Altered resting functional network topology assessed using graph theory in youth with attention-deficit/hyperactivity disorder

Wang, Yanpei; Zuo, Chenyi; Xu, Qin; Liao, Shuirong; Kanji, Maihefulaiti; Wang, Daoyang

doi:10.1016/j.pnpbp.2019.109796

Cited by 27 publications

(15 citation statements)

References 33 publications

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“…9 This method has been applied in various neurodegenerative and neuropsychiatric diseases, but these MRI protocols are not feasible in routine clinical practice due to the long acquisition time required. [10][11][12][13] In addition, these studies were restricted to a group-level analysis. To resolve these problems, Tijms et al proposed single-subject brain networks based on the analysis of the similarities of gray matter features, using conventional 3D-T1 weighted images (T1WI) which are routinely obtained in clinical practice.…”

Section: Introductionmentioning

confidence: 99%

“…A graph theoretical analysis is a mathematical method that has been useful for analyses of brain connectivity networks with the use of functional MRI and diffusion tensor imaging (DTI) 9 . This method has been applied in various neurodegenerative and neuropsychiatric diseases, but these MRI protocols are not feasible in routine clinical practice due to the long acquisition time required 10–13 . In addition, these studies were restricted to a group‐level analysis.…”

Section: Introductionmentioning

confidence: 99%

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Altered Structural Brain Networks Related to Adrenergic/Muscarinic Receptor Autoantibodies in Chronic Fatigue Syndrome

Fujii

Sato

Kimura

et al. 2020

Journal of Neuroimaging

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Recent studies suggest that the autoantibodies against adrenergic/muscarinic receptors might be one of the causes and potential markers of myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). The purpose of this study was to investigate the structural network changes related to autoantibody titers against adrenergic/muscarinic receptors in ME/CFS by performing a single-subject gray matter similarity-based structural network analysis. METHODS: We prospectively examined 89 consecutive right-handed ME/CFS patients who underwent both brain MRI including 3D T1-wighted images and a blood analysis of autoantibodies titers against β1 adrenergic receptor (β1 AdR-Ab), β2 AdR-Ab, M3 acetylcholine receptor (M3 AchR-Ab), and M4 AchR-Ab. Single-subject gray matter similarity-based structural networks were extracted from segmented gray matter images for each patient. We calculated local network properties (betweenness centrality, clustering coefficient, and characteristic path length) and global network properties (normalized path length λ, normalized clustering coefficient γ, and small-world network value δ). We investigated the correlations between the autoantibody titers and regional gray matter/white matter volumes, the local network properties, and the global network properties. RESULTS: Betweenness centrality showed a significant positive correlation with β1-AdR-Ab in the right dorsolateral prefrontal cortex. The characteristic path length showed a significant negative correlation with β2-AdR-Ab in the right precentral gyrus. There were no significant correlations between the antibody titers and the regional gray matter/white matter volumes, and the global network properties. CONCLUSIONS: Our findings suggest that β1 AdR-Ab and β2 AdR-Ab are potential markers of ME/CFS.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Altered Structural Brain Networks Related to Adrenergic/Muscarinic Receptor Autoantibodies in Chronic Fatigue Syndrome

Fujii

Sato

Kimura

et al. 2020

Journal of Neuroimaging

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“…Network organisation is similarly modular, clustered, efficient, and assortative across the groups. In contrast, previous work in children with and without ADHD has found that reductions in strength, clustering, path length, and local efficiency are associated with inattentive behaviours and differ between these groups ( Wang et al, 2020 ). However, these broad differences in graph metrics could be indicative of global differences in mean functional connectivity between children with high and low attention, which was not controlled for in their group level analyses.…”

Section: Discussionmentioning

confidence: 63%

“…Only one study has examined the relationship between global properties of the functional connectome and behavioural difficulties in childhood. Inattentive behaviours in children with and without ADHD were associated with reduced strength, clustering, path length, and local efficiency ( Wang et al, 2020 ). However, it is unclear whether these differences in graph theory metrics are a result of overall differences in functional connectivity.…”

