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The science of attention-deficit/hyperactivity disorder (ADHD) is motivated by a translational goal - the discovery and exploitation of knowledge about the nature of ADHD to the benefit of those individuals whose lives it affects. Over the past fifty years, scientific research has made enormous strides in characterizing the ADHD condition and in understanding its correlates and causes. However, the translation of these scientific insights into clinical benefits has been limited. In this review, we provide a selective and focused survey of the scientific field of ADHD, providing our personal perspectives on what constitutes the scientific consensus, important new leads to be highlighted, and the key outstanding questions to be addressed going forward. We cover two broad domains - clinical characterization and, risk factors, causal processes and neuro-biological pathways. Part one focuses on the developmental course of ADHD, co-occurring characteristics and conditions, and the functional impact of living with ADHD - including impairment, quality of life, and stigma. In part two, we explore genetic and environmental influences and putative mediating brain processes. In the final section, we reflect on the future of the ADHD construct in the light of cross-cutting scientific themes and recent conceptual reformulations that cast ADHD traits as part of a broader spectrum of neurodivergence., (© 2022 The Authors. Journal of Child Psychology and Psychiatry published by John Wiley & Sons Ltd on behalf of Association for Child and Adolescent Mental Health.)

Objective: Abnormal cerebellar development has been implicated in attention-deficit/hyperactivity disorder (ADHD), although cerebro-cerebellar functional connectivity (FC) has yet to be examined in ADHD. Our objective is to investigate the disturbed cerebro-cerebellar FC in children and adolescents with ADHD., Method: We analyzed a dataset of 106 individuals with ADHD (68 children, 38 adolescents) and 62 healthy comparison individuals (34 children, 28 adolescents) from the publicly available ADHD-200 dataset. We identified 7 cerebellar subregions based on cerebro-cerebellar FC and subsequently obtained the FC maps of cerebro-cerebellar networks. The main effects of ADHD and age and their interaction were examined using 2-way analysis of variance., Results: Compared to comparisons, ADHD showed higher cerebro-cerebellar FC in the superior temporal gyrus within the somatomotor network. Interactions of diagnosis and age were identified in the supplementary motor area and postcentral gyrus within the somatomotor network and middle temporal gyrus within the ventral attention network. Follow-up Pearson correlation analysis revealed decreased cerebro-cerebellar FC in these regions with increasing age in comparisons, whereas the opposite pattern of increased cerebro-cerebellar FC occurred in ADHD., Conclusion: Increased cerebro-cerebellar FC in the superior temporal gyrus within the somatomotor network could underlie impairments in cognitive control and somatic motor function in ADHD. In addition, increasing cerebro-cerebellar FC in older participants with ADHD suggests that enhanced cerebellar involvement may compensate for dysfunctions of the cerebral cortex in ADHD., (Copyright © 2022 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.)

Background: Morphology of the human cerebral cortex differs across psychiatric disorders, with neurobiology and developmental origins mostly undetermined. Deviations in the tangential growth of the cerebral cortex during pre/perinatal periods may be reflected in individual variations in cortical surface area later in life., Methods: Interregional profiles of group differences in surface area between cases and controls were generated using T1-weighted magnetic resonance imaging from 27,359 individuals including those with attention-deficit/hyperactivity disorder, autism spectrum disorder, bipolar disorder, major depressive disorder, schizophrenia, and high general psychopathology (through the Child Behavior Checklist). Similarity of interregional profiles of group differences in surface area and prenatal cell-specific gene expression was assessed., Results: Across the 11 cortical regions, group differences in cortical area for attention-deficit/hyperactivity disorder, schizophrenia, and Child Behavior Checklist were dominant in multimodal association cortices. The same interregional profiles were also associated with interregional profiles of (prenatal) gene expression specific to proliferative cells, namely radial glia and intermediate progenitor cells (greater expression, larger difference), as well as differentiated cells, namely excitatory neurons and endothelial and mural cells (greater expression, smaller difference). Finally, these cell types were implicated in known pre/perinatal risk factors for psychosis. Genes coexpressed with radial glia were enriched with genes implicated in congenital abnormalities, birth weight, hypoxia, and starvation. Genes coexpressed with endothelial and mural genes were enriched with genes associated with maternal hypertension and preterm birth., Conclusions: Our findings support a neurodevelopmental model of vulnerability to mental illness whereby prenatal risk factors acting through cell-specific processes lead to deviations from typical brain development during pregnancy., (Copyright © 2022 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

The present study seeks to examine individuals' stream of thought in real time. Specifically, we asked participants to speak their thoughts freely out loud during a typical resting-state condition. We first examined the feasibility and reliability of the method and found that the oral reporting method did not significantly change the frequency or content characteristics of self-generated thoughts; moreover, its test-retest reliability was high. Based on methodological feasibility, we combined natural language processing (NLP) with the Bidirectional Encoder Representation from Transformers (BERT) model to directly quantify thought content. We analyzed the divergence of self-generated thought content and expressions of sadness and empirically verified the validity and behavioral significance of the metrics calculated by BERT. Furthermore, we found that reflection and brooding could be differentiated by detecting the divergence of self-generated thought content and expressions of sadness, thus deepening our understanding of rumination and depression and providing a way to distinguish adaptive from maladaptive rumination. Finally, this study provides a new framework to examine self-generated thoughts in a resting state with NLP, extending research on the continuous content of instant self-generated thoughts with applicability to resting-state functional brain imaging., (© 2021. The Psychonomic Society, Inc.)

Most psychiatric disorders are chronic, associated with high levels of disability and distress, and present during pediatric development. Scientific innovation increasingly allows researchers to probe brain-behavior relationships in the developing human. As a result, ambitions to (1) establish normative pediatric brain development trajectories akin to growth curves, (2) characterize reliable metrics for distinguishing illness, and (3) develop clinically useful tools to assist in the diagnosis and management of mental health and learning disorders have gained significant momentum. To this end, the NKI-Rockland Sample initiative was created to probe lifespan development as a large-scale multimodal dataset. The NKI-Rockland Sample Longitudinal Discovery of Brain Development Trajectories substudy (N = 369) is a 24- to 30-month multi-cohort longitudinal pediatric investigation (ages 6.0-17.0 at enrollment) carried out in a community-ascertained sample. Data include psychiatric diagnostic, medical, behavioral, and cognitive phenotyping, as well as multimodal brain imaging (resting fMRI, diffusion MRI, morphometric MRI, arterial spin labeling), genetics, and actigraphy. Herein, we present the rationale, design, and implementation of the Longitudinal Discovery of Brain Development Trajectories protocol., (© 2022. The Author(s).)

Despite a growing neuroimaging literature on the pathophysiology of major depressive disorder (MDD), reproducible findings are lacking, probably reflecting mostly small sample sizes and heterogeneity in analytic approaches. To address these issues, the Depression Imaging REsearch ConsorTium (DIRECT) was launched. The REST-meta-MDD project, pooling 2428 functional brain images processed with a standardized pipeline across all participating sites, has been the first effort from DIRECT. In this review, we present an overview of the motivations, rationale, and principal findings of the studies so far from the REST-meta-MDD project. Findings from the first round of analyses of the pooled repository have included alterations in functional connectivity within the default mode network, in whole-brain topological properties, in dynamic features, and in functional lateralization. These well-powered exploratory observations have also provided the basis for future longitudinal hypothesis-driven research. Following these fruitful explorations, DIRECT has proceeded to its second stage of data sharing that seeks to examine ethnicity in brain alterations in MDD by extending the exclusive Chinese original sample to other ethnic groups through international collaborations. A state-of-the-art, surface-based preprocessing pipeline has also been introduced to improve sensitivity. Functional images from patients with bipolar disorder and schizophrenia will be included to identify shared and unique abnormalities across diagnosis boundaries. In addition, large-scale longitudinal studies targeting brain network alterations following antidepressant treatment, aggregation of diffusion tensor images, and the development of functional magnetic resonance imaging-guided neuromodulation approaches are underway. Through these endeavours, we hope to accelerate the translation of functional neuroimaging findings to clinical use, such as evaluating longitudinal effects of antidepressant medications and developing individualized neuromodulation targets, while building an open repository for the scientific community., Competing Interests: One of the authors, Dr Qi-Yong Gong, is also the editor-in-chief of Psychoradiology. He was blinded from reviewing or making decisions on the manuscript., (© The Author(s) 2022. Published by Oxford University Press on behalf of West China School of Medicine/West China Hospital (WCSM/WCH) of Sichuan University.)

