history of either left or right hemisphere stroke completed resting state fMRI and the Cookie Theft picture description task.

Results

Participants did not differ in the total number of content units or the percentage of interpretative content units they produced. Stroke survivors with left hemisphere damage produced significantly fewer content units per second than individuals with right hemisphere stroke. Intrinsic connectivity of the left language network was significantly weaker in the left compared to the right hemisphere stroke group for specific connections. Greater efficiency of communication of picture scene content was associated with stronger left but weaker right frontotemporal connectivity of the language network in patients with a history of left hemisphere (but not right hemisphere) stroke. No significant relationships were found between picture description measures and connectivity of the dorsal attention, default mode, or salience networks or with connections between language and other network regions.

Discussion

These findings add to prior behavioral studies of picture description skills in stroke survivors and provide insight into the role of the language network vs. other intrinsic networks during discourse production.

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.

Cross-attractor modeling of resting-state functional connectivity in psychiatric disorders

Resting-state functional connectivity (RSFC) is altered across various psychiatric disorders. Brain network modeling (BNM) has the potential to reveal the neurobiological underpinnings of such abnormalities by dynamically modeling the structure-function relationship and examining biologically relevant parameters after fitting the models with real data. Although innovative BNM approaches have been developed, two main issues need to be further addressed. First, previous BNM approaches are primarily limited to simulating noise-driven dynamics near a chosen attractor (or a stable brain state). An alternative approach is to examine multi(or cross)-attractor dynamics, which can be used to better capture non-stationarity and switching between states in the resting brain. Second, previous BNM work is limited to characterizing one disorder at a time. Given the large degree of co-morbidity across psychiatric disorders, comparing BNMs across disorders might provide a novel avenue to generate insights regarding the dynamical features that are common across (vs. specific to) disorders. Here, we address these issues by (1) examining the layout of the attractor repertoire over the entire multi-attractor landscape using a recently developed cross-attractor BNM approach; and (2) characterizing and comparing multiple disorders (schizophrenia, bipolar, and ADHD) with healthy controls using an openly available and moderately large multimodal dataset from the UCLA Consortium for Neuropsychiatric Phenomics. Both global and local differences were observed across disorders. Specifically, the global coupling between regions was significantly decreased in schizophrenia patients relative to healthy controls. At the same time, the ratio between local excitation and inhibition was significantly higher in the schizophrenia group than the ADHD group. In line with these results, the schizophrenia group had the lowest switching costs (energy gaps) across groups for several networks including the default mode network. Paired comparison also showed that schizophrenia patients had significantly lower energy gaps than healthy controls for the somatomotor and visual networks. Overall, this study provides preliminary evidence supporting transdiagnostic multi-attractor BNM approaches to better understand psychiatric disorders' pathophysiology.

Fronto-parietal white matter microstructure associated with working memory performance in children with ADHD

INTRODUCTION

Attention Deficit/Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder with many functional impairments thought to be underpinned by difficulties in executive function domains such as working memory. The superior longitudinal fasciculus (SLF) plays an integral role in the development of working memory in neurotypical children. Neuroimaging research suggests reduced white matter organization of the SLF may contribute to working memory difficulties commonly seen in ADHD. This study aimed to examine the relationship between white matter organization of the SLF and working memory in children with ADHD.

METHODS

We examined the association of tract volume and apparent fibre density (AFD) of the SLF with working memory in children with ADHD (n = 64) and controls (n = 58) aged 9-11years. Children completed a computerized spatial n-back task and underwent diffusion magnetic resonance imaging (dMRI). Constrained spherical deconvolution-based tractography was used to construct the three branches of the SLF bilaterally and examine volume and AFD of the SLF.

RESULTS

Regression analyses revealed children with ADHD exhibited poorer working memory, and lower volume and AFD of the left SLF-II compared to healthy controls. There was also an association between reaction time and variability (RT and RT-V) and the left SLF-II. Further analyses revealed volume of the left SLF-II mediated the relationship between ADHD and working memory performance (RT and RT-V).

DISCUSSION

These findings add to the current body of ADHD literature, revealing the potential role of frontoparietal white matter in working memory difficulties in ADHD.

Distinctively different human neurobiological responses after trauma exposure and implications for posttraumatic stress disorder subtyping

Trauma elicits various adaptive and maladaptive responses among all exposed people. There may be distinctively different patterns of adaptation/maladaptation or types according to neurobiological predisposition. The present study aims to dissect the heterogeneity of posttraumatic conditions in order to identify clinically meaningful subtypes in recently traumatized individuals and evaluate their neurobiological correlates and long-term prognosis. We implemented a data-driven classification approach in both discovery (n = 480) and replication (n = 220) datasets of trauma-exposed and trauma-unexposed individuals based on the clinical data across a wide range of assessments. Subtype-specific patterns of functional connectivity in higher-order cortical networks, longitudinal clinical outcomes, and changes in functional connectivity were also evaluated. We identified four distinct and replicable subtypes for trauma-exposed individuals according to posttraumatic stress symptoms. Each subtype was distinct in clinical characteristics, brain functional organization, and long-term trajectories for posttraumatic symptoms. These findings help enhance current understanding of mechanisms underlying the human-specific heterogeneous responses to trauma. Furthermore, this study contributes data towards the development of improved interventions, including targeting of subtype-specific characteristics, for trauma-exposed individuals and those with PTSD.

EEG Connectivity in ADHD Compared to a Normative Database: A Cohort Analysis of 120 Subjects from the ICAN Study

This study explores how EEG connectivity measures in children with ADHD ages 7-10 (n = 140) differ from an age-matched nonclinical database. We differentiated connectivity in networks, Brodmann area pairs, and frequencies. Subjects were in the International Collaborative ADHD Neurofeedback study, which explored neurofeedback for ADHD. Inclusion criteria were mainly rigorously diagnosed ADHD and a theta/beta power ratio (TBR) ≤ 4.5. Using statistical and machine learning algorithms, connectivity values were extracted in coherence, phase, and lag coherence at all Brodmann, subcortical, and cerebellar areas within the main networks in all EEG frequencies and then compared with a normative database. There is a higher rate of dysregulation (more than ± 1.97SD), in some cases as much as 75%, of the Brodmann pairs observed in coherence and phase between BAs 7, 10, and 11 with secondary connections from these areas to BAs 21, 30, 35, 37, 39, and 40 in the ADHD children as compared to the normative database. Left and right Brodmann areas 10 and 11 are highly disconnected to each other. The most dysregulated Brodmann Areas in ADHD are 7, 10, and 11, relevant to ADHD executive-function deficits and provide important considerations when developing interventions for ADHD children.