Section: Introductionmentioning

confidence: 99%

A transdiagnostic data-driven study of children’s behaviour and the functional connectome

Jones

Astle

2021

Developmental Cognitive Neuroscience

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Behavioural difficulties are seen as hallmarks of many neurodevelopmental conditions. Differences in functional brain organisation have been observed in these conditions, but little is known about how they are related to a child’s profile of behavioural difficulties. We investigated whether behavioural difficulties are associated with how the brain is functionally organised in an intentionally heterogeneous and transdiagnostic sample of 957 children aged 5–15. We used consensus community detection to derive data-driven profiles of behavioural difficulties and constructed functional connectomes from a subset of 238 children with resting-state functional Magnetic Resonance Imaging (fMRI) data. We identified three distinct profiles of behaviour that were characterised by principal difficulties with hot executive function, cool executive function, and learning. Global organisation of the functional connectome did not differ between the groups, but multivariate patterns of connectivity at the level of Intrinsic Connectivity Networks (ICNs), nodes, and hubs significantly predicted group membership in held-out data. Fronto-parietal connector hubs were under-connected in all groups relative to a comparison sample and children with hot vs cool executive function difficulties were distinguished by connectivity in ICNs associated with cognitive control, emotion processing, and social cognition. This demonstrates both general and specific neurodevelopmental risk factors in the functional connectome.

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“…The authors then followed this with a meta-analysis demonstrating that the hubs of the human connectome were more likely to contain grey matter lesions than non-hub regions across nine different disorders, including schizophrenia and Alzheimer’s disease. Many psychiatric and neurological disorders are associated with reduced brain global efficiency, including prenatal alcohol exposure (Wozniak et al, 2013) and fetal alcohol syndrome (Rodriguez et al, 2021), schizophrenia (Hummer et al, 2020), ADHD (Wang et al, 2020; Wang et al, 2021), generalized anxiety disorder (Guo et al, 2021), heavy smoking (Lin et al, 2015), and major depressive disorder (Meng et al, 2013; Wang et al, 2017; Zhi et al, 2018), among others. Additionally, prefrontal tDCS for alcohol use disorder increased brain network global efficiency (Holla et al, 2020), suggesting that normalizing network global efficiency might contribute to improved treatment outcomes from neuromodulation therapy.…”

Section: Discussionmentioning

confidence: 99%

The Resting-State Causal Human Connectome is Characterized by Hub Connectivity of Executive and Attentional Networks

Rawls

Kummerfeld

Mueller

et al. 2021

Preprint

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We introduce a data-driven causal discovery method (Greedy Adjacencies and Non-Gaussian Orientations; GANGO) for calculating a "causal connectome" of directed connectivity from resting-state fMRI data and characterizing hubs of directed information transfer across the human cortex. Prominent hubs of the causal connectome were situated in attentional (dorsal attention) and executive (frontoparietal and cingulo-opercular) networks. These hub networks had distinctly different connectivity profiles. Attentional networks shared incoming connections with sensory regions and outgoing connections with higher cognitive networks, while executive networks primarily connected to other higher cognitive networks and had a high degree of bidirected connectivity. Virtual lesion analyses accentuated these findings, demonstrating that attentional and executive hubs are points of critical vulnerability in the human causal connectome. These data highlight the central role of attention and executive control networks in the human cortical connectome and set the stage for future applications of data-driven causal ("effective") connectivity analysis in psychiatry.

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Altered resting functional network topology assessed using graph theory in youth with attention-deficit/hyperactivity disorder

Cited by 27 publications

References 33 publications

Altered Structural Brain Networks Related to Adrenergic/Muscarinic Receptor Autoantibodies in Chronic Fatigue Syndrome

Altered Structural Brain Networks Related to Adrenergic/Muscarinic Receptor Autoantibodies in Chronic Fatigue Syndrome

A transdiagnostic data-driven study of children’s behaviour and the functional connectome

The Resting-State Causal Human Connectome is Characterized by Hub Connectivity of Executive and Attentional Networks

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