The nucleus accumbens (NAc) is considered a hub of reward processing and a growing body of evidence has suggested its crucial role in the pathophysiology of major depressive disorder (MDD). However, inconsistent results have been reported by studies on reward network-focused resting-state functional MRI (rs-fMRI). In this study, we examined functional alterations of the NAc-based reward circuits in patients with MDD via meta- and mega-analysis. First, we performed a coordinated-based meta-analysis with a new SDM-PSI method for all up-to-date rs-fMRI studies that focused on the reward circuits of patients with MDD. Then, we tested the meta-analysis results in the REST-meta-MDD database which provided anonymous rs-fMRI data from 186 recurrent MDDs and 465 healthy controls. Decreased functional connectivity (FC) within the reward system in patients with recurrent MDD was the most robust finding in this study. We also found disrupted NAc FCs in the DMN in patients with recurrent MDD compared with healthy controls. Specifically, the combination of disrupted NAc FCs within the reward network could discriminate patients with recurrent MDD from healthy controls with an optimal accuracy of 74.7%. This study confirmed the critical role of decreased FC in the reward network in the neuropathology of MDD. Disrupted inter-network connectivity between the reward network and DMN may also have contributed to the neural mechanisms of MDD. These abnormalities have potential to serve as brain-based biomarkers for individual diagnosis to differentiate patients with recurrent MDD from healthy controls., (© 2022. The Author(s).)

This study investigated motor preparation and action-consequence prediction using the lateralized readiness potential (LRP). Motor impairments are common in autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD), which commonly co-occur. Alterations in predictive processes may impact motor planning. Whether motor planning deficits are characteristic of ASD broadly or magnified in the context of co-morbid ADHD is unclear. ASD children with (ASD + ADHD; n = 12) and without (ASD - ADHD; n = 9) comorbid ADHD and typical controls (n = 29) performed voluntary motor actions that either did or did not result in auditory consequences. ASD - ADHD children demonstrated LRP enhancement when their action produced an effect while ASD + ADHD children had attenuated responses regardless of action-effect pairings. Findings suggest influence of ADHD comorbidity on motor preparation and prediction in ASD., (© 2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Attention-deficit/hyperactivity disorder (ADHD) has been the focus of magnetic resonance imaging studies for more than 30 years, with more than 2200 articles listed in PubMed. Nevertheless, the brain substrates of ADHD remain poorly understood. This reflects the crisis of replicability across nearly all scientific endeavors, deriving from factors such as small sample sizes combined with a proliferation in analytical approaches, yielding high rates of false positive results. The field of molecular genetics confronted this by adopting open and immediate sharing of raw data and insistence on rigorous corrections for multiple comparisons. These strategies are yielding more robust genetic findings, albeit with much smaller effect sizes than before. This brief review focuses on two recent consortium efforts, i.e., the international Enhancing Neuro-Imaging Genetics through Meta-Analysis (ENIGMA), and the U.S. Adolescent Behavior & Cognitive Developm ent Study (ABCD). Both embrace the culture of open science, and are beginning to yield credible findings, despite being limited initially to cross-sectional analyses. As the field continues to mature, these and other ongoing longitudinal large-scale studies are poised to transform our understanding of the pathophysiology of ADHD to bring closer the day when neuroimaging can contribute to clinical utility.

Delineating the association of age and cortical thickness in healthy individuals is critical given the association of cortical thickness with cognition and behavior. Previous research has shown that robust estimates of the association between age and brain morphometry require large-scale studies. In response, we used cross-sectional data from 17,075 individuals aged 3-90 years from the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to infer age-related changes in cortical thickness. We used fractional polynomial (FP) regression to quantify the association between age and cortical thickness, and we computed normalized growth centiles using the parametric Lambda, Mu, and Sigma method. Interindividual variability was estimated using meta-analysis and one-way analysis of variance. For most regions, their highest cortical thickness value was observed in childhood. Age and cortical thickness showed a negative association; the slope was steeper up to the third decade of life and more gradual thereafter; notable exceptions to this general pattern were entorhinal, temporopolar, and anterior cingulate cortices. Interindividual variability was largest in temporal and frontal regions across the lifespan. Age and its FP combinations explained up to 59% variance in cortical thickness. These results may form the basis of further investigation on normative deviation in cortical thickness and its significance for behavioral and cognitive outcomes., (© 2021 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

For many traits, males show greater variability than females, with possible implications for understanding sex differences in health and disease. Here, the ENIGMA (Enhancing Neuro Imaging Genetics through Meta-Analysis) Consortium presents the largest-ever mega-analysis of sex differences in variability of brain structure, based on international data spanning nine decades of life. Subcortical volumes, cortical surface area and cortical thickness were assessed in MRI data of 16,683 healthy individuals 1-90 years old (47% females). We observed significant patterns of greater male than female between-subject variance for all subcortical volumetric measures, all cortical surface area measures, and 60% of cortical thickness measures. This pattern was stable across the lifespan for 50% of the subcortical structures, 70% of the regional area measures, and nearly all regions for thickness. Our findings that these sex differences are present in childhood implicate early life genetic or gene-environment interaction mechanisms. The findings highlight the importance of individual differences within the sexes, that may underpin sex-specific vulnerability to disorders., (© 2020 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Neuroimaging has been extensively used to study brain structure and function in individuals with attention deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) over the past decades. Two of the main shortcomings of the neuroimaging literature of these disorders are the small sample sizes employed and the heterogeneity of methods used. In 2013 and 2014, the ENIGMA-ADHD and ENIGMA-ASD working groups were respectively, founded with a common goal to address these limitations. Here, we provide a narrative review of the thus far completed and still ongoing projects of these working groups. Due to an implicitly hierarchical psychiatric diagnostic classification system, the fields of ADHD and ASD have developed largely in isolation, despite the considerable overlap in the occurrence of the disorders. The collaboration between the ENIGMA-ADHD and -ASD working groups seeks to bring the neuroimaging efforts of the two disorders closer together. The outcomes of case-control studies of subcortical and cortical structures showed that subcortical volumes are similarly affected in ASD and ADHD, albeit with small effect sizes. Cortical analyses identified unique differences in each disorder, but also considerable overlap between the two, specifically in cortical thickness. Ongoing work is examining alternative research questions, such as brain laterality, prediction of case-control status, and anatomical heterogeneity. In brief, great strides have been made toward fulfilling the aims of the ENIGMA collaborations, while new ideas and follow-up analyses continue that include more imaging modalities (diffusion MRI and resting-state functional MRI), collaborations with other large databases, and samples with dual diagnoses., (© 2020 The Authors. Human Brain Mapping published by Wiley Periodicals, Inc.)

Age has a major effect on brain volume. However, the normative studies available are constrained by small sample sizes, restricted age coverage and significant methodological variability. These limitations introduce inconsistencies and may obscure or distort the lifespan trajectories of brain morphometry. In response, we capitalized on the resources of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to examine age-related trajectories inferred from cross-sectional measures of the ventricles, the basal ganglia (caudate, putamen, pallidum, and nucleus accumbens), the thalamus, hippocampus and amygdala using magnetic resonance imaging data obtained from 18,605 individuals aged 3-90 years. All subcortical structure volumes were at their maximum value early in life. The volume of the basal ganglia showed a monotonic negative association with age thereafter; there was no significant association between age and the volumes of the thalamus, amygdala and the hippocampus (with some degree of decline in thalamus) until the sixth decade of life after which they also showed a steep negative association with age. The lateral ventricles showed continuous enlargement throughout the lifespan. Age was positively associated with inter-individual variability in the hippocampus and amygdala and the lateral ventricles. These results were robust to potential confounders and could be used to examine the functional significance of deviations from typical age-related morphometric patterns., (© 2021 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Aberrant topological organization of whole-brain networks has been inconsistently reported in studies of patients with major depressive disorder (MDD), reflecting limited sample sizes. To address this issue, we utilized a big data sample of MDD patients from the REST-meta-MDD Project, including 821 MDD patients and 765 normal controls (NCs) from 16 sites. Using the Dosenbach 160 node atlas, we examined whole-brain functional networks and extracted topological features (e.g., global and local efficiency, nodal efficiency, and degree) using graph theory-based methods. Linear mixed-effect models were used for group comparisons to control for site variability; robustness of results was confirmed (e.g., multiple topological parameters, different node definitions, and several head motion control strategies were applied). We found decreased global and local efficiency in patients with MDD compared to NCs. At the nodal level, patients with MDD were characterized by decreased nodal degrees in the somatomotor network (SMN), dorsal attention network (DAN) and visual network (VN) and decreased nodal efficiency in the default mode network (DMN), SMN, DAN, and VN. These topological differences were mostly driven by recurrent MDD patients, rather than first-episode drug naive (FEDN) patients with MDD. In this highly powered multisite study, we observed disrupted topological architecture of functional brain networks in MDD, suggesting both locally and globally decreased efficiency in brain networks., (© 2021. The Author(s).)