A randomized controlled trial of desvenlafaxine-induced structural brain changes in the treatment of persistent depressive disorder

The anatomical changes that antidepressant medications induce in the brain and through which they exert their therapeutic effects remain largely unknown. We randomized 61 patients with Persistent Depressive Disorder (PDD) to receive either desvenlafaxine or placebo in a 12-week trial and acquired anatomical MRI scans in 42 of those patients at baseline before randomization and immediately at the end of the trial. We also acquired MRIs once in 39 age- and sex-matched healthy controls. We assessed whether the serotonin-norepinephrine reuptake inhibitor, desvenlafaxine, differentially changed cortical thickness during the trial compared with placebo. Patients relative to controls at baseline had thinner cortices across the brain. Although baseline thickness was not associated with symptom severity, thicker baseline cortices predicted greater reduction in symptom severity in those treated with desvenlafaxine but not placebo. We did not detect significant treatment-by-time effects on cortical thickness. These findings suggest that baseline thickness may serve as predictive biomarkers for treatment response to desvenlafaxine. The absence of treatment-by-time effects may be attributable either to use of insufficient desvenlafaxine dosing, a lack of desvenlafaxine efficacy in treating PDD, or the short trial duration.

Systematic bibliometric and visualized analysis of research hotspots and trends in attention-deficit hyperactivity disorder neuroimaging

Introduction

This study focused on the research hotspots and development trends of the neuroimaging of attention deficit hyperactivity disorder (ADHD) in the past thirty years.

Methods

The Web of Science database was searched for articles about ADHD neuroimaging from January 1992 to September 2022. CiteSpace was used to analyze the co-occurrence of keywords in literature, partnerships between authors, institutions, and countries, the sudden occurrence of keywords, clustering of keywords over time, and analysis of references, cited authors, and cited journals.

Results

2,621 articles were included. More and more articles have been published every year in the last years. These articles mainly come from 435 institutions and 65 countries/regions led by the United States. King's College London had the highest number of publications. The study identified 634 authors, among which Buitelaar, J. K. published the largest number of articles and Castellanos, F. X. was co-cited most often. The most productive and cited journal was Biological psychiatry. In recent years, burst keywords were resting-state fMRI, machine learning, functional connectivity, and networks. And a timeline chart of the cluster of keywords showed that “children” had the longest time span.

Conclusions

Increased attention has been paid to ADHD neuroimaging. This work might assist researchers to identify new insight on potential collaborators and cooperative institutions, hot topics, and research directions.

Measures of Brain Connectivity and Cognition by Sex in US Children

IMPORTANCE

The neurobiological underpinnings underlying sex differences in cognition during adolescence are largely unknown.

OBJECTIVE

To examine sex differences in brain circuitry and their association with cognitive performance in US children.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study analyzed behavioral and imaging data from 9- to 11-year-old children from the Adolescent Brain Cognitive Development (ABCD) study between August 2017 and November 2018. The ABCD study is an open-science, multisite study following up more than 11 800 youths into early adulthood for 10 years with annual laboratory-based assessments and biennial magnetic resonance imaging (MRI). The selection of ABCD study children for the current analysis was based on the availability of functional and structural MRI data sets in ABCD Brain Imaging Data Structure Community Collection format. Five hundred and sixty participants who had excessive level of head motion (>50% of time points with framewise displacement >0.5 mm) during resting-state functional MRI were excluded from the analyses. Data were analyzed between January and August 2022.

MAIN OUTCOMES AND MEASURES

The main outcomes were the sex differences in (A) global functional connectivity density at rest and (B) mean water diffusivity (MD) and (C) the correlation of these metrics with total cognitive scores.

RESULTS

A total of 8961 children (4604 boys and 4357 girls; mean [SD] age, 9.92 [0.62] years) were included in this analysis. Girls had higher functional connectivity density in default mode network hubs than boys, predominantly in the posterior cingulate cortex (Cohen d = -0.36), and lower MD and transverse diffusivity, predominantly in the superior corticostriatal white matter bundle (Cohen d = 0.3). Age-corrected fluid and total composite scores were higher for girls than for boys (Cohen d = -0.08 [fluid] and -0.04 [total]; P = 2.7 × 10-5). Although total mean (SD) brain volume (1260 [104] mL in boys and 1160 [95] mL in girls; t = 50; Cohen d = 1.0; df = 8738) and the proportion of white matter (d = 0.4) were larger for boys than for girls, the proportion of gray matter was larger for girls than for boys (d = -0.3; P = 2.2 × 10-16).

CONCLUSIONS AND RELEVANCE

The findings of this cross-sectional study on sex differences in brain connectivity and cognition are relevant to the future creation of brain developmental trajectory charts to monitor for deviations associated with impairments in cognition or behavior, including those due to psychiatric or neurological disorders. They could also serve as a framework for studies investigating the differential contribution of biological vs social or cultural factors in the neurodevelopmental trajectories of girls and boys.

The subcortical and neurochemical organization of the ventral and dorsal attention networks

Attention is a core cognitive function that filters and selects behaviourally relevant information in the environment. The cortical mapping of attentional systems identified two segregated networks that mediate stimulus-driven and goal-driven processes, the Ventral and the Dorsal Attention Networks (VAN, DAN). Deep brain electrophysiological recordings, behavioral data from phylogenetic distant species, and observations from human brain pathologies challenge purely corticocentric models. Here, we used advanced methods of functional alignment applied to resting-state functional connectivity analyses to map the subcortical architecture of the Ventral and Dorsal Attention Networks. Our investigations revealed the involvement of the pulvinar, the superior colliculi, the head of caudate nuclei, and a cluster of brainstem nuclei relevant to both networks. These nuclei are densely connected structural network hubs, as revealed by diffusion-weighted imaging tractography. Their projections establish interrelations with the acetylcholine nicotinic receptor as well as dopamine and serotonin transporters, as demonstrated in a spatial correlation analysis with a normative atlas of neurotransmitter systems. This convergence of functional, structural, and neurochemical evidence provides a comprehensive framework to understand the neural basis of attention across different species and brain diseases.

Reduced subgenual cingulate-dorsolateral prefrontal connectivity as an electrophysiological marker for depression

Major Depressive Disorder (MDD) is a widespread mental illness that causes considerable suffering, and neuroimaging studies are trying to reduce this burden by developing biomarkers that can facilitate detection. Prior fMRI- and neurostimulation studies suggest that aberrant subgenual Anterior Cingulate (sgACC)-dorsolateral Prefrontal Cortex (DLPFC) functional connectivity is consistently present within MDD. Combining the need for reliable depression markers with the electroencephalogram's (EEG) high clinical utility, we investigated whether aberrant EEG sgACC-DLPFC functional connectivity could serve as a marker for depression. Source-space Amplitude Envelope Correlations (AEC) of 20 MDD patients and 20 matched controls were contrasted using non-parametric permutation tests. In addition, extracted AEC values were used to (a) correlate with characteristics of depression and (b) train a Support Vector Machine (SVM) to determine sgACC-DLPFC connectivity's discriminative power. FDR-thresholded statistical maps showed reduced sgACC-DLPFC AEC connectivity in MDD patients relative to controls. This diminished AEC connectivity is located in the beta-1 (13-17 Hz) band and is associated with patients' lifetime number of depressive episodes. Using extracted sgACC-DLPFC AEC values, the SVM achieved a classification accuracy of 84.6% (80% sensitivity and 89.5% specificity) indicating that EEG sgACC-DLPFC connectivity has promise as a biomarker for MDD.

