Objective: The authors performed a comprehensive meta-analysis of task-based functional MRI studies of attention deficit hyperactivity disorder (ADHD). Method: The authors searched PubMed, Ovid, EMBASE, Web of Science, ERIC, CINAHAL, and NeuroSynth for studies published through June 30, 2011. Significant differences in brain region activation between individuals with ADHD and comparison subjects were detected using activation likelihood estimation meta-analysis. Dysfunctional regions in ADHD were related to seven reference neuronal systems. The authors performed a set of meta-analyses focused on age groups (children and adults), clinical characteristics (history of stimulant treatment and presence of psychiatric comorbidities), and specific neuropsychological tasks (inhibition, working memory, and vigilance/attention). Results: Fifty-five studies were included (39 for children and 16 tor adults). In children, hypoactivation in ADHD relative to comparison subjects was observed mostly in systems involved in executive function (frontoparietal network) and attention (ventral attentional network). Significant hyperactivation in ADHD relative to comparison subjects was observed predominantly in the default, ventral attention, and somatomotor networks. In adults, ADHD-related hypoactivation was predominant in the frontoparietal system, while ADHD-related hyperactivation was present in the visual, dorsal attention, and default networks. Significant ADHD-related dysfunction largely reflected task features and was detected even in the absence of comorbid mental disorders or a history of. stimulant treatment. Conclusions: A growing literature provides evidence of ADHD-related dysfunction in multiple neuronal systems involved in higher-level cognitive functions but also in sensorimotor processes, including the visual system, and in the default network. This meta-analytic evidence extends early models of ADHD pathophysiology that were focused on prefrontal-striatal circuits.
Toward Systems Neuroscience of ADHD: A Meta-Analysis of 55 fMRI Studies
DI MARTINO, ADRIANA;
2012-01-01
Abstract
Objective: The authors performed a comprehensive meta-analysis of task-based functional MRI studies of attention deficit hyperactivity disorder (ADHD). Method: The authors searched PubMed, Ovid, EMBASE, Web of Science, ERIC, CINAHAL, and NeuroSynth for studies published through June 30, 2011. Significant differences in brain region activation between individuals with ADHD and comparison subjects were detected using activation likelihood estimation meta-analysis. Dysfunctional regions in ADHD were related to seven reference neuronal systems. The authors performed a set of meta-analyses focused on age groups (children and adults), clinical characteristics (history of stimulant treatment and presence of psychiatric comorbidities), and specific neuropsychological tasks (inhibition, working memory, and vigilance/attention). Results: Fifty-five studies were included (39 for children and 16 tor adults). In children, hypoactivation in ADHD relative to comparison subjects was observed mostly in systems involved in executive function (frontoparietal network) and attention (ventral attentional network). Significant hyperactivation in ADHD relative to comparison subjects was observed predominantly in the default, ventral attention, and somatomotor networks. In adults, ADHD-related hypoactivation was predominant in the frontoparietal system, while ADHD-related hyperactivation was present in the visual, dorsal attention, and default networks. Significant ADHD-related dysfunction largely reflected task features and was detected even in the absence of comorbid mental disorders or a history of. stimulant treatment. Conclusions: A growing literature provides evidence of ADHD-related dysfunction in multiple neuronal systems involved in higher-level cognitive functions but also in sensorimotor processes, including the visual system, and in the default network. This meta-analytic evidence extends early models of ADHD pathophysiology that were focused on prefrontal-striatal circuits.
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