Pediatric brain imaging holds significant promise for understanding neurodevelopment. However, the requirement to remain still inside a noisy, enclosed scanner remains a challenge. Verbal or visual descriptions of the process, and/or practice in MRI simulators are the norm in preparing children. Yet, the factors predictive of successfully obtaining neuroimaging data remain unclear. We examined data from 250 children (6-12 years, 197 males) with autism and/or attention-deficit/hyperactivity disorder. Children completed systematic MRI simulator training aimed to habituate to the scanner environment and minimize head motion. An MRI session comprised multiple structural, resting-state, task and diffusion scans. Of the 201 children passing simulator training and attempting scanning, nearly all (94%) successfully completed the first structural scan in the sequence, and 88% also completed the following functional scan. The number of successful scans decreased as the sequence progressed. Multivariate analyses revealed that age was the strongest predictor of successful scans in the session, with younger children having lower success rates. After age, sensorimotor atypicalities contributed most to prediction. Results provide insights on factors to consider in designing pediatric brain imaging protocols., (Copyright © 2021. Published by Elsevier Ltd.)

Neuroimaging research seeks to identify biomarkers to improve the diagnosis, prognosis, and treatment of attention-deficit/hyperactivity disorder (ADHD), although clinical translation of findings remains distant. Resting-state functional magnetic resonance imaging (R-fMRI) is increasingly being used to characterize functional connectivity in the brain. Despite mixed results to date and multiple methodological challenges, dominant hypotheses implicate hyperconnectivity across brain networks in patients with ADHD, which could be the target of pharmacological treatments. We describe the experience and results of the Clínica Universidad de Navarra (Spain) Metilfenidato (CUNMET) pilot study. CUNMET tested the feasibility of identifying R-fMRI markers of clinical response in children with ADHD undergoing naturalistical pharmacological treatments. We analyzed cross-sectional data from 56 patients with ADHD (18 treated with methylphenidate, 18 treated with lisdexamfetamine, and 20 treatment-naive patients). Standard preprocessing and statistical analyses with attention to control for head motion and correction for multiple comparisons were performed. The only results that survived correction were noted in contrasts of children who responded clinically to lisdexamfetamine after long-term treatment vs. treatment-naive patients. In these children, we observed stronger negative correlations (anticorrelations) across nodes in six brain networks, which is consistent with higher across-network functional segregation in patients treated with lisdexamfetamine, i.e., less inter-network interference than in treatment-naive patients. We also note the lessons learned, which could help those pursuing clinically relevant multidisciplinary research in ADHD en route to eventual personalized medicine. To advance reproducible open science, our report is accompanied with links providing access to our data and analytic scripts., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Pereira-Sanchez, Franco, de Castro-Manglano, Fernandez-Seara, Vallejo-Valdivielso, Díez-Suárez, Fernandez-Martinez, Garcia de Eulate, Milham, Soutullo and Castellanos.)

Objective: Some studies have suggested alterations of structural brain asymmetry in attention-deficit/hyperactivity disorder (ADHD), but findings have been contradictory and based on small samples. Here, we performed the largest ever analysis of brain left-right asymmetry in ADHD, using 39 datasets of the ENIGMA consortium., Methods: We analyzed asymmetry of subcortical and cerebral cortical structures in up to 1,933 people with ADHD and 1,829 unaffected controls. Asymmetry Indexes (AIs) were calculated per participant for each bilaterally paired measure, and linear mixed effects modeling was applied separately in children, adolescents, adults, and the total sample, to test exhaustively for potential associations of ADHD with structural brain asymmetries., Results: There was no evidence for altered caudate nucleus asymmetry in ADHD, in contrast to prior literature. In children, there was less rightward asymmetry of the total hemispheric surface area compared to controls (t = 2.1, p = .04). Lower rightward asymmetry of medial orbitofrontal cortex surface area in ADHD (t = 2.7, p = .01) was similar to a recent finding for autism spectrum disorder. There were also some differences in cortical thickness asymmetry across age groups. In adults with ADHD, globus pallidus asymmetry was altered compared to those without ADHD. However, all effects were small (Cohen's d from -0.18 to 0.18) and would not survive study-wide correction for multiple testing., Conclusion: Prior studies of altered structural brain asymmetry in ADHD were likely underpowered to detect the small effects reported here. Altered structural asymmetry is unlikely to provide a useful biomarker for ADHD, but may provide neurobiological insights into the trait., (© 2021 The Authors. Journal of Child Psychology and Psychiatry published by John Wiley & Sons Ltd on behalf of Association for Child and Adolescent Mental Health.)

Serotonin and dopamine are associated with multiple psychiatric disorders. How they interact during development to affect subsequent behavior remains unknown. Knockout of the serotonin transporter or postnatal blockade with selective serotonin reuptake inhibitors (SSRIs) leads to novelty-induced exploration deficits in adulthood, potentially involving the dopamine system. Here, we show in the mouse that raphe nucleus serotonin neurons activate ventral tegmental area dopamine neurons via glutamate co-transmission and that this co-transmission is reduced in animals exposed postnatally to SSRIs. Blocking serotonin neuron glutamate co-transmission mimics this SSRI-induced hypolocomotion, while optogenetic activation of dopamine neurons reverses this hypolocomotor phenotype. Our data demonstrate that serotonin neurons modulate dopamine neuron activity via glutamate co-transmission and that this pathway is developmentally malleable, with high serotonin levels during early life reducing co-transmission, revealing the basis for the reduced novelty-induced exploration in adulthood due to postnatal SSRI exposure., (© 2020. The Author(s), under exclusive licence to Springer Nature Limited.)

Rhythms of the brain are generated by neural oscillations across multiple frequencies. These oscillations can be decomposed into distinct frequency intervals associated with specific physiological processes. In practice, the number and ranges of decodable frequency intervals are determined by sampling parameters, often ignored by researchers. To improve the situation, we report on an open toolbox with a graphical user interface for decoding rhythms of the brain system (DREAM). We provide worked examples of DREAM to investigate frequency-specific performance of both neural (spontaneous brain activity) and neurobehavioral (in-scanner head motion) oscillations. DREAM decoded the head motion oscillations and uncovered that younger children moved their heads more than older children across all five frequency intervals whereas boys moved more than girls in the age of 7 to 9 years. It is interesting that the higher frequency bands contain more head movements, and showed stronger age-motion associations but weaker sex-motion interactions. Using data from the Human Connectome Project, DREAM mapped the amplitude of these neural oscillations into multiple frequency bands and evaluated their test-retest reliability. The resting-state brain ranks its spontaneous oscillation's amplitudes spatially from high in ventral-temporal areas to low in ventral-occipital areas when the frequency band increased from low to high, while those in part of parietal and ventral frontal regions are reversed. The higher frequency bands exhibited more reliable amplitude measurements, implying more inter-individual variability of the amplitudes for the higher frequency bands. In summary, DREAM adds a reliable and valid tool to mapping human brain function from a multiple-frequency window into brain waves.

Background: Cocaine use disorder (CUD) is a global condition lacking effective treatment. Repetitive transcranial magnetic stimulation (rTMS) may reduce craving and frequency of cocaine use, but little is known about its efficacy and neural effects. We sought to elucidate short- and long-term clinical benefits of 5-Hz rTMS as an add-on to standard treatment in patients with CUD and discern underlying functional connectivity effects using magnetic resonance imaging., Methods: A total of 44 patients with CUD were randomly assigned to complete the 2-week double-blind randomized controlled trial (acute phase) (sham [n = 20, 2 female] and active [n = 24, 4 female]), in which they received two daily sessions of rTMS on the left dorsolateral prefrontal cortex (PFC). Subsequently, 20 patients with CUD continued to an open-label maintenance phase for 6 months (two weekly sessions for up to 6 mo)., Results: rTMS plus standard treatment for 2 weeks significantly reduced craving (baseline: 3.9 ± 3.6; 2 weeks: 1.5 ± 2.4, p = .013, d = 0.77) and impulsivity (baseline: 64.8 ± 16.8; 2 weeks: 53.1 ± 17.4, p = .011, d = 0.79) in the active group. We also found increased functional connectivity between the left dorsolateral PFC and ventromedial PFC and between the ventromedial PFC and right angular gyrus. Clinical and functional connectivity effects were maintained for 3 months, but they dissipated by 6 months. We did not observe reduction in positive results for cocaine in urine; however, self-reported frequency and grams consumed for 6 months were reduced., Conclusions: With this randomized controlled trial, we show that 5-Hz rTMS has potential promise as an adjunctive treatment for CUD and merits further research., (Copyright © 2021 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

