Neuroimaging in attention-deficit/hyperactivity disorder

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 findi...

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Detalles Bibliográficos
Autores: Pereira-Sánchez, V. (Víctor)|||/items/af1d13b6-cb1b-43ec-a926-7387f05a949d, Castellanos, F.X. (Francisco X.)|||/items/96b377d4-821d-4950-bfb2-6d22cc924eba
Tipo de recurso: artículo
Fecha de publicación:2021
País:España
Institución:Universidad de Navarra
Repositorio:Dadun. Depósito Académico Digital de la Universidad de Navarra
Idioma:inglés
OAI Identifier:oai:dadun.unav.edu:10171/116321
Acceso en línea:https://hdl.handle.net/10171/116321
Access Level:acceso abierto
Palabra clave:Attention-deficit/hyperactivity disorder
MRI
Neuroimaging
Personalized medicine
Descripción
Sumario: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.