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Altered structural connectivity in ADHD: a network based analysis

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Abstract

Attention deficit/hyperactivity disorder (ADHD) is increasingly being viewed as a dysfunction of distributed brain networks rather than focal abnormalities. Here we investigated the structural brain network differences in children and adolescents with ADHD and healthy controls, using graph theory metrics to describe the anatomic networks and connectivity patterns, and the Network Based Statistic (NBS) to isolate the network components that differ between the two groups. Using DWI high-angular resolution diffusion imaging (‘HARDI’), whole brain tractography was conducted on 21 ADHD-combined type boys (m 13.3 ± 1.9 yrs) and 21 typically developing boys (m 14.8 ± 2.1 yrs). This study presents a comprehensive structural network investigation in ADHD covering a range of commonly used methodologies, including both streamline and probabilistic tractography, tensor and constrained spherical deconvolution (CSD) models, as well as different edge weighting methods at a range of densities and t-thresholds. Using graph metrics, ADHD was associated with local neighbourhoods that were more modular and interconnected than controls, where there was a decrease in the global, long-range connections, indicating reduced communication between local, specialised networks in ADHD. ADHD presented with a sub-network of stronger connectivity encompassing bilateral frontostriatal connections as well as left occipital, temporal, and parietal regions, of which the white matter microstructure was associated with ADHD symptom severity. Probabilistic tractography using CSD and the Hagmann weighting method produced that highest stability and most robust network differences across t-thresholds. It demonstrates topological organisation disruption in distributed neural networks in ADHD, supportive of the theory of maturation delay in ADHD.

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Acknowledgments

The research was conducted within the Academic Child Psychiatry Unit, University of Melbourne, Royal Children’s Hospital (clinical research assessments and scans) and the Developmental Imaging research group, Murdoch Childrens Research Institute and the Children’s MRI Centre, Royal Children’s Hospital, Melbourne, Victoria (imaging analyses). It was also supported by the Murdoch Childrens Research Institute, the Royal Children’s Hospital, The Royal Children’s Hospital Foundation, Department of Paediatrics The University of Melbourne and the Victorian Government’s Operational Infrastructure Support Program. TS was supported by a NHMRC Career Development Award.

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Authors and Affiliations

  1. Developmental Imaging, Royal Children’s Hospital, Murdoch Childrens Research Institute, Melbourne, 3052, Australia

    Richard Beare, Chris Adamson, Veronika Vilgis, Marc L. Seal & Timothy J. Silk

  2. School of Psychological Sciences, Monash University, Melbourne, 3800, Australia

    Mark A. Bellgrove

  3. Academic Child Psychiatry Unit, Department of Paediatrics, Royal Children’s Hospital, University of Melbourne, Melbourne, 3052, Australia

    Veronika Vilgis & Alasdair Vance

  4. Department of Paediatrics, University of Melbourne, Melbourne, 3052, Australia

    Veronika Vilgis, Marc L. Seal & Timothy J. Silk

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  1. Richard Beare
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  2. Chris Adamson
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  4. Veronika Vilgis
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  7. Timothy J. Silk
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Correspondence to Timothy J. Silk.

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Funding

This work was supported by a Project Grant to MAB and AV (No. 569,533) and AV (No. 384,419) from the National Health and Medical Research Council of Australia.

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Authors declare no conflicts of interest.

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All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Approval was granted by the Royal Children’s Hospital Human Research Ethics Committee, Melbourne, Australia.

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Informed consent was obtained from all individual participants’ parents/guardians included in the study.

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Beare, R., Adamson, C., Bellgrove, M.A. et al. Altered structural connectivity in ADHD: a network based analysis. Brain Imaging and Behavior 11, 846–858 (2017). https://doi.org/10.1007/s11682-016-9559-9

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