Previous neuroimaging studies have revealed abnormal functional connectivity of brain networks in patients with major depressive disorder (MDD), but findings have been inconsistent. A recent big-data study found abnormal intrinsic functional connectivity within the default mode network in patients with recurrent MDD but not in first-episode drug-naïve patients with MDD. This study also provided evidence for reduced default mode network functional connectivity in medicated MDD patients, raising the question of whether previously observed abnormalities may be attributable to antidepressant effects. The present study (ClinicalTrials.gov identifier: NCT03294525) aimed to disentangle the effects of antidepressant treatment from the pathophysiology of MDD and test the medication normalization hypothesis. Forty-one first-episode drug-naïve MDD patients were administrated antidepressant medication (escitalopram or duloxetine) for 8 weeks, with resting-state functional connectivity compared between posttreatment and baseline. To assess the replicability of the big-data finding, we also conducted a cross-sectional comparison of resting-state functional connectivity between the MDD patients and 92 matched healthy controls. Both Network-Based Statistic analyses and large-scale network analyses revealed intrinsic functional connectivity decreases in extensive brain networks after treatment, indicating considerable antidepressant effects. Neither Network-Based Statistic analyses nor large-scale network analyses detected significant functional connectivity differences between treatment-naïve patients and healthy controls. In short, antidepressant effects are widespread across most brain networks and need to be accounted for when considering functional connectivity abnormalities in MDD., (© 2021 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Early life is a sensitive period, in which enhanced neural plasticity allows the developing brain to adapt to its environment. This plasticity can also be a risk factor in which maladaptive development can lead to long-lasting behavioral deficits. Here, we test how early-life exposure to the selective-serotonin-reuptake-inhibitor (SSRI), fluoxetine, affects motivation, and dopaminergic signaling in adulthood. We show for the first time that mice exposed to fluoxetine in the early postnatal period exhibit a reduction in effort-related motivation. These mice also show blunted responses to amphetamine and reduced dopaminergic activation in a sucrose reward task. Interestingly, we find that the reduction in motivation can be rescued in the adult by administering bupropion, a dopamine-norepinephrine reuptake inhibitor used as an antidepressant and a smoke cessation aid but not by fluoxetine. Taken together, our studies highlight the effects of early postnatal exposure of fluoxetine on motivation and demonstrate the involvement of the dopaminergic system in this process. SIGNIFICANCE STATEMENT The developmental period is characterized by enhanced plasticity. During this period, environmental factors have the potential to lead to enduring behavioral changes. Here, we show that exposure to the SSRI fluoxetine during a restricted period in early life leads to a reduction in adult motivation. We further show that this reduction is associated with decreased dopaminergic responsivity. Finally, we show that motivational deficits induced by early-life fluoxetine exposure can be rescued by adult administration of bupropion but not by fluoxetine., (Copyright © 2021 the authors.)

Purpose of Review: Neuroimaging research on attention-deficit/hyperactivity disorder (ADHD) continues growing in extent and complexity, although it has yet to become clinically meaningful. We review recent MRI research on ADHD, to identify robust findings, current trends and challenges., Recent Findings: We identified 40 publications between January 2019 and September 2020 reporting or reviewing MRI research on ADHD. Four meta-analyses have presented conflicting results regarding across-study convergence of functional and resting-state functional (fMRI and R-fMRI) studies on ADHD. On the other hand, the Enhancing NeuroImaging Genetics Through Meta-Analysis international consortium has identified statistically robust albeit small differences in structural brain cortical and subcortical indices in children with ADHD versus typically developing controls. Other international consortia are harnessing open-science efforts and multimodal data (imaging, genetics, phenotypic) to shed light on the complex interplay of genetics, environment, and development in the pathophysiology of ADHD. We note growing research in 'prediction' science, which applies machine-learning analysis to identify biomarkers of disease based on big data., Summary: Neuroimaging in ADHD is still far from informing clinical practice. Current large-scale, multimodal, and open-science initiatives represent promising paths toward untangling the neurobiology of ADHD., (Copyright © 2020 The Author(s). Published by Wolters Kluwer Health, Inc.)

Objective: The habenula is a small region in the epithalamus that contributes to the regulation of midbrain dopaminergic circuits implicated in attention-deficit hyperactivity disorder (ADHD). This investigation aims to evaluate the intrinsic functional connectivity (iFC) of the habenula in children with ADHD. Method: A total of 112 children (5-9 years; 75 ADHD, 37 healthy comparisons) completed anatomical and resting-state functional magnetic resonance imaging (MRI) scans. Habenula regions of interest (ROIs) were identified individually on normalized T1-weighted anatomical images. Seed-based iFC analyses and group comparisons were conducted for habenula ROIs, as well as thalamic ROIs to test the specificity of habenula findings. Results: Children with ADHD exhibited reduced habenula-putamen iFC compared with healthy comparisons. Group differences in thalamic iFC showed no overlap with habenular findings. Conclusion: These preliminary findings suggest that habenula-putamen iFC may be disrupted in children with ADHD. Further work is needed to confirm and elucidate the role of this circuit in ADHD pathophysiology.

Background: Endocannabinoid dysfunction in animal models of autism spectrum disorder (ASD) and accumulating, albeit anecdotal, evidence for efficacy in humans motivated this placebo-controlled double-blind comparison of two oral cannabinoid solutions in 150 participants (age 5-21 years) with ASD., Methods: We tested (1) BOL-DP-O-01-W, a whole-plant cannabis extract containing cannabidiol and Δ9-tetrahydrocannabinol at a 20:1 ratio and (2) BOL-DP-O-01, purified cannabidiol and Δ9-tetrahydrocannabinol at the same ratio. Participants (N = 150) received either placebo or cannabinoids for 12-weeks (testing efficacy) followed by a 4-week washout and predetermined cross-over for another 12 weeks to further assess tolerability. Registered primary efficacy outcome measures were improvement in behavioral problems (differences between whole-plant extract and placebo) on the Home Situation Questionnaire-ASD (HSQ-ASD) and the Clinical Global Impression-Improvement scale with disruptive behavior anchor points (CGI-I). Secondary measures were Social Responsiveness Scale (SRS-2) and Autism Parenting Stress Index (APSI)., Results: Changes in Total Scores of HSQ-ASD (primary-outcome) and APSI (secondary-outcome) did not differ among groups. Disruptive behavior on the CGI-I (co-primary outcome) was either much or very much improved in 49% on whole-plant extract (n = 45) versus 21% on placebo (n = 47; p = 0.005). Median SRS Total Score (secondary-outcome) improved by 14.9 on whole-plant extract (n = 34) versus 3.6 points after placebo (n = 36); p = 0.009). There were no treatment-related serious adverse events. Common adverse events included somnolence and decreased appetite, reported for 28% and 25% on whole-plant extract, respectively (n = 95); 23% and 21% on pure-cannabinoids (n = 93), and 8% and 15% on placebo (n = 94). Limitations Lack of pharmacokinetic data and a wide range of ages and functional levels among participants warrant caution when interpreting the results., Conclusions: This interventional study provides evidence that BOL-DP-O-01-W and BOL-DP-O-01, administrated for 3 months, are well tolerated. Evidence for efficacy of these interventions are mixed and insufficient. Further testing of cannabinoids in ASD is recommended. Trial registration ClinicalTrials.gov: NCT02956226. Registered 06 November 2016, https://clinicaltrials.gov/ct2/show/NCT02956226.