Electroencephalographic Microstates as Novel Functional Biomarkers for Adult Attention-Deficit/Hyperactivity Disorder

BACKGROUND

Research on the electroencephalographic (EEG) signatures of attention-deficit/hyperactivity disorder (ADHD) has historically concentrated on its frequency spectrum or event-related evoked potentials. In this work, we investigate EEG microstates (MSs), an alternative framework defined by the clustering of recurring topographical patterns, as a novel approach for examining large-scale cortical dynamics in ADHD.

METHODS

Using k-means clustering, we studied the spatiotemporal dynamics of ADHD during the rest condition by comparing the MS segmentations between adult patients with ADHD and neurotypical control subjects across two independent datasets: the first dataset consisted of 66 patients with ADHD and 66 control subjects, and the second dataset comprised 22 patients with ADHD and 22 control subjects and was used for out-of-sample validation.

RESULTS

Spatially, patients with ADHD and control subjects displayed equivalent MS topographies (canonical maps), indicating the preservation of prototypical EEG generators in patients with ADHD. However, this concordance was accompanied by significant differences in temporal dynamics. At the group level, and across both datasets, ADHD diagnosis was associated with longer mean durations of a frontocentral topography (MS D), indicating that its electrocortical generator(s) could be acting as pronounced attractors of global cortical dynamics. In addition, its spatiotemporal metrics were correlated with sleep disturbance, the latter being known to have a strong relationship with ADHD. Finally, in the first (larger) dataset, we also found evidence of decreased time coverage and mean duration of a left-right diagonal topography (MS A), which inversely correlated with ADHD scores.

CONCLUSIONS

Overall, our study underlines the value of EEG MSs as promising functional biomarkers for ADHD, offering an additional lens through which to examine its neurophysiological mechanisms.

Shared intrinsic functional connectivity alterations as a familial risk marker for ADHD: a resting-state functional magnetic resonance imaging study with sibling design

BACKGROUND

Although aberrant intrinsic functional connectivity has been reported in attention-deficit/hyperactivity disorder (ADHD), we have a limited understanding of whether connectivity alterations are related to the familial risk of ADHD.

METHODS

Fifty-three probands with ADHD, their unaffected siblings (n = 53) and typically developing controls (n = 53) underwent resting-state functional magnetic resonance imaging scans. A seed-based approach with the bilateral precuneus/posterior cingulate cortex (PCC) was used to derive a whole-brain functional connectivity map in each subject. The differences in functional connectivity among the three groups were tested with one-way ANOVA using randomized permutation. Comparisons between two groups were also performed to examine the increase or decrease in connectivity. The severity of ADHD symptoms was used to identify brain regions where symptom severity is correlated to the strength of intrinsic functional connectivity.

RESULTS

When compared to controls, both probands and unaffected siblings showed increased functional connectivity in the left insula and left inferior frontal gyrus. The connectivity in these regions was linked to better performance in response inhibition in the control group but absent in other groups. Higher ADHD symptom severity was correlated with increased functional connectivity in bilateral fronto-parietal-temporal regions only noted in probands with ADHD.

CONCLUSIONS

Alterations in resting-state functional connectivities with the precuneus/PCC, hubs of default-mode network, account for the underlying familial risks of ADHD. Since the left insula and left inferior frontal gyri are key regions of the salience and frontoparietal network, respectively, future studies focusing on alterations of cross-network functional connectivity as the familial risk of ADHD are suggested.

The potential shared brain functional alterations between adults with ADHD and children with ADHD co-occurred with disruptive behaviors

BACKGROUND

Attention-deficit/hyperactivity disorder (ADHD) is a common neurodevelopmental disorder. Many previous studies have shown that the comorbid status of disruptive behaviour disorders (DBD) was a predictor for ADHD persistence into adulthood. However, the brain mechanisms underlying such a relationship remain unclear. Thus, we aim to investigate whether the brain functional alteration in adults with ADHD could also be detected in children with ADHD co-occurring with disruptive behaviours from both quantitative and categorical dimensions.

METHODS

A total of 172 children with ADHD (cADHD), 98 adults with ADHD (aADHD), 77 healthy control children (cHC) and 40 healthy control adults (aHC) were recruited. The whole-brain spontaneous fluctuations in brain activity of each participant were recorded using functional near-infrared spectroscopy (fNIRS), and the functional connectivities (FCs) were calculated. We first compared the FC differences between aADHD and aHC. Then, for the regions with significantly abnormal FCs in aADHD, we further compared these features between cADHD and cHC. In addition, the correlation between these FCs and the conduct disorder (CD)/oppositional defiant disorder (ODD) symptoms were analysed in cADHD. Moreover, to render the results readily interpretable, we compared the FC differences among ADHD_CD-, subthreshold ADHD_CD+ and cHC groups, and among ADHD_ODD-, ADHD_ODD+ and cHC groups. Finally, we repeated the above analysis after controlling for other comorbidities and core symptoms to diminish the potential confounding effects.

RESULTS

We found that compared with aHC, aADHD showed significantly increased FCs in the VN, DMN, SMN, and DAN. The aforementioned abnormal FCs were also detected in cADHD, however, in an opposite orientation. Notably, these abnormal FCs were positively correlated with CD symptoms. Finally, the subthreshold ADHD_CD+ group even exhibited a tendency of adult-like increased FCs compared with the cHC. The results held after controlling for other comorbidities and core symptoms.

CONCLUSION

This study provides functional neuroimaging evidence that CD might be a risk factor for ADHD persistence into adulthood. Our work highlights the importance of differentiating ADHD_CD+ from ADHD and inspiring further understanding of brain development in ADHD.

Lifespan associations of resting-state brain functional networks with ADHD symptoms

Attention-deficit/hyperactivity disorder (ADHD) is increasingly being diagnosed in both children and adults, but the neural mechanisms that underlie its distinct symptoms and whether children and adults share the same mechanism remain poorly understood. Here, we used a nested-spectral partition approach to study resting-state brain networks of ADHD patients (n = 97) and healthy controls (HCs, n = 97) across the lifespan (7–50 years). Compared to the linear lifespan associations of brain segregation and integration with age in HCs, ADHD patients have a quadratic association in the whole-brain and in most functional systems, whereas the limbic system dominantly affected by ADHD has a linear association. Furthermore, the limbic system better predicts hyperactivity, and the salient attention system better predicts inattention. These predictions are shared in children and adults with ADHD. Our findings reveal a lifespan association of brain networks with ADHD and provide potential shared neural bases of distinct ADHD symptoms in children and adults.

