ArticleNature communications2018
Mapping higher-order relations between brain structure and function with embedded vector representations of connectomes.
Article in Nature communications, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers.
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Who cites it
52 citing papers in PubMed.
- Connectome-based predictive modeling of concurrent and longitudinal substance use vulnerability in adolescence.Developmental cognitive neuroscience · 2026Article
- Cross-atlas Identification of Narrative Hubs via Multi-embedding Graph Models in fMRI Data.Neuroinformatics · 2026Article
- Machine-enhanced reconstruction of functional connectomes unravels discriminative brain sub-systems in health and disease.Scientific reports · 2026Article
- Anomaly Detection for Structural and Functional Connectivity in Glioma Patients.NMR in biomedicine · 2026Article
- TransBrain: a computational framework for translating brain-wide phenotypes between humans and mice.Nature methods · 2026Article
- The network architecture of general intelligence in the human connectome.Nature communications · 2026Article
- Structural-functional fingerprinting for abnormalities investigation in glioma patients.Scientific reports · 2025Article
- Random Walk-Based Node Feature Learning for Major Depressive Disorder Identification Through Multi-Site rs-fMRI Data.Human brain mapping · 2025Article
- Krakencoder: a unified brain connectome translation and fusion tool.Nature methods · 2025Article
- Fully Hyperbolic Neural Networks: A Novel Approach to Studying Aging Trajectories.IEEE journal of biomedical and health informatics · 2025Article
- Diffusion wavelets on connectome: Localizing the sources of diffusion mediating structure-function mapping using graph diffusion wavelets.Network neuroscience (Cambridge, Mass.) · 2025Article
- Disruption of Multimodal Brain Networks and Structural-Functional Coupling in Adolescents with Major Depressive Disorder.Neuropsychiatric disease and treatment · 2025Article
- Neural network embedding of functional microconnectome.Network neuroscience (Cambridge, Mass.) · 2025Article
- Hyperbolic Graph Embedding of MEG Brain Networks to Study Brain Alterations in Individuals With Subjective Cognitive Decline.IEEE journal of biomedical and health informatics · 2024Article
- Triadic percolation induces dynamical topological patterns in higher-order networks.PNAS nexus · 2024Article
- A within-subject voxel-wise constant-block partial least squares correlation method to explore MRI-based brain structure-function relationship.Cognitive neurodynamics · 2024Article
- Unveiling the Core Functional Networks of Cognition: An Ontology-Guided Machine Learning Approach.bioRxiv : the preprint server for biology · 2024Article
- Literature mining discerns latent disease-gene relationships.Bioinformatics (Oxford, England) · 2024Article
- Open datasets and code for multi-scale relations on structure, function and neuro-genetics in the human brain.Scientific data · 2024Article
- How brain structure-function decoupling supports individual cognition and its molecular mechanism.Human brain mapping · 2024Article
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8 authors.
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Abstract
Connectomics generates comprehensive maps of brain networks, represented as nodes and their pairwise connections. The functional roles of nodes are defined by their direct and indirect connectivity with the rest of the network. However, the network context is not directly accessible at the level of individual nodes. Similar problems in language processing have been addressed with algorithms such as word2vec that create embeddings of words and their relations in a meaningful low-dimensional vector space. Here we apply this approach to create embedded vector representations of brain networks or connectome embeddings (CE). CE can characterize correspondence relations among brain regions, and can be used to infer links that are lacking from the original structural diffusion imaging, e.g., inter-hemispheric homotopic connections. Moreover, we construct predictive deep models of functional and structural connectivity, and simulate network-wide lesion effects using the face processing system as our application domain. We suggest that CE offers a novel approach to revealing relations between connectome structure and function.
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