Patterns of functional connectivity are unique at the individual level, enabling test-retest matching algorithms to identify a subject from among a group using only their functional connectome. Recent findings show that accuracies of these algorithms in children increase with age. Relatedly, the persistence of functional connectivity (FC) patterns across tasks and rest also increases with age. This study investigated the hypothesis that within-subject stability and between-subject similarity of the whole-brain pediatric connectome are developmentally relevant outcomes. Using data from 210 help-seeking children and adolescents, ages 6-21 years (Healthy Brain Network Biobank), we computed whole-brain FC matrices for each participant during two different movies (MovieDM and MovieTP) and two runs of task-free rest (all from a single scan session) and fed these matrices to a test-retest matching algorithm. We replicated the finding that matching accuracies for children and youth (ages 6-21 years) are low (18-44%), and that cross-state and cross-movie accuracies were the lowest. Results also showed that parcellation resolution and the number of volumes used in each matrix affect fingerprinting accuracies. Next, we calculated three measures of whole-connectome stability for each subject: cross-rest (Rest1-Rest2), cross-state (MovieDM-Rest1), and cross-movie (MovieDM-MovieTP), and three measures of within-state between-subject connectome similarity for Rest1, MovieDM, and MovieTP. We show that stability and similarity were correlated, but that these measures were not related to age. A principal component analysis of these measures yielded two components that we used to test for brain-behavior correlations with IQ, general psychopathology, and social skills measures (n = 119). The first component was significantly correlated with the social skills measure (r=-0.26, p = 0.005). Post hoc correlations showed that the social skills measure correlated with both cross-rest stability (r=-0.29, p = 0.001) and with connectome similarity during MovieDM (r=-0.28, p = 0.002). These findings suggest that the stability and similarity of the whole-brain connectome relate to the development of social skills. We infer that the maturation of the functional connectome simultaneously achieves patterns of FC that are distinct at the individual subject level, that are shared across individuals, and that are persistent across states and across runs-features which presumably combine to optimize neural processing during development. Future longitudinal work could reveal the developmental trajectories of stability and similarity of the connectome., (Copyright © 2020. Published by Elsevier Inc.)

Objective: Resting-state functional magnetic resonance imaging (R-fMRI) studies of the neural correlates of medication treatment in attention-deficit/hyperactivity disorder (ADHD) have not been systematically reviewed. Our objective was to systematically identify, assess and summarize within-subject R-fMRI studies of pharmacological-induced changes in patients with ADHD. We critically appraised strengths and limitations, and provide recommendations for future research., Method: Systematic review of published original reports in English meeting criteria in pediatric and adult patients with ADHD up to July 1, 2020. A thorough search preceded selection of studies matching prespecified criteria. Strengths and limitations of selected studies, regarding design and reporting, were identified based on current best practices., Results: We identified and reviewed 9 studies (5 pediatric and 4 adult studies). Sample sizes were small-medium (16-38 patients), and included few female participants. Medications were methylphenidate, amphetamines, and atomoxetine. Wide heterogeneity was observed in designs, analyses and results, which could not be combined quantitatively. Qualitatively, the multiplicity of brain regions and networks identified, some of which correlated with clinical improvements, do not support a coherent mechanistic hypothesis of medication effects. Overall, reports did not meet current standards to ensure reproducibility., Conclusion: In this emerging field, the few studies using R-fMRI to analyze the neural correlates of medications in patients with ADHD suggest a potential modulatory effect of stimulants and atomoxetine on several intrinsic brain activity metrics. However, methodological heterogeneity and reporting issues need to be addressed in future research to validate findings which may contribute to clinical care. Such a goal is not yet at hand., (Copyright © 2020 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.)

Previous studies have shown that the gene encoding the adhesion G protein-coupled receptor L3 (ADGRL3; formerly latrophilin 3, LPHN3) is associated with Attention-Deficit/Hyperactivity Disorder (ADHD). Conversely, no studies have investigated the anatomical or functional brain substrates of ADGRL3 risk variants. We examined here whether individuals with different ADGRL3 haplotypes, including both patients with ADHD and healthy controls, showed differences in brain anatomy and function. We recruited and genotyped adult patients with combined type ADHD and healthy controls to achieve a sample balanced for age, sex, premorbid IQ, and three ADGRL3 haplotype groups (risk, protective, and others). The final sample (n = 128) underwent structural and functional brain imaging (voxel-based morphometry and n-back working memory fMRI). We analyzed the brain structural and functional effects of ADHD, haplotypes, and their interaction, covarying for age, sex, and medication. Individuals (patients or controls) with the protective haplotype showed strong, widespread hypo-activation in the frontal cortex extending to inferior temporal and fusiform gyri. Individuals (patients or controls) with the risk haplotype also showed hypo-activation, more focused in the right temporal cortex. Patients showed parietal hyper-activation. Disorder-haplotype interactions, as well as structural findings, were not statistically significant. To sum up, both protective and risk ADGRL3 haplotypes are associated with substantial brain hypo-activation during working memory tasks, stressing this gene's relevance in cognitive brain function. Conversely, we did not find brain effects of the interactions between adult ADHD and ADGRL3 haplotypes.

Multilayer network models have been proposed as an effective means of capturing the dynamic configuration of distributed neural circuits and quantitatively describing how communities vary over time. Beyond general insights into brain function, a growing number of studies have begun to employ these methods for the study of individual differences. However, test-retest reliabilities for multilayer network measures have yet to be fully quantified or optimized, potentially limiting their utility for individual difference studies. Here, we systematically evaluated the impact of multilayer community detection algorithms, selection of network parameters, scan duration, and task condition on test-retest reliabilities of multilayer network measures (i.e., flexibility, integration, and recruitment). A key finding was that the default method used for community detection by the popular generalized Louvain algorithm can generate erroneous results. Although available, an updated algorithm addressing this issue is yet to be broadly adopted in the neuroimaging literature. Beyond the algorithm, the present work identified parameter selection as a key determinant of test-retest reliability; however, optimization of these parameters and expected reliabilities appeared to be dataset-specific. Once parameters were optimized, consistent with findings from the static functional connectivity literature, scan duration was a much stronger determinant of reliability than scan condition. When the parameters were optimized and scan duration was sufficient, both passive (i.e., resting state, Inscapes, and movie) and active (i.e., flanker) tasks were reliable, although reliability in the movie watching condition was significantly higher than in the other three tasks. The minimal data requirement for achieving reliable measures for the movie watching condition was 20 min, and 30 min for the other three tasks. Our results caution the field against the use of default parameters without optimization based on the specific datasets to be employed - a process likely to be limited for most due to the lack of test-retest samples to enable parameter optimization., (Copyright © 2020. Published by Elsevier Inc.)

Objective: To conduct a meta-analysis of resting-state functional magnetic resonance imaging (R-fMRI) studies in children and adolescents with attention-deficit/hyperactivity disorder (ADHD) and in adults with ADHD to assess spatial convergence of findings from available studies., Method: Based on a preregistered protocol in PROSPERO (CRD42019119553), a large set of databases were searched up to April 9, 2019, with no language or article type restrictions. Study authors were systematically contacted for additional unpublished information/data. Resting-state functional magnetic resonance imaging studies using seed-based connectivity (SBC) or any other method (non-SBC) reporting whole-brain results of group comparisons between participants with ADHD and typically developing controls were eligible. Voxelwise meta-analysis via activation likelihood estimation with cluster-level familywise error (voxel-level: p < .001; cluster-level: p < .05) was used., Results: Thirty studies (18 SBC and 12 non-SBC), comprising 1,978 participants (1,094 with ADHD; 884 controls) were retained. The meta-analysis focused on SBC studies found no significant spatial convergence of ADHD-related hyperconnectivity or hypoconnectivity across studies. This nonsignificant finding remained after integrating 12 non-SBC studies into the main analysis and in sensitivity analyses limited to studies including only children or only non-medication-naïve patients., Conclusion: The lack of significant spatial convergence may be accounted for by heterogeneity in study participants, experimental procedures, and analytic flexibility as well as in ADHD pathophysiology. Alongside other neuroimaging meta-analyses in other psychiatric conditions, the present results should inform the conduct and publication of future neuroimaging studies of psychiatric disorders., (Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.)

Prior ex vivo histological postmortem studies of autism spectrum disorder (ASD) have shown gray matter microstructural abnormalities, however, in vivo examination of gray matter microstructure in ASD has remained scarce due to the relative lack of non-invasive methods to assess it. The aim of this work was to evaluate the feasibility of employing diffusional kurtosis imaging (DKI) to describe gray matter abnormalities in ASD in vivo. DKI data were examined for 16 male participants with a diagnosis of ASD and IQ>80 and 17 age- and IQ-matched male typically developing (TD) young adults 18-25 years old. Mean (MK), axial (AK), radial (RK) kurtosis and mean diffusivity (MD) metrics were calculated for lobar and sub-lobar regions of interest. Significantly decreased MK, RK, and MD were found in ASD compared to TD participants in the frontal and temporal lobes and several sub-lobar regions previously associated with ASD pathology. In ASD participants, decreased kurtosis in gray matter ROIs correlated with increased repetitive and restricted behaviors and poor social interaction symptoms. Decreased kurtosis in ASD may reflect a pathology associated with a less restrictive microstructural environment such as decreased neuronal density and size, atypically sized cortical columns, or limited dendritic arborizations.

