ArticleNature communications2024
A multi-modal, asymmetric, weighted, and signed description of anatomical connectivity.
Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Human cortical networks trade communication efficiency for computational reliability.Science advances · 2026Article
- Multi-Scale Structural MRI Features Reveal Task-Based Functional Connectivity and Its Alterations in Psychiatric Disorders: A Collaborative Graph Attention Network Approach.Brain topography · 2026Article
- Spatiotemporal patterns and optimization of dominant and recessive morphology of cultivated land use in the Ili River Valley.iScience · 2026Article
- Task-induced topological and geometrical changes in whole-brain dynamics predict cognitive individual differences.bioRxiv : the preprint server for biology · 2026Article
- Competitive interactions shape mammalian brain network dynamics and computation.Nature neuroscience · 2026Article
- The structural grammar of integration and competition in the human connectome.Frontiers in computational neuroscience · 2026Article
- Human cortical dynamics reflect graded contributions of local geometry and network topography.Nature communications · 2025Article
- Article
- The Constrained Disorder Principle: A Paradigm Shift for Accurate Interactome Mapping and Information Analysis in Complex Biological Systems.Bioengineering (Basel, Switzerland) · 2025Review
- Structurally informed resting-state effective connectivity recapitulates cortical hierarchy.bioRxiv : the preprint server for biology · 2025Article
- Bridging local and global dynamics: a biologically grounded model for cooperative and competitive interactions in the brain.bioRxiv : the preprint server for biology · 2025Article
- Spectral imprint of structural embedding in effective connectivity.bioRxiv : the preprint server for biology · 2025Article
- Structurally informed models of directed brain connectivity.Nature reviews. Neuroscience · 2025Review
- The impact of input node placement in the controllability of structural brain networks.Scientific reports · 2024Article
- Analyzing asymmetry in brain hierarchies with a linear state-space model of resting-state fMRI data.Network neuroscience (Cambridge, Mass.) · 2024Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The macroscale connectome is the network of physical, white-matter tracts between brain areas. The connections are generally weighted and their values interpreted as measures of communication efficacy. In most applications, weights are either assigned based on imaging features-e.g. diffusion parameters-or inferred using statistical models. In reality, the ground-truth weights are unknown, motivating the exploration of alternative edge weighting schemes. Here, we explore a multi-modal, regression-based model that endows reconstructed fiber tracts with directed and signed weights. We find that the model fits observed data well, outperforming a suite of null models. The estimated weights are subject-specific and highly reliable, even when fit using relatively few training samples, and the networks maintain a number of desirable features. In summary, we offer a simple framework for weighting connectome data, demonstrating both its ease of implementation while benchmarking its utility for typical connectome analyses, including graph theoretic modeling and brain-behavior associations.
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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 Socratic graph.