ArticleNetwork neuroscience (Cambridge, Mass.)2021
Combining network topology and information theory to construct representative brain networks.
Article in Network neuroscience (Cambridge, Mass.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers, 1 of them a synthesis that pooled it.
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Who cites it
47 citing papers in PubMed, 1 synthesis or guideline pooled it.
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- Ecologically-Valid Emotion Signatures Enhance Mood Disorder Diagnostics.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Dynamics of brain connectivity across the Alzheimer's disease spectrum through magnetoencephalography.Scientific reports · 2026Article
- Capturing the emergent dynamical structure in biophysical neural models.PLoS computational biology · 2025Article
- General anaesthesia decreases the uniqueness of brain functional connectivity across individuals and species.Nature human behaviour · 2025Article
- Association of Bidirectional Network Cores in the Brain with Perceptual Awareness and Cognition.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
- Typical and disrupted small-world architecture and regional communication in full-term and preterm infants.PNAS nexus · 2025Article
- Association of bidirectional network cores in the brain with perceptual awareness and cognition.bioRxiv : the preprint server for biology · 2025Article
- Mapping the aggregate g-ratio of white matter tracts using multi-modal MRI.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Altered integrated and segregated states in cocaine use disorder.Frontiers in neuroscience · 2025Article
- Low-dimensional controllability of brain networks.PLoS computational biology · 2025Article
- The impact of smartphone use on working memory in college students: a functional near-infrared spectroscopy study.Frontiers in psychiatry · 2025Article
- Genetic fingerprinting with heritable phenotypes of the resting-state brain network topology.Communications biology · 2024Article
- Dataset factors associated with age-related changes in brain structure and function in neurodevelopmental conditions.Human brain mapping · 2024Article
- Contributions of network structure, chemoarchitecture and diagnostic categories to transitions between cognitive topographies.Nature biomedical engineering · 2024Article
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2 authors.
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Abstract
Network neuroscience employs graph theory to investigate the human brain as a complex network, and derive generalizable insights about the brain's network properties. However, graph-theoretical results obtained from network construction pipelines that produce idiosyncratic networks may not generalize when alternative pipelines are employed. This issue is especially pressing because a wide variety of network construction pipelines have been employed in the human network neuroscience literature, making comparisons between studies problematic. Here, we investigate how to produce networks that are maximally representative of the broader set of brain networks obtained from the same neuroimaging data. We do so by minimizing an information-theoretic measure of divergence between network topologies, known as the portrait divergence. Based on functional and diffusion MRI data from the Human Connectome Project, we consider anatomical, functional, and multimodal parcellations at three different scales, and 48 distinct ways of defining network edges. We show that the highest representativeness can be obtained by using parcellations in the order of 200 regions and filtering functional networks based on efficiency-cost optimization-though suitable alternatives are also highlighted. Overall, we identify specific node definition and thresholding procedures that neuroscientists can follow in order to derive representative networks from their human neuroimaging data.
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