Brain growth charts and age-normed brain templates are essential resources for researchers to eventually contribute to the care of individuals with atypical developmental trajectories. The present work generates age-normed brain templates for children and adolescents at one-year intervals and the corresponding growth charts to investigate the influences of age and ethnicity using a common pediatric neuroimaging protocol. Two accelerated longitudinal cohorts with the identical experimental design were implemented in the United States and China. Anatomical magnetic resonance imaging (MRI) of typically developing school-age children (TDC) was obtained up to three times at nominal intervals of 1.25 years. The protocol generated and compared population- and age-specific brain templates and growth charts, respectively. A total of 674 Chinese pediatric MRI scans were obtained from 457 Chinese TDC and 190 American pediatric MRI scans were obtained from 133 American TDC. Population- and age-specific brain templates were used to quantify warp cost, the differences between individual brains and brain templates. Volumetric growth charts for labeled brain network areas were generated. Shape analyses of cost functions supported the necessity of age-specific and ethnicity-matched brain templates, which was confirmed by growth chart analyses. These analyses revealed volumetric growth differences between the two ethnicities primarily in lateral frontal and parietal areas, regions which are most variable across individuals in regard to their structure and function. Age- and ethnicity-specific brain templates facilitate establishing unbiased pediatric brain growth charts, indicating the necessity of the brain charts and brain templates generated in tandem. These templates and growth charts as well as related codes have been made freely available to the public for open neuroscience (https://github.com/zuoxinian/CCS/tree/master/H3/GrowthCharts)., Competing Interests: Conflict of interest The authors declare that they have no conflict of interest., (Copyright © 2020 Science China Press. Published by Elsevier B.V. All rights reserved.)

Objective: Attention deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), and obsessive-compulsive disorder (OCD) are common neurodevelopmental disorders that frequently co-occur. The authors sought to directly compare these disorders using structural brain imaging data from ENIGMA consortium data., Methods: Structural T 1 -weighted whole-brain MRI data from healthy control subjects (N=5,827) and from patients with ADHD (N=2,271), ASD (N=1,777), and OCD (N=2,323) from 151 cohorts worldwide were analyzed using standardized processing protocols. The authors examined subcortical volume, cortical thickness, and cortical surface area differences within a mega-analytical framework, pooling measures extracted from each cohort. Analyses were performed separately for children, adolescents, and adults, using linear mixed-effects models adjusting for age, sex, and site (and intracranial volume for subcortical and surface area measures)., Results: No shared differences were found among all three disorders, and shared differences between any two disorders did not survive correction for multiple comparisons. Children with ADHD compared with those with OCD had smaller hippocampal volumes, possibly influenced by IQ. Children and adolescents with ADHD also had smaller intracranial volume than control subjects and those with OCD or ASD. Adults with ASD showed thicker frontal cortices compared with adult control subjects and other clinical groups. No OCD-specific differences were observed across different age groups and surface area differences among all disorders in childhood and adulthood., Conclusions: The study findings suggest robust but subtle differences across different age groups among ADHD, ASD, and OCD. ADHD-specific intracranial volume and hippocampal differences in children and adolescents, and ASD-specific cortical thickness differences in the frontal cortex in adults, support previous work emphasizing structural brain differences in these disorders.

Objective: Elevated response time intrasubject variability (RT-ISV) characterizes ADHD. Deficient emotional self-regulation (DESR), defined by summating Child Behavior Checklist Anxious/Depressed, Aggressive, and Attention subscale scores, has been associated with worse outcome in ADHD. To determine if DESR is differentially associated with elevated RT-ISV, we examined RT-ISV in children with ADHD with and without DESR and in typically developing children (TDC). Method: We contrasted RT-ISV during a 6-min Eriksen Flanker Task in 31 children with ADHD without DESR, 34 with ADHD with DESR, and 65 TDC. Results: Regardless of DESR, children with ADHD showed significantly greater RT-ISV than TDC ( p < .001). The ADHD subgroups, defined by presence or absence of DESR, did not differ from each other. Conclusion: Increased RT-ISV characterizes ADHD regardless of comorbid DESR. Alongside similar findings in children and adults with ADHD, these results suggest that RT-ISV is related to cognitive rather than emotional dysregulation in ADHD.

Objective: Impaired multisensory integration in autism spectrum disorder (ASD) may arise from functional dysconnectivity among brain systems. Our study examines the functional connectivity integration between primary modal sensory regions and heteromodal processing cortex in ASD, and whether abnormalities in network integration relate to clinical severity., Method: We studied a sample of 55 high-functioning ASD and 64 healthy control (HC) male children and adolescents (total n = 119, age range 7-18 years). Stepwise functional connectivity analysis (SFC) was applied to resting state functional magnetic resonance images (rsfMRI) to characterize the connectivity paths that link primary sensory cortices to higher-order brain cognitive functional circuits and to relate alterations in functional connectivity integration with three clinical scales: Social Communication Questionnaire, Social Responsiveness Scale, and Vineland Adaptive Behavior Scales., Results: HC displayed typical functional connectivity transitions from primary sensory systems to association areas, but the ASD group showed altered patterns of multimodal sensory integration to heteromodal systems. Specifically, compared to the HC group, the ASD group showed the following: (1) hyperconnectivity in the visual cortex at initial link step distances; (2) hyperconnectivity between sensory unimodal regions and regions of the default mode network; and (3) hypoconnectivity between sensory unimodal regions and areas of the fronto-parietal and attentional networks. These patterns of hyper- and hypoconnectivity were associated with increased clinical severity in ASD., Conclusion: Networkwise reorganization in high-functioning ASD individuals affects strategic regions of unimodal-to-heteromodal cortical integration predicting clinical severity. In addition, SFC analysis appears to be a promising approach for studying the neural pathophysiology of multisensory integration deficits in ASD., (Copyright © 2019 American Academy of Child and Adolescent Psychiatry. All rights reserved.)

Rumination is strongly and consistently correlated with depression. Although multiple studies have explored the neural correlates of rumination, findings have been inconsistent and the mechanisms underlying rumination remain elusive. Functional brain imaging studies have identified areas in the default mode network (DMN) that appear to be critically involved in ruminative processes. However, a meta-analysis to synthesize the findings of brain regions underlying rumination is currently lacking. Here, we conducted a meta-analysis consisting of experimental tasks that investigate rumination by using Signed Differential Mapping of 14 fMRI studies comprising 286 healthy participants. Furthermore, rather than treat the DMN as a unitary network, we examined the contribution of three DMN subsystems to rumination. Results confirm the suspected association between rumination and DMN activation, specifically implicating the DMN core regions and the dorsal medial prefrontal cortex subsystem. Based on these findings, we suggest a hypothesis of how DMN regions support rumination and present the implications of this model for treating major depressive disorder characterized by rumination., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Background: Major depressive disorder (MDD) is known to be characterized by altered brain functional connectivity (FC) patterns. However, whether and how the features of dynamic FC would change in patients with MDD are unclear. In this study, we aimed to characterize dynamic FC in MDD using a large multi-site sample and a novel dynamic network-based approach., Methods: Resting-state functional magnetic resonance imaging (fMRI) data were acquired from a total of 460 MDD patients and 473 healthy controls, as a part of the REST-meta-MDD consortium. Resting-state dynamic functional brain networks were constructed for each subject by a sliding-window approach. Multiple spatio-temporal features of dynamic brain networks, including temporal variability, temporal clustering and temporal efficiency, were then compared between patients and healthy subjects at both global and local levels., Results: The group of MDD patients showed significantly higher temporal variability, lower temporal correlation coefficient (indicating decreased temporal clustering) and shorter characteristic temporal path length (indicating increased temporal efficiency) compared with healthy controls (corrected p < 3.14×10 -3 ). Corresponding local changes in MDD were mainly found in the default-mode, sensorimotor and subcortical areas. Measures of temporal variability and characteristic temporal path length were significantly correlated with depression severity in patients (corrected p < 0.05). Moreover, the observed between-group differences were robustly present in both first-episode, drug-naïve (FEDN) and non-FEDN patients., Conclusions: Our findings suggest that excessive temporal variations of brain FC, reflecting abnormal communications between large-scale bran networks over time, may underlie the neuropathology of MDD., Competing Interests: Declaration of Competing Interest The authors report no biomedical financial interests or potential conflicts of interest related to the present work. Dr. Castellanos reports serving on the advisory board of BOL Pharma and receiving research support (study drug) from Greenwich Biosciences., (Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.)

