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      Neuroimaging in attention-deficit/hyperactivity disorder

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          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          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.

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          Most cited references49

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          Large-scale brain networks and psychopathology: a unifying triple network model.

          The science of large-scale brain networks offers a powerful paradigm for investigating cognitive and affective dysfunction in psychiatric and neurological disorders. This review examines recent conceptual and methodological developments which are contributing to a paradigm shift in the study of psychopathology. I summarize methods for characterizing aberrant brain networks and demonstrate how network analysis provides novel insights into dysfunctional brain architecture. Deficits in access, engagement and disengagement of large-scale neurocognitive networks are shown to play a prominent role in several disorders including schizophrenia, depression, anxiety, dementia and autism. Synthesizing recent research, I propose a triple network model of aberrant saliency mapping and cognitive dysfunction in psychopathology, emphasizing the surprising parallels that are beginning to emerge across psychiatric and neurological disorders. Copyright © 2011 Elsevier Ltd. All rights reserved.
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            Discovery of the first genome-wide significant risk loci for attention deficit/hyperactivity disorder

            Attention deficit/hyperactivity disorder (ADHD) is a highly heritable childhood behavioral disorder affecting 5% of children and 2.5% of adults. Common genetic variants contribute substantially to ADHD susceptibility, but no variants have been robustly associated with ADHD. We report a genome-wide association meta-analysis of 20,183 individuals diagnosed with ADHD and 35,191 controls that identifies variants surpassing genome-wide significance in 12 independent loci, finding important new information about the underlying biology of ADHD. Associations are enriched in evolutionarily constrained genomic regions and loss-of-function intolerant genes and around brain-expressed regulatory marks. Analyses of three replication studies: a cohort of individuals diagnosed with ADHD, a self-reported ADHD sample and a meta-analysis of quantitative measures of ADHD symptoms in the population, support these findings while highlighting study-specific differences on genetic overlap with educational attainment. Strong concordance with GWAS of quantitative population measures of ADHD symptoms supports that clinical diagnosis of ADHD is an extreme expression of continuous heritable traits.
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              Toward the future of psychiatric diagnosis: the seven pillars of RDoC

              Background Current diagnostic systems for mental disorders rely upon presenting signs and symptoms, with the result that current definitions do not adequately reflect relevant neurobiological and behavioral systems - impeding not only research on etiology and pathophysiology but also the development of new treatments. Discussion The National Institute of Mental Health began the Research Domain Criteria (RDoC) project in 2009 to develop a research classification system for mental disorders based upon dimensions of neurobiology and observable behavior. RDoC supports research to explicate fundamental biobehavioral dimensions that cut across current heterogeneous disorder categories. We summarize the rationale, status and long-term goals of RDoC, outline challenges in developing a research classification system (such as construct validity and a suitable process for updating the framework) and discuss seven distinct differences in conception and emphasis from current psychiatric nosologies. Summary Future diagnostic systems cannot reflect ongoing advances in genetics, neuroscience and cognitive science until a literature organized around these disciplines is available to inform the revision efforts. The goal of the RDoC project is to provide a framework for research to transform the approach to the nosology of mental disorders.
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                Author and article information

                Journal
                Curr Opin Psychiatry
                Curr Opin Psychiatry
                COIP
                Current Opinion in Psychiatry
                Lippincott Williams & Wilkins (Hagerstown, MD )
                0951-7367
                1473-6578
                March 2021
                15 January 2021
                : 34
                : 2
                : 105-111
                Affiliations
                [a ]Department of Child and Adolescent Psychiatry, NYU Grossman School of Medicine, New York, New York, USA
                [b ]Department of Psychiatry and Medical Psychology, Clínica Universidad de Navarra, Pamplona, Navarra, Spain
                [c ]Center of Brain Imaging and Neuromodulation, Nathan Kline Institute of Psychiatric Research, Orangeburg, New York, USA
                Author notes
                Correspondence to Francisco X. Castellanos, MD, Department of Child and Adolescent Psychiatry, NYU Grossman School of Medicine. Child Study Center, 1 Park Avenue, New York, NY 10016, USA. Tel: +1 646 754 5000; e-mail: francisco.castellanos@ 123456nyulangone.org
                Article
                YCO340209 00006
                10.1097/YCO.0000000000000669
                7879851
                33278156
                6f64a948-0748-4b01-a54a-eac19b5e64ae
                Copyright © 2020 The Author(s). Published by Wolters Kluwer Health, Inc.

                This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc-nd/4.0

                History
                Categories
                NEURODEVELOPMENTAL DISORDERS: Edited by James C. Harris
                Custom metadata
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                attention-deficit/hyperactivity disorder,mri,neuroimaging,personalized medicine

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