ArticlePloS one2017
Accounting for the complex hierarchical topology of EEG phase-based functional connectivity in network binarisation.
Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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13 citing papers in PubMed.
- Planning-related hubs and brain network organization during motor decision-making.Brain structure & function · 2026Article
- Sensorimotor postural training induces multi-level cortical network reorganization in older adults enhancing efficiency and resilience.GeroScience · 2026Article
- Role of Sex in Shaping Brain Network Organization During Reading in Developmental Dyslexia.Children (Basel, Switzerland) · 2025Article
- Primate brain pattern-based automated Alzheimer's disease detection model using EEG signals.Cognitive neurodynamics · 2023Article
- Abnormal Functional Hierarchies of EEG Networks in Familial and Sporadic Prodromal Alzheimer's Disease During Visual Short-Term Memory Binding.Frontiers in neuroimaging · 2022Article
- Electroconvulsive Therapy-Induced Changes in Functional Brain Network of Major Depressive Disorder Patients: A Longitudinal Resting-State Electroencephalography Study.Frontiers in human neuroscience · 2022Article
- Ranking of communities in multiplex spatiotemporal models of brain dynamics.Applied network science · 2022Article
- Altered electroencephalographic networks in developmental dyslexia after remedial training: a prospective case-control study.Neural regeneration research · 2021Article
- Brain network reorganisation and spatial lesion distribution in systemic lupus erythematosus.Lupus · 2021Article
- Normalised degree variance.Applied network science · 2020Article
- On neighbourhood degree sequences of complex networks.Scientific reports · 2019Article
- Hierarchical complexity of the adult human structural connectome.NeuroImage · 2019Article
- Network analysis through the use of joint-distribution entropy on EEG recordings of MCI patients during a visual short-term memory binding task.Healthcare technology letters · 2019Article
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3 authors.
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Abstract
Research into binary network analysis of brain function faces a methodological challenge in selecting an appropriate threshold to binarise edge weights. For EEG phase-based functional connectivity, we test the hypothesis that such binarisation should take into account the complex hierarchical structure found in functional connectivity. We explore the density range suitable for such structure and provide a comparison of state-of-the-art binarisation techniques, the recently proposed Cluster-Span Threshold (CST), minimum spanning trees, efficiency-cost optimisation and union of shortest path graphs, with arbitrary proportional thresholds and weighted networks. We test these techniques on weighted complex hierarchy models by contrasting model realisations with small parametric differences. We also test the robustness of these techniques to random and targeted topological attacks. We find that the CST performs consistenty well in state-of-the-art modelling of EEG network topology, robustness to topological network attacks, and in three real datasets, agreeing with our hypothesis of hierarchical complexity. This provides interesting new evidence into the relevance of considering a large number of edges in EEG functional connectivity research to provide informational density in the topology.
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