Cortical development is characterized by distinct spatial and temporal patterns of maturational changes across various cortical shape measures. There is a growing interest in summarizing complex developmental patterns into a single index, which can be used to characterize an individual's brain age. We conducted this study with two primary aims. First, we sought to quantify covariation patterns for a variety of cortical shape measures, including cortical thickness, gray matter volume, surface area, mean curvature, and travel depth, as well as white matter volume, and subcortical gray matter volume. We examined these measures in a sample of 869 participants aged 5-18 from the Healthy Brain Network (HBN) neurodevelopmental cohort using the Joint and Individual Variation Explained (Lock et al., 2013) method. We validated our results in an independent dataset from the Nathan Kline Institute - Rockland Sample (NKI-RS; N = 210) and found remarkable consistency for some covariation patterns. Second, we assessed whether covariation patterns in the brain can be used to accurately predict a person's chronological age. Using ridge regression, we showed that covariation patterns can predict chronological age with high accuracy, reflected by our ability to cross-validate our model in an independent sample with a correlation coefficient of 0.84 between chronologic and predicted age. These covariation patterns also predicted sex with high accuracy (AUC = 0.85), and explained a substantial portion of variation in full scale intelligence quotient (R 2  = 0.10). In summary, we found significant covariation across different cortical shape measures and subcortical gray matter volumes. In addition, each shape measure exhibited distinct covariations that could not be accounted for by other shape measures. These covariation patterns accurately predicted chronological age, sex and general cognitive ability. In a subset of NKI-RS, test-retest (<1 month apart, N = 120) and longitudinal scans (1.22 ± 0.29 years apart, N = 77) were available, allowing us to demonstrate high reliability for the prediction models obtained and the ability to detect subtle differences in the longitudinal scan interval among participants (median and median absolute deviation of absolute differences between predicted age difference and real age difference = 0.53 ± 0.47 years, r = 0.24, p-value = 0.04)., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Importance: An increasing prevalence of adult attention-deficit/hyperactivity disorder (ADHD) diagnosis and treatment has been reported in clinical settings and administrative data in the United States. However, there are limited data on recent trends of adult ADHD diagnosis among racial/ethnic subgroups., Objective: To examine trends, including associated demographic characteristics, psychiatric diagnoses, and negative outcomes, in the prevalence and incidence of adult ADHD diagnosis among 7 racial/ethnic groups during a 10-year period., Design, Setting, and Participants: This cohort study investigated trends in the diagnosis of ADHD in adults who identified as African American or black, Native American, Pacific Islander, Latino or Hispanic, non-Hispanic white, Asian American, or other using the Kaiser Permanente Northern California health plan medical records. A total of 5 282 877 adult patients and 867 453 children aged 5 to 11 years who received care at Kaiser Permanente Northern California from January 1, 2007, to December 31, 2016, were included. Data analysis was performed from January 2017 through September 2019., Exposures: Period of ADHD diagnosis., Main Outcomes and Measures: Prevalence and incidence of licensed mental health clinician-diagnosed ADHD in adults and prevalence of licensed mental health clinician-diagnosed ADHD in children aged 5 to 11 years., Results: Of 5 282 877 adult patients (1 155 790 [21.9%] aged 25-34 years; 2 667 562 [50.5%] women; 2 204 493 [41.7%] white individuals), 59 371 (1.12%) received diagnoses of ADHD. Prevalence increased from 0.43% in 2007 to 0.96% in 2016. Among 867 453 children aged 5 to 11 years (424 449 [48.9%] girls; 260 236 [30.0%] white individuals), prevalence increased from 2.96% in 2007 to 3.74% in 2016. During the study period, annual adult ADHD prevalence increased for every race/ethnicity, but white individuals consistently had the highest prevalence rates (white individuals: 0.67%-1.42%; black individuals: 0.22%-0.69%; Native American individuals: 0.56%-1.14%; Pacific Islander individuals: 0.11%-0.39%; Hispanic or Latino individuals: 0.25%-0.65%; Asian American individuals: 0.11%-0.35%; individuals from other races/ethnicities: 0.29%-0.71%). Incidence of ADHD diagnosis per 10 000 person-years increased from 9.43 in 2007 to 13.49 in 2016. Younger age (eg, >65 years vs 18-24 years: odds ratio [OR], 0.094; 95% CI, 0.088-0.101; P < .001), male sex (women: OR, 0.943; 95% CI, 0.928-0.959; P < .001), white race (eg, Asian patients vs white patients: OR, 0.248; 95% CI, 0.240-0.257; P < .001), being divorced (OR, 1.131; 95% CI, 1.093-1.171; P < .001), being employed (eg, retired vs employed persons: OR, 0.278; 95% CI, 0.267-0.290; P < .001), and having a higher median education level (OR, 2.156; 95% CI, 2.062-2.256; P < .001) were positively associated with odds of ADHD diagnosis. Having an eating disorder (OR, 5.192; 95% CI, 4.926-5.473; P < .001), depressive disorder (OR, 4.118; 95% CI, 4.030-4.207; P < .001), bipolar disorder (OR, 4.722; 95% CI, 4.556-4.894; P < .001), or anxiety disorder (OR, 2.438; 95% CI, 2.385-2.491; P < .001) was associated with higher odds of receiving an ADHD diagnosis. Adults with ADHD had significantly higher odds of frequent health care utilization (OR, 1.303; 95% CI, 1.272-1.334; P < .001) and sexually transmitted infections (OR, 1.289; 95% CI 1.251-1.329; P < .001) compared with adults with no ADHD diagnosis., Conclusions and Relevance: This study confirmed the reported increases in rates of ADHD diagnosis among adults, showing substantially lower rates of detection among minority racial/ethnic subgroups in the United States. Higher odds of negative outcomes reflect the economic and personal consequences that substantiate the need to improve assessment and treatment of ADHD in adults.

Neuroimaging studies indicate that children with attention-deficit/hyperactivity disorder (ADHD) present alterations in several functional networks of the sensation-to-cognition spectrum. These alterations include functional overconnectivity within sensory regions and underconnectivity between sensory regions and neural hubs supporting higher order cognitive functions. Today, it is unknown whether this same pattern of alterations persists in adult patients with ADHD who had never been medicated for their condition. The aim of the present study was to assess whether medication-naïve adults with ADHD presented alterations in functional networks of the sensation-to-cognition spectrum. Thirty-one medication-naïve adults with ADHD and twenty-two healthy adults underwent resting-state functional magnetic resonance imaging (rs-fMRI). Stepwise functional connectivity (SFC) was used to characterize the pattern of functional connectivity between sensory seed regions and the rest of the brain at direct, short, intermediate, and long functional connectivity distances, thus covering the continuum from the sensory input to the neural hubs supporting higher order cognitive functions. As compared to controls, adults with ADHD presented increased SFC degree within primary sensory regions and decreased SFC degree between sensory seeds and higher order integration nodes. In addition, they exhibited decreased connectivity degree between sensory seeds and regions of the default-mode network. Consistently, the higher the score in clinical severity scales the lower connectivity degree between seed regions and the default mode network., (© 2019 Wiley Periodicals, Inc.)

Children with the autosomal dominant single gene disorder, neurofibromatosis type 1 (NF1), display multiple structural and functional changes in the central nervous system, resulting in neuropsychological cognitive abnormalities. Here we assessed the pathological functional organization that may underlie the behavioral impairments in NF1 using resting-state functional connectivity MRI. Coherent spontaneous fluctuations in the fMRI signal across the entire brain were used to interrogate the pattern of functional organization of corticocortical and corticostriatal networks in both NF1 pediatric patients and mice with a heterozygous mutation in the Nf1 gene (Nf1 +/- ). Children with NF1 demonstrated abnormal organization of cortical association networks and altered posterior-anterior functional connectivity in the default network. Examining the contribution of the striatum revealed that corticostriatal functional connectivity was altered. NF1 children demonstrated reduced functional connectivity between striatum and the frontoparietal network and increased striatal functional connectivity with the limbic network. Awake passive mouse functional connectivity MRI in Nf1 +/- mice similarly revealed reduced posterior-anterior connectivity along the cingulate cortex as well as disrupted corticostriatal connectivity. The striatum of Nf1 +/- mice showed increased functional connectivity to somatomotor and frontal cortices and decreased functional connectivity to the auditory cortex. Collectively, these results demonstrate similar alterations across species, suggesting that NF1 pathogenesis is linked to striatal dysfunction and disrupted corticocortical connectivity in the default network., (Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.)