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ADHD patients have a quadratic association with age in brain functional networks

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Limbic system better predicts hyperactivity across the lifespan

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Salient attention system better predicts the inattention across the lifespan

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The predictions on symptom scores are shared in ADHD children and adults

Frontal corticostriatal functional connectivity reveals task positive and negative network dysregulation in relation to ADHD, sex, and inhibitory control

Frontal corticostriatal circuits (FCSC) are involved in self-regulation of cognition, emotion, and motor function. While these circuits are implicated in attention-deficit/hyperactivity disorder (ADHD), the literature establishing FCSC associations with ADHD is inconsistent. This may be due to study variability in considerations of how fMRI motion regression was handled between groups, or study specific differences in age, sex, or the striatal subregions under investigation. Given the importance of these domains in ADHD it is crucial to consider the complex interactions of age, sex, striatal subregions and FCSC in ADHD presentation and diagnosis. In this large-scale study of 362 8-12 year-old children with ADHD (n = 165) and typically developing (TD; n = 197) children, we investigate associations between FCSC with ADHD diagnosis and symptoms, sex, and go/no-go (GNG) task performance. Results include: (1) increased striatal connectivity with age across striatal subregions with most of the frontal cortex, (2) increased frontal-limbic striatum connectivity among boys with ADHD only, mostly in default mode network (DMN) regions not associated with age, and (3) increased frontal-motor striatum connectivity to regions of the DMN were associated with greater parent-rated inattention problems, particularly among the ADHD group. Although diagnostic group differences were no longer significant when strictly controlling for head motion, with motion possibly reflecting the phenotypic variance of ADHD itself, the spatial distribution of all symptom, age, sex, and other ADHD group effects were nearly identical to the initial results. These results demonstrate differential associations of FCSC between striatal subregions with the DMN and FPN in relation to age, ADHD, sex, and inhibitory control.

A Novel Constrained Non-negative Matrix Factorization Method for Group Functional Magnetic Resonance Imaging Data Analysis of Adult Attention-Deficit/Hyperactivity Disorder

Attention-deficit/hyperactivity disorder (ADHD) is a common childhood psychiatric disorder that often persists into adulthood. Extracting brain networks from functional magnetic resonance imaging (fMRI) data can help explore neurocognitive disorders in adult ADHD. However, there is still a lack of effective methods to extract large-scale brain networks to identify disease-related brain network changes. Hence, this study proposed a spatial constrained non-negative matrix factorization (SCNMF) method based on the fMRI real reference signal. First, non-negative matrix factorization analysis was carried out on each subject to select the brain network components of interest. Subsequently, the available spatial prior information was mined by integrating the interested components of all subjects. This prior constraint was then incorporated into the NMF objective function to improve its efficiency. For the sake of verifying the effectiveness and feasibility of the proposed method, we quantitatively compared the SCNMF method with other classical algorithms and applied it to the dynamic functional connectivity analysis framework. The algorithm successfully extracted ten resting-state brain functional networks from fMRI data of adult ADHD and healthy controls and found large-scale brain network changes in adult ADHD patients, such as enhanced connectivity between executive control network and right frontoparietal network. In addition, we found that older ADHD spent more time in the pattern of relatively weak connectivity. These findings indicate that the method can effectively extract large-scale functional networks and provide new insights into understanding the neurobiological mechanisms of adult ADHD from the perspective of brain networks.

An examination of the relationships between attention/deficit hyperactivity disorder symptoms and functional connectivity over time

Previous cross-sectional work has demonstrated resting-state connectivity abnormalities in children and adolescents with attention/deficit hyperactivity disorder (ADHD) relative to typically developing controls. However, it is unclear to what extent these neural abnormalities confer risk for later symptoms of the disorder, or represent the downstream effects of symptoms on functional connectivity. Here, we studied 167 children and adolescents (mean age at baseline = 10.74 years (SD = 2.54); mean age at follow-up = 13.3 years (SD = 2.48); 56 females) with varying levels of ADHD symptoms, all of whom underwent resting-state functional magnetic resonance imaging and ADHD symptom assessments on two occasions during development. Resting-state functional connectivity was quantified using eigenvector centrality mapping. Using voxelwise cross-lag modeling, we found that less connectivity at baseline within right inferior frontal gyrus was associated with more follow-up symptoms of inattention (significant at an uncorrected cluster-forming threshold of p ≤ 0.001 and a cluster-level familywise error corrected threshold of p < 0.05). Findings suggest that previously reported cross-sectional abnormalities in functional connectivity within inferior frontal gyrus in patients with ADHD may represent a longitudinal risk factor for the disorder, in line with efforts to target this region with novel therapeutic methods.

Dynamic Functional Connectivity Alterations and Their Associated Gene Expression Pattern in Autism Spectrum Disorders

Autism spectrum disorders (ASDs) are a group of heterogeneous neurodevelopmental disorders that are highly heritable and are associated with impaired dynamic functional connectivity (DFC). However, the molecular mechanisms behind DFC alterations remain largely unknown. Eighty-eight patients with ASDs and 87 demographically matched typical controls (TCs) from the Autism Brain Imaging Data Exchange II database were included in this study. A seed-based sliding window approach was then performed to investigate the DFC changes in each of the 29 seeds in 10 classic resting-state functional networks and the whole brain. Subsequently, the relationships between DFC alterations in patients with ASDs and their symptom severity were assessed. Finally, transcription-neuroimaging association analyses were conducted to explore the molecular mechanisms of DFC disruptions in patients with ASDs. Compared with TCs, patients with ASDs showed significantly increased DFC between the right dorsolateral prefrontal cortex (DLPFC) and left fusiform/lingual gyrus, between the DLPFC and the superior temporal gyrus, between the right frontal eye field (FEF) and left middle frontal gyrus, between the FEF and the right angular gyrus, and between the left intraparietal sulcus and the right middle temporal gyrus. Moreover, significant relationships between DFC alterations and symptom severity were observed. Furthermore, the genes associated with DFC changes in ASDs were identified by performing gene-wise across-sample spatial correlation analysis between gene expression extracted from six donors’ brain of the Allen Human Brain Atlas and case-control DFC difference. In enrichment analysis, these genes were enriched for processes associated with synaptic signaling and voltage-gated ion channels and calcium pathways; also, these genes were highly expressed in autistic disorder, chronic alcoholic intoxication and several disorders related to depression. These results not only demonstrated higher DFC in patients with ASDs but also provided novel insight into the molecular mechanisms underlying these alterations.

