ArticleHuman brain mapping2018
Statistical inference in brain graphs using threshold-free network-based statistics.
Article in Human brain mapping, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers.
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Who cites it
47 citing papers in PubMed.
- White matter microstructure and motor function in amnestic mild cognitive impairment and Alzheimer's dementia.Neuroimage. Reports · 2026Article
- Brain Graph Sparsification for fMRI-based Connectome Analysis: A Methodological Review.Neuroinformatics · 2026Review
- Neurophysiological Functional Connectivity Changes during Difficult Listening in Older and Younger Adults.bioRxiv : the preprint server for biology · 2026Article
- Shared subcortical-default mode morphological dysconnectivity in adolescent bipolar disorder, major depressive disorder and schizophrenia.Communications biology · 2026Article
- Long-Acting Naltrexone Restores Network Connectivity in Subjects With Comorbid Cannabis and Opioid Use Disorder.Addiction biology · 2026Article
- Functional Connectivity Linked to Cognitive Recovery After Minor Stroke.Annals of clinical and translational neurology · 2026Article
- The Incremental Cluster Threshold-Free Cluster Enhancement Algorithm for Functional Connectivity Analysis.bioRxiv : the preprint server for biology · 2026Article
- White matter changes in reward circuits of amyotrophic lateral sclerosis: a fixel-based study of appetite loss.BMC medicine · 2026Article
- Longitudinal quantitative streamline tractography: robust estimation of white matter connectivity differences.bioRxiv : the preprint server for biology · 2026Article
- Altered structural connectivity in white matter lesion-induced mild cognitive impairment: a probabilistic fiber tracking and graph theory analysis.Frontiers in neural circuits · 2026Article
- Impact of tractogram filtering and graph creation for structural connectomics in subjects with Parkinson's disease.Frontiers in human neuroscience · 2026Article
- Long-acting naltrexone restores network connectivity in subjects with co-morbid cannabis and opioid use disorder.bioRxiv : the preprint server for biology · 2025Article
- Structural connectome construction using constrained spherical deconvolution in multi-shell diffusion-weighted magnetic resonance imaging.Nature protocols · 2025Review
- Introduction to correlation networks: Interdisciplinary approaches beyond thresholding.Physics reports · 2025Article
- Juvenile Myoclonic Epilepsy Imaging Endophenotypes and Relationship With Cognition and Resting-State EEG.Human brain mapping · 2025Article
- Cortical Morphological Networks Differ Between Gyri and Sulci.Neuroscience bulletin · 2025Article
- Multiscale comparative connectomics.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Alterations of upper-extremity functional muscle networks in chronic stroke survivors.Experimental brain research · 2024Article
- Morphological Brain Networks of White Matter: Mapping, Evaluation, Characterization, and Application.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- Characterizing white matter connectome abnormalities in patients with temporal lobe epilepsy using threshold-free network-based statistics.Brain and behavior · 2024Article
Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The description of brain networks as graphs where nodes represent different brain regions and edges represent a measure of connectivity between a pair of nodes is an increasingly used approach in neuroimaging research. The development of powerful methods for edge-wise group-level statistical inference in brain graphs while controlling for multiple-testing associated false-positive rates, however, remains a difficult task. In this study, we use simulated data to assess the properties of threshold-free network-based statistics (TFNBS). The TFNBS combines threshold-free cluster enhancement, a method commonly used in voxel-wise statistical inference, and network-based statistic (NBS), which is frequently used for statistical analysis of brain graphs. Unlike the NBS, TFNBS generates edge-wise significance values and does not require the a priori definition of a hard cluster-defining threshold. Other test parameters, nonetheless, need to be set. We show that it is possible to find parameters that make TFNBS sensitive to strong and topologically clustered effects, while appropriately controlling false-positive rates. Our results show that the TFNBS is an adequate technique for the statistical assessment of brain graphs.
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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.