Attention Deficit Hyperactivity Disorder (ADHD) is a highly heritable and prevalent neurodevelopmental disorder that frequently persists into adulthood. Strong evidence from genetic studies indicates that single nucleotide polymorphisms (SNPs) harboured in the ADGRL3 ( LPHN3 ), SNAP25 , FGF1 , DRD4 , and SLC6A2 genes are associated with ADHD. We genotyped 26 SNPs harboured in genes previously reported to be associated with ADHD and evaluated their potential association in 386 individuals belonging to 113 nuclear families from a Caribbean community in Barranquilla, Colombia, using family-based association tests. SNPs rs362990- SNAP25 (T allele; p = 2.46 × 10 -4 ), rs2282794- FGF1 (A allele; p = 1.33 × 10 -2 ), rs2122642- ADGRL3 (C allele, p = 3.5 × 10 -2 ), and ADGRL3 haplotype CCC (markers rs1565902-rs10001410-rs2122642, OR = 1.74, P permuted = 0.021) were significantly associated with ADHD. Our results confirm the susceptibility to ADHD conferred by SNAP25 , FGF1 , and ADGRL3 variants in a community with a significant African American component, and provide evidence supporting the existence of specific patterns of genetic stratification underpinning the susceptibility to ADHD. Knowledge of population genetics is crucial to define risk and predict susceptibility to disease.

The integrity of white matter architecture in the human brain is related to cognitive processing abilities. The corpus callosum is the largest white matter bundle interconnecting the two cerebral hemispheres. "Split-brain" patients in whom all cortical commissures have been severed to alleviate intractable epilepsy demonstrate remarkably intact cognitive abilities despite the lack of this important interhemispheric pathway. While it has often been speculated that there are compensatory alterations in the remaining interhemispheric fibers in split-brain patients several years post-commissurotomy, this has never been directly shown. Here we examined extra-callosal pathways for interhemispheric communication in the brain of a patient who underwent complete cerebral commissurotomy using diffusion weighted imaging tractography. We found that compared with a healthy age-matched comparison group, the split-brain patient exhibited increased fractional anisotropy (FA) of the dorsal and ventral pontine decussations of the cortico-cerebellar interhemispheric pathways. Few differences were observed between the patient and the comparison group with respect to FA of other long-range intrahemispheric fibers. These results point to specific cerebellar anatomical substrates that may account for the spared interhemispheric coordination and intact cognitive abilities that have been extensively documented in this unique patient.

Identify correlates of nicotine dependence [lifetime (l) and ongoing (o)] in adults with attention-deficit/hyperactivity disorder (ADHD) in childhood. We conducted a 33-year prospective follow-up of boys (mean age 8) with combined type ADHD (n = 135/207, 65% original sample). Correlates of nicotine dependence in adulthood were selected from characteristics obtained in childhood and adolescence. Among selected childhood features, only immature behavior was significantly related to nicotine dependence (OR (o)  = 0.29, p = 0.02), indexing decreased risk. In contrast, several adolescent variables significantly correlated (p < 0.01) with nicotine dependence at mean age 41, including alcohol substance use disorder (SUD, OR (l)  = 4.97), non-alcohol SUD (OR (o)  = 4.33/OR (l)  = 10.93), parental antisocial personality disorder (OR (l)  = 4.42), parental SUD (OR (l)  = 3.58), dropped out of school (OR (l)  = 2.29), impulsivity (OR (o)  = 1.53/OR (l)  = 1.59), hyperactivity (OR (o)  = 1.38), and number of antisocial behaviors (OR (o)  = 1.10/OR (l)  = 1.14). Results highlight the role of adolescent psychopathology in the development of nicotine dependence, motivating prospective longitudinal efforts to better define the developmental trajectories of risk and protection.

Major depressive disorder (MDD) is common and disabling, but its neuropathophysiology remains unclear. Most studies of functional brain networks in MDD have had limited statistical power and data analysis approaches have varied widely. The REST-meta-MDD Project of resting-state fMRI (R-fMRI) addresses these issues. Twenty-five research groups in China established the REST-meta-MDD Consortium by contributing R-fMRI data from 1,300 patients with MDD and 1,128 normal controls (NCs). Data were preprocessed locally with a standardized protocol before aggregated group analyses. We focused on functional connectivity (FC) within the default mode network (DMN), frequently reported to be increased in MDD. Instead, we found decreased DMN FC when we compared 848 patients with MDD to 794 NCs from 17 sites after data exclusion. We found FC reduction only in recurrent MDD, not in first-episode drug-naïve MDD. Decreased DMN FC was associated with medication usage but not with MDD duration. DMN FC was also positively related to symptom severity but only in recurrent MDD. Exploratory analyses also revealed alterations in FC of visual, sensory-motor, and dorsal attention networks in MDD. We confirmed the key role of DMN in MDD but found reduced rather than increased FC within the DMN. Future studies should test whether decreased DMN FC mediates response to treatment. All R-fMRI indices of data contributed by the REST-meta-MDD consortium are being shared publicly via the R-fMRI Maps Project., Competing Interests: The authors declare no conflict of interest., (Copyright © 2019 the Author(s). Published by PNAS.)

The use of movie-watching as an acquisition state for functional connectivity (FC) MRI has recently enabled multiple groups to obtain rich data sets in younger children with both substantial sample sizes and scan durations. Using naturalistic paradigms such as movies has also provided analytic flexibility for these developmental studies that extends beyond conventional resting state approaches. This review highlights the advantages and challenges of using movies for developmental neuroimaging and explores some of the methodological issues involved in designing pediatric studies with movies. Emerging themes from movie-watching studies are discussed, including an emphasis on intersubject correlations, developmental changes in network interactions under complex naturalistic conditions, and dynamic age-related changes in both sensory and higher-order network FC even in narrow age ranges. Converging evidence suggests an enhanced ability to identify brain-behavior correlations in children when using movie-watching data relative to both resting state and conventional tasks. Future directions and cautionary notes highlight the potential and the limitations of using movies to study FC in pediatric populations., (Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Increased reaction time variability (RTV) is one of the most replicable behavioral correlates of attention-deficit/hyperactivity disorder (ADHD). However, this may not be specific to ADHD but a more general marker of psychopathology. Here we compare RT variability in individuals with ADHD and those with other childhood internalizing and externalizing conditions both in terms of standard (i.e., the standard deviation of reaction time) and alternative indices that capture low-frequency oscillatory patterns in RT variations over time thought to mark periodic lapses of attention in ADHD. A total of 667 participants (6-12 years old) were classified into non-overlapping diagnostic groups consisting of children with fear disorders (n = 91), distress disorders (n = 56), ADHD (n = 103), oppositional defiant or conduct disorder (ODD/CD; n = 40) and typically developing controls (TDC; n = 377). We used a simple two-choice reaction time task to measure reaction time. The strength of oscillations in RTs across the session was extracted using spectral analyses. Higher RTV was present in ADHD compared to all other disorder groups, effects that were equally strong across all frequency bands. Interestingly, we found that lower RTV to characterize ODD/CD relative to TDC, a finding that was more pronounced at lower frequencies. In general, our data support RTV as a specific marker of ADHD. RT variation across time in ADHD did not show periodicity in a specific frequency band, not supporting that ADHD RTV is the product of spontaneous periodic lapses of attention. Low-frequency oscillations may be particularly useful to differentiate ODD/CD from TDC.

Genetic factors are strongly implicated in the susceptibility to develop externalizing syndromes such as attention-deficit/hyperactivity disorder (ADHD), oppositional defiant disorder, conduct disorder, and substance use disorder (SUD). Variants in the ADGRL3 (LPHN3) gene predispose to ADHD and predict ADHD severity, disruptive behaviors comorbidity, long-term outcome, and response to treatment. In this study, we investigated whether variants within ADGRL3 are associated with SUD, a disorder that is frequently co-morbid with ADHD. Using family-based, case-control, and longitudinal samples from disparate regions of the world (n = 2698), recruited either for clinical, genetic epidemiological or pharmacogenomic studies of ADHD, we assembled recursive-partitioning frameworks (classification tree analyses) with clinical, demographic, and ADGRL3 genetic information to predict SUD susceptibility. Our results indicate that SUD can be efficiently and robustly predicted in ADHD participants. The genetic models used remained highly efficient in predicting SUD in a large sample of individuals with severe SUD from a psychiatric institution that were not ascertained on the basis of ADHD diagnosis, thus identifying ADGRL3 as a risk gene for SUD. Recursive-partitioning analyses revealed that rs4860437 was the predominant predictive variant. This new methodological approach offers novel insights into higher order predictive interactions and offers a unique opportunity for translational application in the clinical assessment of patients at high risk for SUD.