ArticleNeuroImage2019
The community structure of functional brain networks exhibits scale-specific patterns of inter- and intra-subject variability.
Article in NeuroImage, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
58 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Co-alteration Network Architecture of Major Depressive Disorder: A Multi-modal Neuroimaging Assessment of Large-scale Disease Effects.Neuroinformatics · 2023Pooled it
- Individual-fMRI-approaches reveal cerebellum and visual communities to be functionally connected in obsessive compulsive disorder.Scientific reports · 2021Trial
- A neuro-synthesis of psychological constructs relevant to posttraumatic stress disorder.Scientific reports · 2026Article
- The dual interpretation of edge time series: Time-varying connectivity versus statistical interaction.iScience · 2026Article
- Methylphenidate stabilizes dynamic brain network organization during tasks probing attention and reward processing in stimulant-naïve children with ADHD.Translational psychiatry · 2025Article
- Cognitive and neural mechanisms of mental imagery supporting creative cognition.Communications biology · 2025Article
- Geometric constraints on the architecture of mammalian cortical connectomes.bioRxiv : the preprint server for biology · 2025Article
- Leveraging multivariate information for community detection in functional brain networks.Communications biology · 2025Article
- Multimodal gradients unify local and global cortical organization.Nature communications · 2025Article
- Partial correlation as a tool for mapping functional-structural correspondence in human brain connectivity.Network neuroscience (Cambridge, Mass.) · 2025Article
- Deep learning-based embedding of functional connectivity profiles for precision functional mapping.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Kernel machine tests of association using extrinsic and intrinsic cluster evaluation metrics.PLoS computational biology · 2024Article
- Effects of connectivity hyperalignment (CHA) on estimated brain network properties: from coarse-scale to fine-scale.bioRxiv : the preprint server for biology · 2024Article
- The multiscale topological organization of the functional brain network in adolescent PTSD.Cerebral cortex (New York, N.Y. : 1991) · 2024Article
- A Brainwide Risk Score for Psychiatric Disorder Evaluated in a Large Adolescent Population Reveals Increased Divergence Among Higher-Risk Groups Relative to Control Participants.Biological psychiatry · 2024Article
- Article
- Modular subgraphs in large-scale connectomes underpin spontaneous co-fluctuation events in mouse and human brains.Communications biology · 2024Article
- Unraveling neural complexity: Exploring brain entropy to yield mechanistic insight in neuromodulation therapies for tobacco use disorder.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- covSTATIS: a multi-table technique for network neuroscience.Aperture neuro · 2024Article
- Dimensions of early life adversity and their associations with functional brain organisation.Imaging neuroscience (Cambridge, Mass.) · 2024Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
The network organization of the human brain varies across individuals, changes with development and aging, and differs in disease. Discovering the major dimensions along which this variability is displayed remains a central goal of both neuroscience and clinical medicine. Such efforts can be usefully framed within the context of the brain's modular network organization, which can be assessed quantitatively using computational techniques and extended for the purposes of multi-scale analysis, dimensionality reduction, and biomarker generation. Although the concept of modularity and its utility in describing brain network organization is clear, principled methods for comparing multi-scale communities across individuals and time are surprisingly lacking. Here, we present a method that uses multi-layer networks to simultaneously discover the modular structure of many subjects at once. This method builds upon the well-known multi-layer modularity maximization technique, and provides a viable and principled tool for studying differences in network communities across individuals and within individuals across time. We test this method on two datasets and identify consistent patterns of inter-subject community variability, demonstrating that this variability - which would be undetectable using past approaches - is associated with measures of cognitive performance. In general, the multi-layer, multi-subject framework proposed here represents an advance over current approaches by straighforwardly mapping community assignments across subjects and holds promise for future investigations of inter-subject community variation in clinical populations or as a result of task constraints.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.