ArticleSocial cognitive and affective neuroscience2018
Resting-state functional connectivity predicts neuroticism and extraversion in novel individuals.
Article in Social cognitive and affective neuroscience, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 104 papers, 1 of them a synthesis that pooled it.
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Who cites it
104 citing papers in PubMed, 1 synthesis or guideline pooled it, 198 citations in OpenAlex.
- Extraversion and the resting brain: a coordinate-based meta-analysis of resting-state functional brain imaging studies.Brain structure & function · 2025Pooled it
- Article
- Ongoing thoughts at rest reflect functional brain organization and behaviour.Nature human behaviour · 2026Article
- Multivariate relationships between social cognitive performance and functional connectivity during task and rest across schizophrenia spectrum disorders and healthy controls.Molecular psychiatry · 2026Article
- Feature selection leads to divergent neurobiological interpretations of brain-based machine learning biomarkers.Nature human behaviour · 2026Article
- In-scanner thoughts contribute to resting-state functional connectivity.Nature communications · 2026Article
- Trait-Relevant Tasks Improve Personality Prediction From Structural-Functional Brain Network Coupling.Human brain mapping · 2026Article
- Impulsivity and neuroticism share distinct functional connectivity signatures with alcohol-use risk in youth.Molecular psychiatry · 2026Article
- Neuroticism heterogeneity through item-level associations in resting-state functional connectivity.Communications biology · 2025Article
- Deviation From Typical Brain Activity During Naturalistic Stimulation Is Related to Personality Traits.Psychophysiology · 2025Article
- Mapping trait justice sensitivity in the Brain: Whole-brain resting-state functional connectivity as a predictor of other-oriented not self-oriented justice sensitivity.Cognitive, affective & behavioral neuroscience · 2025Article
- Overlooked features lead to divergent neurobiological interpretations of brain-based machine learning biomarkers.bioRxiv : the preprint server for biology · 2025Article
- Uncovering functional connectivity patterns predictive of cognition in youth using interpretable predictive modeling.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Trait-Relevant Tasks Improve Personality Prediction from Structural-Functional Brain Network Coupling.bioRxiv : the preprint server for biology · 2025Article
- Connectome-based predictive modeling of early and chronic psychosis symptoms.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2025Article
- Connectome-Based Predictive Modeling of PTSD Development Among Recent Trauma Survivors.JAMA network open · 2025Article
- Association between healthy neuroticism and eating behavior as revealed by the NKI Rockland Sample.Scientific reports · 2025Article
- Stimulus Selection Influences Prediction of Individual Phenotypes in Naturalistic Conditions.Human brain mapping · 2025Article
- Hypothalamic resting-state functional connectivity and self-evaluated aggression in young adults.Journal of psychiatric research · 2025Article
- Network-based mapping and neurotransmitter architecture of brain gray matter correlates of extraversion.Frontiers in systems neuroscience · 2025Article
44 more citing papers are in PubMed but not listed here.
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
The personality dimensions of neuroticism and extraversion are strongly associated with emotional experience and affective disorders. Previous studies reported functional magnetic resonance imaging (fMRI) activity correlates of these traits, but no study has used brain-based measures to predict them. Here, using a fully cross-validated approach, we predict novel individuals' neuroticism and extraversion from functional connectivity (FC) data observed as they simply rested during fMRI scanning. We applied a data-driven technique, connectome-based predictive modeling (CPM), to resting-state FC data and neuroticism and extraversion scores (self-reported NEO Five Factor Inventory) from 114 participants of the Nathan Kline Institute Rockland sample. After dividing the whole brain into 268 nodes using a predefined functional atlas, we defined each individual's FC matrix as the set of correlations between the activity timecourses of every pair of nodes. CPM identified networks consisting of functional connections correlated with neuroticism and extraversion scores, and used strength in these networks to predict a left-out individual's scores. CPM predicted neuroticism and extraversion in novel individuals, demonstrating that patterns in resting-state FC reveal trait-level measures of personality. CPM also revealed predictive networks that exhibit some anatomical patterns consistent with past studies and potential new brain areas of interest in personality.
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