ArticlePersonality neuroscience2018
Resting-state functional brain connectivity best predicts the personality dimension of openness to experience.
Article in Personality neuroscience, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 87 papers.
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Who cites it
87 citing papers in PubMed, 184 citations in OpenAlex.
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- Trait-Relevant Tasks Improve Personality Prediction From Structural-Functional Brain Network Coupling.Human brain mapping · 2026Article
- Predicting individual differences of fear and cognitive learning and extinction.Nature communications · 2026Article
- Anxiety facilitates disengagement when switching from negative-valenced stimuli: Mediating role of attentional control.Cognitive, affective & behavioral neuroscience · 2026Article
- Replication challenges in linking personality to resting-state functional connectomics.Frontiers in computational neuroscience · 2026Article
- Deviation From Typical Brain Activity During Naturalistic Stimulation Is Related to Personality Traits.Psychophysiology · 2025Article
- Multimodal neuroimaging data boosts the prediction of multifaceted cognition.Research square · 2025Article
- Using Simulations to Explore Sampling Distributions: An Antidote to Hasty and Extravagant Inferences.eNeuro · 2025Article
- Trait-Relevant Tasks Improve Personality Prediction from Structural-Functional Brain Network Coupling.bioRxiv : the preprint server for biology · 2025Article
- Prediction of alcohol intake patterns with olfactory and gustatory brain connectivity networks.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2025Article
- Transforming 3D MRI to 2D Feature Maps Using Pre-Trained Models for Diagnosis of Attention Deficit Hyperactivity Disorder.Tomography (Ann Arbor, Mich.) · 2025Article
- Weak and unstable prediction of personality from the structural connectome.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Sophisticated perspective-takers are distinctive: Neural idiosyncrasy of functional connectivity in the mentalizing network.iScience · 2024Article
- How measurement noise limits the accuracy of brain-behaviour predictions.Nature communications · 2024Article
- Empathy enhances decoding accuracy of human neurophysiological responses to emotional facial expressions of humans and dogs.Social cognitive and affective neuroscience · 2024Article
- Connectome-based fingerprinting: reproducibility, precision, and behavioral prediction.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2024Review
- A cortical surface template for human neuroscience.Nature methods · 2024Article
- Network and state specificity in connectivity-based predictions of individual behavior.Human brain mapping · 2024Article
27 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 3 countries.
Funding
Abstract
Personality neuroscience aims to find associations between brain measures and personality traits. Findings to date have been severely limited by a number of factors, including small sample size and omission of out-of-sample prediction. We capitalized on the recent availability of a large database, together with the emergence of specific criteria for best practices in neuroimaging studies of individual differences. We analyzed resting-state functional magnetic resonance imaging data from 884 young healthy adults in the Human Connectome Project (HCP) database. We attempted to predict personality traits from the "Big Five", as assessed with the NEO-FFI test, using individual functional connectivity matrices. After regressing out potential confounds (such as age, sex, handedness and fluid intelligence), we used a cross-validated framework, together with test-retest replication (across two sessions of resting-state fMRI for each subject), to quantify how well the neuroimaging data could predict each of the five personality factors. We tested three different (published) denoising strategies for the fMRI data, two inter-subject alignment and brain parcellation schemes, and three different linear models for prediction. As measurement noise is known to moderate statistical relationships, we performed final prediction analyses using average connectivity across both imaging sessions (1 h of data), with the analysis pipeline that yielded the highest predictability overall. Across all results (test/retest; 3 denoising strategies; 2 alignment schemes; 3 models), Openness to experience emerged as the only reliably predicted personality factor. Using the full hour of resting-state data and the best pipeline, we could predict Openness to experience (NEOFAC_O: r=0.24, R
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Registered trials
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.