ArticlePLoS computational biology2016
Quantifying Differences and Similarities in Whole-Brain White Matter Architecture Using Local Connectome Fingerprints.
Article in PLoS computational biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 85 papers.
What it found
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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.
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Who cites it
85 citing papers in PubMed.
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- Trial
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- Machine-Learning-Based Survival Prediction in Glioblastoma Using Graph-Theoretical Analysis of Structural Network Alterations.Cancers · 2026Article
- Global white matter microstructure changes induced by repetitive transcranial magnetic stimulation in cocaine use disorder: a longitudinal correlational tractography study.Brain imaging and behavior · 2026Article
- Separable, symptom specific alterations in brain microstructure associated with early-stage Parkinson's disease.Frontiers in neuroscience · 2026Article
- Diffusion connectometry reveals white matter substrates of individual differences in loss aversion.Scientific reports · 2025Article
- Multimodal brain structural and functional analysis in systemic lupus erythematosus patients without overt neuropsychiatric manifestations: associations with disease duration, organ damage, and neurocognitive function.Arthritis research & therapy · 2025Article
- White matter microstructural changes across the menstrual cycle: a differential tractography study.Neuroradiology · 2025Article
- Alterations in microarchitecture and network integrity in diffusion tensor images of children with marginal intelligence or intellectual disabilities.Neuroradiology · 2025Article
- FUS Mislocalization Rewires a Cortical Gene Network to Drive Cognitive and Behavioral Impairment in ALS.medRxiv : the preprint server for health sciences · 2025Article
- Revealing morphological fingerprints in perinatal brains using quasi-conformal mapping: occurrence and neurodevelopmental implications.Brain imaging and behavior · 2025Article
- Neural pathways underlying the production of pitch and rhythm in aphasia.Annals of the New York Academy of Sciences · 2025Article
- The scientific value of tractography: accuracy vs usefulness.Brain structure & function · 2025Article
- Article
- Enhancing Neuroanatomy Teaching with DSI Studio's Fiber Reconstruction Technology.Advances in medical education and practice · 2025Article
- Subcortical Alterations in Newly Diagnosed Epilepsy and Associated Changes in Brain Connectivity and Cognition.Human brain mapping · 2024Review
- Identifying novel data-driven subgroups in congenital heart disease using multi-modal measures of brain structure.NeuroImage · 2024Article
25 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
Quantifying differences or similarities in connectomes has been a challenge due to the immense complexity of global brain networks. Here we introduce a noninvasive method that uses diffusion MRI to characterize whole-brain white matter architecture as a single local connectome fingerprint that allows for a direct comparison between structural connectomes. In four independently acquired data sets with repeated scans (total N = 213), we show that the local connectome fingerprint is highly specific to an individual, allowing for an accurate self-versus-others classification that achieved 100% accuracy across 17,398 identification tests. The estimated classification error was approximately one thousand times smaller than fingerprints derived from diffusivity-based measures or region-to-region connectivity patterns for repeat scans acquired within 3 months. The local connectome fingerprint also revealed neuroplasticity within an individual reflected as a decreasing trend in self-similarity across time, whereas this change was not observed in the diffusivity measures. Moreover, the local connectome fingerprint can be used as a phenotypic marker, revealing 12.51% similarity between monozygotic twins, 5.14% between dizygotic twins, and 4.51% between none-twin siblings, relative to differences between unrelated subjects. This novel approach opens a new door for probing the influence of pathological, genetic, social, or environmental factors on the unique configuration of the human connectome.
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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.