ArticleHuman brain mapping2021
Prediction of trust propensity from intrinsic brain morphology and functional connectome.
Article in Human brain mapping, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Propensity to trust in Large Language Models.PloS one · 2026Article
- An integrated approach of feature selection and machine learning for early detection of breast cancer.Scientific reports · 2025Article
- Neurocomputational Substrates Underlying the Effect of Identifiability on Third-Party Punishment.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2023Article
- The connectome-based prediction of trust propensity in older adults: A resting-state functional magnetic resonance imaging study.Human brain mapping · 2023Article
- Multivariate resting-state functional connectomes predict and characterize obesity phenotypes.Cerebral cortex (New York, N.Y. : 1991) · 2023Article
- Classify patients with Moyamoya disease according to their cognitive performance might be helpful in clinical and practical with support vector machine based on hypergraph.Human brain mapping · 2023Article
- Self-attention random forest for breast cancer image classification.Frontiers in oncology · 2023Article
- Trust toward humans and trust toward artificial intelligence are not associated: Initial insights from self-report and neurostructural brain imaging.Personality neuroscience · 2023Article
- Intrinsic brain activity patterns across large-scale networks predict reciprocity propensity.Human brain mapping · 2022Article
- Neural implementation of computational mechanisms underlying the continuous trade-off between cooperation and competition.Nature communications · 2022Article
- Interpreting Brain Biomarkers: Challenges and solutions in interpreting machine learning-based predictive neuroimaging.IEEE signal processing magazine · 2022Article
- Multivariate morphological brain signatures enable individualized prediction of dispositional need for closure.Brain imaging and behavior · 2022Article
- Intrinsic functional connectivity of the frontoparietal network predicts inter-individual differences in the propensity for costly third-party punishment.Cognitive, affective & behavioral neuroscience · 2021Article
- Ant colony optimization with Cauchy and greedy Levy mutations for multilevel COVID 19 X-ray image segmentation.Computers in biology and medicine · 2021Article
- Evolutionary warning system for COVID-19 severity: Colony predation algorithm enhanced extreme learning machine.Computers in biology and medicine · 2021Article
- Prediction of trust propensity from intrinsic brain morphology and functional connectome.Human brain mapping · 2021Article
- Trust transfer in digital healthcare: The role of self-service systems in reducing patient treatment barriers.Digital healthArticle
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Trust forms the basis of virtually all interpersonal relationships. Although significant individual differences characterize trust, the driving neuropsychological signatures behind its heterogeneity remain obscure. Here, we applied a prediction framework in two independent samples of healthy participants to examine the relationship between trust propensity and multimodal brain measures. Our multivariate prediction analyses revealed that trust propensity was predicted by gray matter volume and node strength across multiple regions. The gray matter volume of identified regions further enabled the classification of individuals from an independent sample with the propensity to trust or distrust. Our modular and functional decoding analyses showed that the contributing regions were part of three large-scale networks implicated in calculus-based trust strategy, cost-benefit calculation, and trustworthiness inference. These findings do not only deepen our neuropsychological understanding of individual differences in trust propensity, but also provide potential biomarkers in predicting trust impairment in neuropsychiatric disorders.
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