Time of onset and/or diagnosis of ADHD in European children: a systematic review

BACKGROUND

Attention-Deficit/ Hyperactivity Disorder (ADHD) is one of the most common childhood neurobehavioral conditions. Symptoms related to this disorder cause a significant impairment in school tasks and in the activities of children's daily lives; an early diagnosis and appropriate treatment could almost certainly help improve their outcomes. The current study, part of the Models Of Child Health Appraised (MOCHA) project, aims to explore the age at which children experience the onset or diagnosis of ADHD in European countries.

METHODS

A systematic review was done examining the studies reporting the age of onset/diagnosis (AO/AD) of ADHD in European countries (28 European Member States plus 2 European Economic Area countries), published between January 1, 2010 and December 31, 2019. Of the 2276 identified studies, 44 met all the predefined criteria and were included in the review.

RESULTS

The lowest mean AO in the children diagnosed with ADHD alone was 2.25 years and the highest was 7.5 years. It was 15.3 years in the children with ADHD and disruptive behaviour disorder. The mean AD ranges between 6.2 and 18.1 years.

CONCLUSIONS

Our findings indicate that there is a wide variability in both the AO and AD of ADHD, and a too large distance between AO and AD. Since studies in the literature suggest that an early identification of ADHD symptoms may facilitate early referral and treatment, it would be important to understand the underlying reasons behind the wide variability found.

TRIAL REGISTRATION

PROSPERO registration: CRD42017070631 .

Resting state functional connectivity in adolescent synthetic cannabinoid users with and without attention-deficit/hyperactivity disorder

OBJECTIVE

Synthetic cannabinoids (SCs) have become increasingly popular in recent years, especially among adolescents. The first aim of the current study was to examine resting-state functional connectivity (rsFC) in SC users compared to controls. Our second aim was to examine the influence of comorbid attention-deficit/hyperactivity disorder (ADHD) symptomatology on rsFC changes in SC users compared to controls.

METHODS

Resting-state functional magnetic resonance imaging (fMRI) analysis included 25 SC users (14 without ADHD and 11 with ADHD combined type) and 12 control subjects.

RESULTS

We found (i) higher rsFC between the default mode network (DMN) and salience network, dorsal attention network and cingulo-opercular network, and (ii) lower rsFC within the DMN and between the DMN and visual network in SC users compared to controls. There were no significant differences between SC users with ADHD and controls, nor were there any significant differences between SC users with and without ADHD.

CONCLUSIONS

We found the first evidence of abnormalities within and between resting state networks in adolescent SC users without ADHD. In contrast, SC users with ADHD showed no differences compared to controls. These results suggest that comorbidity of ADHD and substance dependence may show different rsFC alterations than substance use alone.

Inhibition-related modulation of salience and frontoparietal networks predicts cognitive control ability and inattention symptoms in children with ADHD

Attention-deficit hyperactivity disorder (ADHD) is associated with pervasive impairments in attention and cognitive control. Although brain circuits underlying these impairments have been extensively investigated with resting-state fMRI, little is known about task-evoked functional brain circuits and their relation to cognitive control deficits and inattention symptoms in children with ADHD. Children with ADHD and age, gender and head motion matched typically developing (TD) children completed a Go/NoGo fMRI task. We used multivariate and dimensional analyses to investigate impairments in two core cognitive control systems: (i) cingulo-opercular "salience" network (SN) anchored in the right anterior insula, dorsal anterior cingulate cortex (rdACC), and ventrolateral prefrontal cortex (rVLPFC) and (ii) dorsal frontoparietal "central executive" (FPN) network anchored in right dorsolateral prefrontal cortex (rDLPFC) and posterior parietal cortex (rPPC). We found that multivariate patterns of task-evoked effective connectivity between brain regions in SN and FPN distinguished the ADHD and TD groups, with rDLPFC-rPPC connectivity emerging as the most distinguishing link. Task-evoked rdACC-rVLPFC connectivity was positively correlated with NoGo accuracy, and negatively correlated with severity of inattention symptoms. Brain-behavior relationships were robust against potential age, gender, and head motion confounds. Our findings highlight aberrancies in task-evoked modulation of SN and FPN connectivity in children with ADHD. Crucially, cingulo-frontal connectivity was a common locus of deficits in cognitive control and clinical measures of inattention symptoms. Our study provides insights into a parsimonious systems neuroscience model of cognitive control deficits in ADHD, and suggests specific circuit biomarkers for predicting treatment outcomes in childhood ADHD.

Comparison of brain activity within the sensorimotor network between sports players and patients with somatic symptom disorder

OBJECTIVE

We aimed to identify differences in brain functional connectivity (FC) and characteristics of body sensation between sports players and patients with somatic symptom disorder (SSD), in order to investigate the neurobiological basis of SSD.

METHODS

Thirty-five sports players (SPORTS group), 36 patients with SSD (SOM group), and 33 healthy control participants (HC group) underwent resting-state functional magnetic resonance imaging. We used a seed-based FC analysis.

RESULTS

Both groups showed increased brain activity in the left precuneus. The level of body intelligence in the SPORTS group and the level of somatosensory amplification in the SOM group were positively correlated with brain activity in the left precuneus. The SPORTS group showed increased FC between the left precuneus and the right/left insula compared to the HC group. The SOM group showed increased FC between the left precuneus and the right parahippocampal gyrus compared to the HC group. The SPORTS group showed increased FC between the left precuneus and left posterior cingulate gyrus compared to the SOM group.

CONCLUSION

Increased FC between the precuneus within the default mode network (DMN) and the insula connected to the sensorimotor network in sports players may be related to better somatosensory functions. In contrast, increased FC between the precuneus of the DMN and the parahippocampal gyrus of the affective network in SSD may be associated with dysfunctional processing and misconception of information. Future studies should examine whether treatments for improving affective processing normalize the affective network, and if this is correlated with somatic symptom improvement.

Atypical resting-state gamma band trajectory in adult attention deficit/hyperactivity disorder

Decreased gamma activity has been reported both in children and adults with attention deficit/hyperactivity disorder (ADHD). However, while ADHD is a lifelong neurodevelopmental disorder, our insight into the associations of spontaneous gamma band activity with age is limited, especially in adults. Therefore, we conducted an explorative study to investigate trajectories of resting gamma activity in adult ADHD patients (N = 42) versus matched healthy controls (N = 59). We investigated the relationship of resting gamma activity (30–48 Hz) with age in four right hemispheric electrode clusters where diminished gamma power in ADHD had previously been demonstrated by our group. We found significant non-linear association between resting gamma power and age in the lower frequency gamma₁ range (30–39 Hz) in ADHD as compared to controls in all investigated locations. Resting gamma₁ increased with age and was significantly lower in ADHD than in control subjects from early adulthood. We found no significant association between gamma activity and age in the gamma₂ range (39–48 Hz). Alterations of gamma band activity might reflect altered cortical network functioning in adult ADHD relative to controls. Our results reveal that abnormal gamma power is present at all ages, highlighting the lifelong nature of ADHD. Nonetheless, longitudinal studies are needed to confirm our results.

