ArticleNeuroImage2018
Functional brain connectivity is predictable from anatomic network's Laplacian eigen-structure.
Article in NeuroImage, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 71 papers.
What it found
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Who cites it
71 citing papers in PubMed.
- Variations of structural-functional coupling in post-traumatic stress disorder are associated with underlying molecular and transcriptional features.Psychological medicine · 2026Article
- Accurately modeling resting-brain functional connectivity using hypergraph neural field-Fourier deep neural network.Scientific reports · 2026Article
- Transcriptional correlates of structure-function coupling plasticity in trigeminal neuralgia: unveiling the synaptic and metabolic associations.The journal of headache and pain · 2026Article
- Decoupling of neurophysiological activity from structure mirrors global microarchitectural and neuromodulatory trends.Communications biology · 2026Article
- Global Signal Removal (GSR) as graph spatial filtering.bioRxiv : the preprint server for biology · 2026Article
- HONeD-in on Brain Activity: Deconvolving Passive Diffusion on the Structural Network from Functional Brain Signals.bioRxiv : the preprint server for biology · 2026Article
- Network Diffusion Modeling in Computational Neuroscience.Advances in experimental medicine and biology · 2026Article
- Investigating Brain Functional Connectivity and Its Correlation With Cognitive Dysfunction in Chronic Kidney Disease Patients via Resting-State fMRI.Brain and behavior · 2025Article
- The role of structural connectivity on brain function through a Markov model of signal transmission.bioRxiv : the preprint server for biology · 2025Article
- Large-scale comparative analysis reveals top graph signal processing features for subject identification.bioRxiv : the preprint server for biology · 2025Article
- Physical mechanisms of human brain functions.Quantitative biology (Beijing, China) · 2025Review
- Analyzing the brain's dynamic response to targeted stimulation using generative modeling.Network neuroscience (Cambridge, Mass.) · 2025Review
- Communication in Brain Circuits and Systems: a Primer.IEEE International Symposium on Circuits and Systems proceedings. IEEE International Symposium on Circuits and Systems · 2025Article
- Contributions of connectional pathways to shaping Alzheimer's disease pathologies.Brain communications · 2025Article
- The role of structural connectivity on brain function through a Markov model of signal transmission.PloS one · 2025Article
- Metric structural human connectomes: Localization and multifractality of eigenmodes.Network neuroscience (Cambridge, Mass.) · 2025Article
- Effects of childhood trauma on sustained attention in major depressive disorder: the mediating role of brain activity and functional connectivity.BMC psychiatry · 2024Article
- DFC-Igloo: A dynamic functional connectome learning framework for identifying neurodevelopmental biomarkers in very preterm infants.Computer methods and programs in biomedicine · 2024Article
- Comparing structure-function relationships in brain networks using EEG and fNIRS.Scientific reports · 2024Article
- Integrative, segregative, and degenerate harmonics of the structural connectome.Communications biology · 2024Article
11 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
How structural connectivity (SC) gives rise to functional connectivity (FC) is not fully understood. Here we mathematically derive a simple relationship between SC measured from diffusion tensor imaging, and FC from resting state fMRI. We establish that SC and FC are related via (structural) Laplacian spectra, whereby FC and SC share eigenvectors and their eigenvalues are exponentially related. This gives, for the first time, a simple and analytical relationship between the graph spectra of structural and functional networks. Laplacian eigenvectors are shown to be good predictors of functional eigenvectors and networks based on independent component analysis of functional time series. A small number of Laplacian eigenmodes are shown to be sufficient to reconstruct FC matrices, serving as basis functions. This approach is fast, and requires no time-consuming simulations. It was tested on two empirical SC/FC datasets, and was found to significantly outperform generative model simulations of coupled neural masses.
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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 OpenQuestion graph.