ArticleHuman brain mapping2017
Structural brain connectivity and cognitive ability differences: A multivariate distance matrix regression analysis.
Article in Human brain mapping, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Distinct neural substrates of obsessions and compulsions in adolescent obsessive compulsive disorder.Translational psychiatry · 2026Article
- Long-acting naltrexone restores network connectivity in subjects with co-morbid cannabis and opioid use disorder.bioRxiv : the preprint server for biology · 2025Article
- Manatee cognition and behavior: a neurobiological perspective on an unusual constellation of senses and a unique brain.Frontiers in behavioral neuroscience · 2025Article
- The interplay between polygenic score for tumor necrosis factor-α, brain structural connectivity, and processing speed in major depression.Molecular psychiatry · 2024Article
- The significance of structural rich club hubs for the processing of hierarchical stimuli.Human brain mapping · 2024Article
- Inferring neurocognition using artificial intelligence on brain MRIs.Frontiers in neuroimaging · 2024Review
- Article
- Computer Programming E-Learners' Personality Traits, Self-Reported Cognitive Abilities, and Learning Motivating Factors.Brain sciences · 2021Article
- Geodesic Distance on Optimally Regularized Functional Connectomes Uncovers Individual Fingerprints.Brain connectivity · 2021Article
- Typicality of functional connectivity robustly captures motion artifacts in rs-fMRI across datasets, atlases, and preprocessing pipelines.Human brain mapping · 2020Article
- Comparing functional connectivity matrices: A geometry-aware approach applied to participant identification.NeuroImage · 2020Article
- Graph Matching Based Connectomic Biomarker with Learning for Brain Disorders.Uncertainty for safe utilization of machine learning in medical imaging, and graphs in biomedical image analysis : Second International Workshop, UNSURE 2020, and Third International Workshop, GRAIL 2020, Held in Conjunction with MICCAI... · 2020Article
- Effective Diagnosis of Alzheimer's DiseaseFrontiers in genetics · 2019Article
- Topological Modification of Brain Networks Organization in Children With High Intelligence Quotient: A Resting-State fMRI Study.Frontiers in human neuroscience · 2019Article
- Subject specificity of the correlation between large-scale structural and functional connectivity.Network neuroscience (Cambridge, Mass.) · 2019Article
- Unique Mapping of Structural and Functional Connectivity on Cognition.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2018Article
- The structural connectome in children: basic concepts, how to build it, and synopsis of challenges for the developing pediatric brain.Neuroradiology · 2017Review
- Abnormalities in the default mode network in late-life depression: A study of resting-state fMRI.International journal of clinical and health psychology : IJCHPArticle
- Linking Brain Biology to Intellectual Endowment: A Review on the Associations of Human Intelligence With Neuroimaging Data.Basic and clinical neuroscienceReview
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Neuroimaging research involves analyses of huge amounts of biological data that might or might not be related with cognition. This relationship is usually approached using univariate methods, and, therefore, correction methods are mandatory for reducing false positives. Nevertheless, the probability of false negatives is also increased. Multivariate frameworks have been proposed for helping to alleviate this balance. Here we apply multivariate distance matrix regression for the simultaneous analysis of biological and cognitive data, namely, structural connections among 82 brain regions and several latent factors estimating cognitive performance. We tested whether cognitive differences predict distances among individuals regarding their connectivity pattern. Beginning with 3,321 connections among regions, the 36 edges better predicted by the individuals' cognitive scores were selected. Cognitive scores were related to connectivity distances in both the full (3,321) and reduced (36) connectivity patterns. The selected edges connect regions distributed across the entire brain and the network defined by these edges supports high-order cognitive processes such as (a) (fluid) executive control, (b) (crystallized) recognition, learning, and language processing, and (c) visuospatial processing. This multivariate study suggests that one widespread, but limited number, of regions in the human brain, supports high-level cognitive ability differences. Hum Brain Mapp 38:803-816, 2017. © 2016 Wiley Periodicals, Inc.
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