Detecting network anomalies using Forman-Ricci curvature and a case study for human brain networks

We analyze networks of functional correlations between brain regions to identify changes in their structure caused by Attention Deficit Hyperactivity Disorder (adhd). We express the task for finding changes as a network anomaly detection problem on temporal networks. We propose the use of a curvature measure based on the Forman–Ricci curvature, which expresses higher-order correlations among two connected nodes. Our theoretical result on comparing this Forman–Ricci curvature with another well-known notion of network curvature, namely the Ollivier–Ricci curvature, lends further justification to the assertions that these two notions of network curvatures are not well correlated and therefore one of these curvature measures cannot be used as an universal substitute for the other measure. Our experimental results indicate nine critical edges whose curvature differs dramatically in brains of adhd patients compared to healthy brains. The importance of these edges is supported by existing neuroscience evidence. We demonstrate that comparative analysis of curvature identifies changes that more traditional approaches, for example analysis of edge weights, would not be able to identify.

Altered cortical functional network in drug-naive adult male patients with attention-deficit hyperactivity disorder: A resting-state electroencephalographic study

Relatively little is known about the neurophysiology of adult Attention-deficit/hyperactivity disorder (ADHD). Brain network analysis can yield important insights into the neuropathology in adult ADHD. The objective of this study was to investigate source-level cortical functional network using resting-state electroencephalography (EEG) in drug-naive adult patients with ADHD. Resting-state EEG was performed for 30 adult male patients with ADHD and 27 male healthy controls. Source-level weighted functional networks based on graph theory were evaluated, including strength, clustering coefficient (CC) and path length (PL) in six frequency bands. At the global level, strength (η² = 0.167) and CC (η² = 0.156) were lower while PL (η² = 0.159) was higher for the high beta band in the ADHD patient group compared to healthy controls. At the nodal level, CCs of the high beta band were lower in the left middle temporal gyrus (η² = 0.244), right inferior occipital cortex (η² = 0.214), right posterior transverse collateral sulcus (η² = 0.237), and right anterior occipital sulcus (η² = 0.251) for the adult ADHD group. Furthermore, the nodal-level high beta band CCs of the left middle temporal gyrus and right anterior occipital sulcus were significantly negatively correlated with ADHD symptoms. The altered cortical functional network showed inefficient connectivity in the left middle temporal gyrus, belonging to the default mode network, the right inferior occipital cortex, belonging to the extrastriate visual resting state network, the right posterior transverse collateral sulcus, belonging to the visual network, and the anterior occipital sulcus, reflecting visual attention, which might affect the pathophysiology of ADHD. Taken together, these attenuated network inefficiencies in adult patients with ADHD may lead to suboptimal information processing and affect symptoms of ADHD, such as inattention and hyperactivity. Our findings should be further replicated using longitudinal study designs.

Functional Connectivity of Attention-Related Networks in Drug-Naïve Children With ADHD

Objective: This study aimed to explore alterations of seed-based functional connectivity (FC) in dorsal attention network (DAN), ventral attention network (VAN), and default mode network (DMN) in ADHD children. Method: A voxel-based comparison of FC maps between 46 drug-naïve children with ADHD and 31 healthy controls (HCs) and correlation analysis between connectivity features and behavior were performed. Results: Compared with the HCs, children with ADHD were characterized by hyperconnectivity between DAN and regions of DMN and by hyperconnectivity between DMN and a set of regions involved in somatosensory, visual, and auditory cortices. No significant group different FC was found between VAN and the whole brain. Higher FC between DMN and somatosensory, visual, and auditory cortex was associated with better performance in attention and executive function. Conclusion: The dysregulation of networks in children with ADHD not only involves the DAN and DMN but also the somatosensory, motor, visual, and auditory networks.

Children with attention-deficit/hyperactivity disorder spend more time in hyperconnected network states and less time in segregated network states as revealed by dynamic connectivity analysis

Previous studies in children with attention-deficit/hyperactivity disorder (ADHD) have observed functional brain network disruption on a whole-brain level, as well as on a sub-network level, particularly as related to the default mode network, attention-related networks, and cognitive control-related networks. Given behavioral findings that children with ADHD have more difficulty sustaining attention and more extreme moment-to-moment fluctuations in behavior than typically developing (TD) children, recently developed methods to assess changes in connectivity over shorter time periods (i.e., "dynamic functional connectivity"), may provide unique insight into dysfunctional network organization in ADHD. Thus, we performed a dynamic functional connectivity (FC) analysis on resting state fMRI data from 38 children with ADHD and 79 TD children. We used Hidden semi-Markov models (HSMMs) to estimate six network states, as well as the most probable sequence of states for each participant. We quantified the dwell time, sojourn time, and transition probabilities across states. We found that children with ADHD spent less total time in, and switched more quickly out of, anticorrelated states involving the default mode network and task-relevant networks as compared to TD children. Moreover, children with ADHD spent more time in a hyperconnected state as compared to TD children. These results provide novel evidence that underlying dynamics may drive the differences in static FC patterns that have been observed in ADHD and imply that disrupted FC dynamics may be a mechanism underlying the behavioral symptoms and cognitive deficits commonly observed in children with ADHD.

Resting-state network dysconnectivity in ADHD: A system-neuroscience-based meta-analysis

OBJECTIVES

Neuroimaging studies report altered resting-state functional connectivity in attention deficit/hyperactivity disorder (ADHD) across multiple brain systems. However, there is inconsistency among individual studies.

METHODS

We meta-analyzed seed-based resting state studies of ADHD connectivity within and between four established resting state brain networks (default mode, cognitive control, salience, affective/motivational) using Multilevel Kernel Density Analysis method.

RESULTS

Twenty studies with 944 ADHD patients and 1121 controls were included in the analysis. Compared to controls, ADHD was associated with disrupted within-default mode network (DMN) connectivity - reduced in the core (i.e. posterior cingulate cortex seed) but elevated in the dorsal medial prefrontal cortex sub-system (i.e. temporal pole-inferior frontal gyrus). Connectivity was elevated between nodes in the cognitive control system. When the analysis was restricted to children and adolescents, additional reduced connectivity was detected between DMN and cognitive control and affective/motivational and salience networks.

CONCLUSIONS

Our data are consistent with the hypothesis that paediatric ADHD is a DMN-dysconnectivity disorder with reduced connectivity both within the core DMN sub-system and between that system and a broad set of nodes in systems involved in cognition and motivation.

