ArticleNature communications2024
Higher-order connectomics of human brain function reveals local topological signatures of task decoding, individual identification, and behavior.
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 31 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
31 citing papers in PubMed.
- Structure Guides Function: Beyond Pairwise Neural Interactions.The Journal of comparative neurology · 2026Review
- Distributed Neural Substrates for Autonomic Control During Human Thermoregulation: Brain Network Configurations of Sympathetic and Parasympathetic Innervation.Brain topography · 2026Article
- Charting higher-order models of brain function beyond pairwise interactions.Nature communications · 2026Article
- Phase locking and multistability in the topological Kuramoto model on cell complexes.Nature communications · 2026Article
- Information theory for hypergraph similarity.Science advances · 2026Article
- Global topology of brain-wide co-fluctuations links task states, personality, and behavioral symptom dimensions.bioRxiv : the preprint server for biology · 2026Article
- Higher-order functional connectivity and topological analysis of multichannel fNIRS data.Biomedical optics express · 2026Article
- Astrocyte-mediated higher-order control of synaptic plasticity.Communications biology · 2026Article
- Reducibility of higher-order networks from dynamics.Nature communications · 2026Article
- A data-driven approach to identifying and evaluating connectivity-based neural correlates of conscious visual perception.Neuroscience of consciousness · 2026Article
- Positive psychology 4.0: a science of consequence for a world that can no longer wait.Frontiers in psychology · 2026Article
- The microscale organization of directed hypergraphs.Communications physics · 2026Article
- Modelling brain metabolism with interacting nonautonomous phase oscillators.Frontiers in network physiology · 2026Article
- THOI: An efficient and accessible library for computing higher-order interactions enhanced by batch-processing.PloS one · 2026Article
- Building blocks of functional connectivity measures for aperiodic electrophysiological brain signals.Neuroimage. Reports · 2025Article
- Large-scale brain mediation network based on resting-state functional MRI.Communications biology · 2025Article
- Cancer and Aging Biomarkers: Classification, Early Detection Technologies and Emerging Research Trends.Biosensors · 2025Review
- The topology of synergy: Linking topological and information-theoretic approaches to higher-order interactions in complex systems.PLoS computational biology · 2025Article
- High energy consumption characterizes abnormal brain state transitions in temporal lobe epilepsy.Neurobiology of disease · 2025Article
- Introduction to correlation networks: Interdisciplinary approaches beyond thresholding.Physics reports · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Traditional models of human brain activity often represent it as a network of pairwise interactions between brain regions. Going beyond this limitation, recent approaches have been proposed to infer higher-order interactions from temporal brain signals involving three or more regions. However, to this day it remains unclear whether methods based on inferred higher-order interactions outperform traditional pairwise ones for the analysis of fMRI data. To address this question, we conducted a comprehensive analysis using fMRI time series of 100 unrelated subjects from the Human Connectome Project. We show that higher-order approaches greatly enhance our ability to decode dynamically between various tasks, to improve the individual identification of unimodal and transmodal functional subsystems, and to strengthen significantly the associations between brain activity and behavior. Overall, our approach sheds new light on the higher-order organization of fMRI time series, improving the characterization of dynamic group dependencies in rest and tasks, and revealing a vast space of unexplored structures within human functional brain data, which may remain hidden when using traditional pairwise approaches.
Indexed as
Identifiers
What OpenQuestion holds
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.