Head Motion During MRI Predicted by out-of-Scanner Sustained Attention Performance in Attention-Deficit/Hyperactivity Disorder

Thomson, Phoebe; Johnson, Katherine A.; Malpas, Charles B; Efron, Daryl; Sciberras, Emma; Silk, Tim

doi:10.1177/1087054720911988

Cited by 14 publications

(9 citation statements)

References 56 publications

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“…The amount of measurement error in brain morphology may differ across children with versus without ADHD. In fact, children with impulsivity and inattention have been shown to move more during MRI scanning ( Thomson et al, 2021 ; Kong et al, 2014 ), determining different levels of error in the brain morphology assessments ( Figure 7 , path from ADHD symptoms to motion to error in MRI measurement). In this scenario, adjusting for motion might lead to two situations.…”

Section: Resultsmentioning

confidence: 99%

Attention-deficit hyperactivity disorder symptoms and brain morphology: Examining confounding bias

Dall'Aglio

Kim

Lamballais

et al. 2022

eLife

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Background: Associations between attention-deficit/hyperactivity disorder (ADHD) and brain morphology have been reported, although with several inconsistencies. These may partly stem from confounding bias, which could distort associations and limit generalizability. We examined how associations between brain morphology and ADHD symptoms change with adjustments for potential confounders typically overlooked in the literature (aim 1), and for IQ and head motion, which are typically corrected for but play ambiguous roles (aim 2).Methods: Participants were 10-year-old children from the Adolescent Brain Cognitive Development (N=7,722) and Generation R (N=2,531) studies. Cortical area, volume, and thickness were measured with MRI and ADHD symptoms with the Child Behavior Checklist. Surface-based cross-sectional analyses were run.Results: ADHD symptoms related to widespread cortical regions when solely adjusting for demographic factors. Additional adjustments for socioeconomic and maternal behavioral confounders (aim 1) generally attenuated associations, as cluster sizes halved and effect sizes substantially reduced. Cluster sizes further changed when including IQ and head motion (aim 2), however, we argue that adjustments might have introduced bias.Conclusions: Careful confounder selection and control can help identify more robust and specific regions of associations for ADHD symptoms, across two cohorts. We provided guidance to minimizing confounding bias in psychiatric neuroimaging.Funding: Authors are supported by an NWO-VICI grant (NWO-ZonMW: 016.VICI.170.200 to HT) for HT, LDA, SL, and the Sophia Foundation S18-20, and Erasmus University and Erasmus MC Fellowship for RLM.

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Section: Resultsmentioning

confidence: 99%

Attention-deficit hyperactivity disorder symptoms and brain morphology: Examining confounding bias

Dall'Aglio

Kim

Lamballais

et al. 2022

eLife

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“…The reproducible identification of RSFC subtypes across individuals who meet typical inclusion criteria and those often excluded from neurodevelopmental research due to noisy data could have significant implications for improving retention and representation in these studies. Historically, individuals who exhibit high motion during scans, often those with pronounced behavioral problems or cognitive impairments (Thomson et al, 2021), are excluded from neurodevelopmental research. This exclusion has limited our understanding of brain-behavior relationships in those who might benefit most from such insights (Satterthwaite et al, 2012).…”

Section: Discussionmentioning

confidence: 99%

Neurodevelopmental Subtypes of Functional Brain Organization in the ABCD Study Using a Rigorous Analytic Framework

DeRosa,

Friedman,

Calhoun

et al. 2024

Preprint

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The current study demonstrates that an individual's resting-state functional connectivity (RSFC) is a dependable biomarker for identifying differential patterns of cognitive and emotional functioning during late childhood. Using baseline RSFC data from the Adolescent Brain Cognitive Development (ABCD) study, which includes children aged 9-11, we identified four distinct RSFC subtypes We introduce an integrated methodological pipeline for testing the reliability and importance of these subtypes. In the Identification phase, Leiden Community Detection defined RSFC subtypes, with their reproducibility confirmed through a split-sample technique in the Validation stage. The Evaluation phase showed that distinct cognitive and mental health profiles are associated with each subtype, with the Predictive phase indicating that subtypes better predict various cognitive and mental health characteristics than individual RSFC connections. The Replication stage employed bootstrapping and down-sampling methods to substantiate the reproducibility of these subtypes further. This work allows future explorations of developmental trajectories of these RSFC subtypes.

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“…With head motion linked to age and ADHD diagnosis, inclusion as a covariate likely results in an underestimation of effects of interest (Dosenbach et al, 2017 ; Kong et al, 2014 ; Thomson et al, 2021 ). However, given the potential for motion in our sample and to ensure confidence in findings, models were rerun in two motion-matched subsamples following the matching approach of Satterthwaite et al ( 2013 ).…”

Section: Methodsmentioning

confidence: 99%

Longitudinal maturation of resting state networks: Relevance to sustained attention and attention deficit/hyperactivity disorder

Thomson

Malpas

Vijayakumar

et al. 2022

Cogn Affect Behav Neurosci

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The transition from childhood to adolescence involves important neural function, cognition, and behavior changes. However, the links between maturing brain function and sustained attention over this period could be better understood. This study examined typical changes in network functional connectivity over childhood to adolescence, developmental differences in attention deficit/hyperactivity disorder (ADHD), and how functional connectivity might underpin variability in sustained attention development in a longitudinal sample. A total of 398 resting state scans were collected from 173 children and adolescents (88 ADHD, 85 control) at up to three timepoints across ages 9-14 years. The effects of age, sex, and diagnostic group on changes in network functional connectivity were assessed, followed by relationships between functional connectivity and sustained attention development using linear mixed effects modelling. The ADHD group displayed greater decreases in functional connectivity between salience and visual networks compared with controls. Lower childhood functional connectivity between the frontoparietal and several brain networks was associated with more rapid sustained attention development, whereas frontoparietal to dorsal attention network connectivity related to attention trajectories in children with ADHD alone. Brain network segregation may increase into adolescence as predicted by key developmental theories; however, participants with ADHD demonstrated altered developmental trajectories between salience and visual networks. The segregation of the frontoparietal network from other brain networks may be a mechanism supporting sustained attention development. Frontoparietal to dorsal attention connectivity can be a focus for further work in ADHD.

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Head Motion During MRI Predicted by out-of-Scanner Sustained Attention Performance in Attention-Deficit/Hyperactivity Disorder

Cited by 14 publications

References 56 publications

Attention-deficit hyperactivity disorder symptoms and brain morphology: Examining confounding bias

Attention-deficit hyperactivity disorder symptoms and brain morphology: Examining confounding bias

Neurodevelopmental Subtypes of Functional Brain Organization in the ABCD Study Using a Rigorous Analytic Framework

Longitudinal maturation of resting state networks: Relevance to sustained attention and attention deficit/hyperactivity disorder

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