Brain Network Connectivity and Association with Catechol-O-Methyltransferase Gene Polymorphism in Korean Attention-Deficit Hyperactivity Disorder Children

OBJECTIVE

We sought to determine if the links between and within the default mode network (DMN) and dorsal attention network (DAT) exhibited different conditions according to catechol-O-methyltransferase (COMT) gene polymorphism in relationship to attention-deficit hyperactivity disorder (ADHD) symptoms.

METHODS

Fifty-seven children with ADHD and 48 healthy controls (HCs) were administered an intelligence test, the Children's Depression Inventory, the Korean ADHD rating scale, and continuous performance test. Resting-state brain functional MRI scans were obtained, and COMT genotyping was performed to distinguish valine carriers and methionine homozygotes.

RESULTS

Compared to controls, children with ADHD showed increased ADHD scale scores, increased visual commission errors, and increased functional connectivity (FC) within the DMN and DAT. Compared to all children with ADHD, children with the methionine homozygote and those who were valine carriers showed increased FC within the DMN and DAT and decreased FC between the DMN and DAT. FC within the DMN was also increased in HC valine carriers compared to HC children with the methionine homozygote, and in children with ADHD who were valine carriers compared to HC valine carriers.

CONCLUSION

We observed increased brain connectivity within the DMN and DAT and altered brain connectivity within and between the DMN and DAT associated with COMT polymorphism in children with ADHD.

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.

Shared and distinct resting functional connectivity in children and adults with attention-deficit/hyperactivity disorder

Attention-deficit/hyperactivity disorder (ADHD) often persists into adulthood, with a shift of symptoms including less hyperactivity/impulsivity and more co-morbidity of affective disorders in ADHD_adult. Many studies have questioned the stability in diagnosing of ADHD from childhood to adulthood, and the shared and distinct aberrant functional connectivities (FCs) between ADHD_child and ADHD_adult remain unidentified. We aim to explore shared and distinct FC patterns in ADHD_child and ADHD_adult, and further investigated the cross-cohort predictability using the identified FCs. After investigating the ADHD-discriminative FCs from healthy controls (HCs) in both child (34 ADHD_child, 28 HCs) and adult (112 ADHD_adult,77 HCs) cohorts, we identified both shared and distinct aberrant FC patterns between cohorts and their association with clinical symptoms. Moreover, the cross-cohort predictability using the identified FCs were tested. The ADHD-HC classification accuracies were 84.4% and 81.0% for children and male adults, respectively. The ADHD-discriminative FCs shared in children and adults lie in the intra-network within default mode network (DMN) and the inter-network between DMN and ventral attention network, positively correlated with total scores of ADHD symptoms. Particularly, inter-network FC between somatomotor network and dorsal attention network was uniquely impaired in ADHD_child, positively correlated with hyperactivity index; whereas the aberrant inter-network FC between DMN and limbic network exhibited more adult-specific ADHD dysfunction. And their cross-cohort predictions were 70.4% and 75.6% between each other. This work provided imaging evidence for symptomatic changes and pathophysiological continuity in ADHD from childhood to adulthood, suggesting that FCs may serve as potential biomarkers for ADHD diagnosis.

Methylphenidate Alters Functional Connectivity of Default Mode Network in Drug-Naive Male Adults With ADHD

Objective: This study evaluated the hypothesis that methylphenidate immediate release (MPH-IR) treatment would improve Default Mode Network (DMN) within-connectivity. Method: Resting-state functional connectivity of the main nodes of DMN was evaluated in a highly homogeneous sample of 18 drug-naive male adult participants with ADHD. Results: Comparing resting-state functional connectivity functional magnetic resonance imaging (R-fMRI) scans before and after MPH treatment focusing exclusively on within-DMN connectivity, we evidenced the strengthening of functional connectivity between two nodes of the DMN: posterior cingulate cortex (PCC) and left lateral parietal cortex (LLP). Conclusion: Our results contribute to the further understanding on how MPH affects functional connectivity within DMN of male adults with ADHD and corroborate the hypothesis of ADHD being a delayed neurodevelopmental disorder.

Healthy Subjects With Extreme Patterns of Performance Differ in Functional Network Topology and Benefits From Nicotine

Do subjects with atypical patterns in attentional and executive behaviour show different brain network topology and react differently towards nicotine administration? The efficacy of pro-cognitive drugs like nicotine considerably varies between subjects and previous theoretical and empirical evidence suggest stronger behavioural nicotine effects in subjects with low performance. One problem is, however, how to best define low performance, especially if several cognitive functions are assessed for subject characterisation. We here present a method that used a multivariate, robust outlier detection algorithm to identify subjects with suspicious patterns of performance in attentional and executive functioning. In contrast to univariate approaches, this method is sensitive towards extreme positions within the multidimensional space that do not have to be extreme values in the individual behavioural distributions. The method was applied to a dataset of healthy, non-smoking subjects (n = 34) who were behaviorally characterised by an attention and executive function test on which N = 12 volunteers were classified as outliers. All subjects then underwent a resting-state functional magnetic resonance imaging (fMRI) scan to characterise brain network topology and an experimental behavioural paradigm under placebo and nicotine (7 mg patch) that gauged aspects of attention and executive function. Our results indicate that subjects with an atypical multivariate pattern in attention and executive functioning showed significant differences in nodal brain network integration in visual association and pre-motor brain regions during resting state. These differences in brain network topology significantly predicted larger individual nicotine effects on attentional processing. In summary, the current approach successfully identified a subgroup of healthy volunteers with low behavioural performance who differ in brain network topology and attentional benefit from nicotine.

Impairments of large-scale functional networks in attention-deficit/hyperactivity disorder: a meta-analysis of resting-state functional connectivity

Altered resting-state functional connectivity (rsFC) has been noted in large-scale functional networks in attention-deficit/hyperactivity disorder (ADHD). However, identifying consistent abnormalities of functional networks is difficult due to varied methods and results across studies. To integrate rsFC alterations and search for coherent patterns of intrinsic functional network impairments in ADHD, this research conducts a coordinate-based meta-analysis of voxel-wise seed-based rsFC studies comparing rsFC between ADHD patients and healthy controls. A total of 25 datasets from 21 studies including 700 ADHD patients and 580 controls were analyzed. We extracted the coordinates of seeds and between-group effects. Each seed was then categorized into a seed-network by its location within priori 7-network parcellations. Then, pooled meta-analyses were conducted for the default mode network (DMN), frontoparietal network (FPN) and affective network (AN) separately, but not for the ventral attention network (VAN), dorsal attention network (DAN), somatosensory network (SSN) and visual network due to a lack of primary studies. The results showed that ADHD was characterized by hyperconnectivity between the FPN and regions of the DMN and AN as well as hypoconnectivity between the FPN and regions of the VAN and SSN. These findings not only support the triple-network model of pathophysiology associated with ADHD but also extend this model by highlighting the involvement of the SSN and AN in the mechanisms of network interactions that may account for motor hyperactivity and impulsive symptoms.

