ArticleNeuroImage2020
The effect of network thresholding and weighting on structural brain networks in the UK Biobank.
Article in NeuroImage, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 72 papers.
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Who cites it
72 citing papers in PubMed.
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- Demographics change the relationships between socioeconomic status, white matter network organization, and cognition in children.Developmental cognitive neuroscience · 2026Article
- The microstructure-weighted human connectome: network properties and structure-function correlations across spatial scales.bioRxiv : the preprint server for biology · 2026Article
- General cognitive function and the brain's structural connectome.bioRxiv : the preprint server for biology · 2026Article
- Shared and Specific Patterns of Brain Functional Network Abnormalities in Patients With Idiopathic Dystonia and Across Subtypes.CNS neuroscience & therapeutics · 2026Article
- Associations of Racial Discrimination with Resting-state Network Topology: A Mechanism for Post-traumatic Sensory Disruptions.Research square · 2026Article
- Alterations of white matter connectivity in alopecia areata patients.Brain imaging and behavior · 2026Article
- Critical and non-critical connections not differently associated with either Alzheimer's disease or vascular pathologies.medRxiv : the preprint server for health sciences · 2026Article
- Non-invasive preoperative prediction of surgical outcomes in drug-resistant epilepsy using seizure-related EEG network dynamics.Frontiers in neuroscience · 2026Article
- Higher-order statistics for constructing centered edge functional connectivity.Network neuroscience (Cambridge, Mass.) · 2026Article
- Multidimensional structural-functional coupling uncovers network dysregulation and predicts binge-eating severity in bulimia nervosa.BMC medicine · 2025Article
- Relative Strength Variability Measures for Brain Structural Connectomes and Their Relationship With Cognitive Functioning.Human brain mapping · 2025Article
- Tracking causal pathways in TMS-evoked brain responses.PLoS computational biology · 2025Article
- Amyloid pathology related to aberrant structure-function coupling of brain networks in Alzheimer's disease: insights from [European journal of nuclear medicine and molecular imaging · 2025Article
- More Than the Sum of Its Parts: Disrupted Core Periphery of Multiplex Brain Networks in Multiple Sclerosis.Human brain mapping · 2025Article
- Audiovisual integration and whole-brain networks in preterm and full-term neonates: A two-layer multiplex network perspective on structural and functional connectivity.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- TIME: Tractography-Informed myelin estimation.NeuroImage. Clinical · 2025Article
- Elevated Activity in Left Homologous Music Circuits Is Inhibitory for Music Perception but Mediated by Structure-Function Coupling.CNS neuroscience & therapeutics · 2024Article
- Sex Differences in Hierarchical and Modular Organization of Functional Brain Networks: Insights from Hierarchical Entropy and Modularity Analysis.Entropy (Basel, Switzerland) · 2024Article
12 more citing papers are in PubMed but not listed here.
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Authors and funding
8 authors.
Funding
Abstract
Whole-brain structural networks can be constructed using diffusion MRI and probabilistic tractography. However, measurement noise and the probabilistic nature of the tracking procedure result in an unknown proportion of spurious white matter connections. Faithful disentanglement of spurious and genuine connections is hindered by a lack of comprehensive anatomical information at the network-level. Therefore, network thresholding methods are widely used to remove ostensibly false connections, but it is not yet clear how different thresholding strategies affect basic network properties and their associations with meaningful demographic variables, such as age. In a sample of 3153 generally healthy volunteers from the UK Biobank Imaging Study (aged 44-77 years), we constructed whole-brain structural networks and applied two principled network thresholding approaches (consistency and proportional thresholding). These were applied over a broad range of threshold levels across six alternative network weightings (streamline count, fractional anisotropy, mean diffusivity and three novel weightings from neurite orientation dispersion and density imaging) and for four common network measures (mean edge weight, characteristic path length, network efficiency and network clustering coefficient). We compared network measures against age associations and found that: 1) measures derived from unthresholded matrices yielded the weakest age-associations (0.033 ≤ |β| ≤ 0.409); and 2) the most commonly-used level of proportional-thresholding from the literature (retaining 68.7% of all possible connections) yielded significantly weaker age-associations (0.070 ≤ |β| ≤ 0.406) than the consistency-based approach which retained only 30% of connections (0.140 ≤ |β| ≤ 0.409). However, we determined that the stringency of the threshold was a stronger determinant of the network-age association than the choice of threshold method and the two thresholding approaches identified a highly overlapping set of connections (ICC = 0.84), when matched at 70% network sparsity. Generally, more stringent thresholding resulted in more age-sensitive network measures in five of the six network weightings, except at the highest levels of sparsity (>90%), where crucial connections were then removed. At two commonly-used threshold levels, the age-associations of the connections that were discarded (mean β ≤ |0.068|) were significantly smaller in magnitude than the corresponding age-associations of the connections that were retained (mean β ≤ |0.219|, p < 0.001, uncorrected). Given histological evidence of widespread degeneration of structural brain connectivity with increasing age, these results indicate that stringent thresholding methods may be most accurate in identifying true white matter connections.
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