Hierarchical integrated and segregated processing in the functional brain default mode network within attention-deficit/hyperactivity disorder

The hierarchical modular organization of functional networks in the brain is crucial for supporting diverse cognitive functions. Functional disorders in the brain are associated with an abnormal hierarchical modular organization. The default mode network (DMN) is a complex dynamic network that is linked to specialized cognitive functions and clinically relevant information. In this study, we hypothesize that hierarchical functional segregation and integration of the DMN within attention-deficit/hyperactivity disorder (ADHD) is abnormal. We investigated topological metrics of both segregation and integration in different hierarchical subnetworks of the DMN between patients with ADHD and healthy controls. We found that the hierarchical functional integration and segregation of the DMN decreased and increased, respectively, in ADHD. Our results also indicated that the abnormalities in the DMN are intrinsically caused by changes in functional segregation and integration in its higher-level subnetworks. To better understand the temporally dynamic changes in the hierarchical functional integration and segregation of the DMN within ADHD, we further analyzed the dynamic transitions between functional segregation and integration. We found that the adaptive reorganizational ability of brain network states decreased in ADHD patients, which indicated less adaptive regulation between the DMN subnetworks in ADHD for supporting correspondingly normal cognitive function. From the perspective of hierarchical functional segregation and integration, our results further provide evidence to support dysfunctional brain cognitive functions within ADHD linked to brain network segregation and integration.

A comparison of efficacy between cognitive behavioral therapy (CBT) and CBT combined with medication in adults with attention-deficit/hyperactivity disorder (ADHD)

The study aimed to explore whether cognitive behavioral therapy (CBT) combined with medication is superior to CBT alone in core symptoms, emotional symptoms, self-esteem as well as social and cognitive functions of adult attention-deficit/hyperactivity disorder (ADHD) patients. Samples from a previous RCT study and outpatient participants were all included. A total of 124 patients received 12 weeks of manualized CBT sessions, either with (n = 57) or without (n = 67) medication. Efficacy variables were evaluated at baseline and each week. Mixed linear models (MLM) were used to compare differences between the two groups in all of the above domains. Within-group comparisons showed that both groups had robust improvements in core ADHD symptoms, emotional symptoms and social functional outcomes. The CBT + M group presented more domains of improvement in executive functions than the CBT group. However, comparisons between groups didn't indicate the superiority of CBT + M in core symptoms, emotional symptoms and self-esteem. Instead, the CBT group showed a greater improvement in the physical domain of the WHOQOL-BREF than the CBT + M group. This study further indicated that CBT is an effective treatment for adults with ADHD. A combination of CBT and medication presented broader improvements in executive functions, but not in clinical symptoms, than CBT alone.

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.

Compulsivity and impulsivity traits linked to attenuated developmental frontostriatal myelination trajectories

The transition from adolescence to adulthood is a period when ongoing brain development coincides with a substantially increased risk of psychiatric disorders. The developmental brain changes accounting for this emergent psychiatric symptomatology remain obscure. Capitalizing on a unique longitudinal dataset that includes in vivo myelin-sensitive magnetization transfer (MT) MRI scans, we show that this developmental period is characterized by brain-wide growth in MT trajectories within both gray matter and adjacent juxtacortical white matter. In this healthy population, the expression of common developmental traits, namely compulsivity and impulsivity, is tied to a reduced growth of these MT trajectories in frontostriatal regions. This reduction is most marked in dorsomedial and dorsolateral prefrontal regions for compulsivity and in lateral and medial prefrontal regions for impulsivity. These findings highlight that psychiatric traits of compulsivity and impulsivity are linked to regionally specific reductions in myelin-related growth in late adolescent brain development.

Towards interpretable machine learning models for diagnosis aid: A case study on attention deficit/hyperactivity disorder

Attention Deficit/Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder that has heavy consequences on a child's wellbeing, especially in the academic, psychological and relational planes. The current evaluation of the disorder is supported by clinical assessment and written tests. A definitive diagnosis is usually made based on the DSM-V criteria. There is a lot of ongoing research on ADHD, in order to determine the neurophysiological basis of the disorder and to reach a more objective diagnosis. The advent of Machine Learning (ML) opens up promising prospects for the development of systems able to predict a diagnosis from phenotypic and neuroimaging data. This was the reason why the ADHD-200 contest was launched a few years ago. Based on the publicly available ADHD-200 collection, participants were challenged to predict ADHD with the best possible predictive accuracy. In the present work, we propose instead a ML methodology which primarily places importance on the explanatory power of a model. Such an approach is intended to achieve a fair trade-off between the needs of performance and interpretability expected from medical diagnosis aid systems. We applied our methodology on a data sample extracted from the ADHD-200 collection, through the development of decision trees which are valued for their readability. Our analysis indicates the relevance of the limbic system for the diagnosis of the disorder. Moreover, while providing explanations that make sense, the resulting decision tree performs favorably given the recent results reported in the literature.

Atypical functional connectivity in adolescents and adults with persistent and remitted ADHD during a cognitive control task

We previously provided initial evidence for cognitive and event-related potential markers of persistence/remission of attention-deficit/hyperactivity disorder (ADHD) from childhood to adolescence and adulthood. Here, using a novel brain-network connectivity approach, we aimed to examine whether task-based functional connectivity reflects a marker of ADHD remission or an enduring deficit unrelated to ADHD outcome. High-density EEG was recorded in a follow-up of 110 adolescents and young adults with childhood ADHD (87 persisters, 23 remitters) and 169 typically developing individuals during an arrow-flanker task, eliciting cognitive control. Functional connectivity was quantified with network-based graph-theory metrics before incongruent (high-conflict) target onset (pre-stimulus), during target processing (post-stimulus) and in the degree of change between pre-stimulus/post-stimulus. ADHD outcome was examined with parent-reported symptoms and impairment using both a categorical (DSM-IV) and a dimensional approach. Graph-theory measures converged in indicating that, compared to controls, ADHD persisters showed increased connectivity in pre-stimulus theta, alpha, and beta and in post-stimulus beta (all p < .01) and reduced pre-stimulus/post-stimulus change in theta connectivity (p < .01). In the majority of indices showing ADHD persister-control differences, ADHD remitters differed from controls (all p < .05) but not from persisters. Similarly, connectivity measures were unrelated to continuous outcome measures of ADHD symptoms and impairment in participants with childhood ADHD. These findings indicate that adolescents and young adults with persistent and remitted ADHD share atypical over-connectivity profiles and reduced ability to modulate connectivity patterns with task demands, compared to controls. Task-based functional connectivity impairments may represent enduring deficits in individuals with childhood ADHD irrespective of diagnostic status in adolescence/young adulthood.