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Updated: Feb 15, 2026

Cerebral Blood Flow-Based Resting State Functional Connectivity of the Human Brain using Optical Diffuse Correlation Spectroscopy
Published on: May 27, 2020
Resting-state functional connectivity predicts neuroticism and extraversion in novel individuals
Wei-Ting Hsu1, Monica D Rosenberg1, Dustin Scheinost2
1Department of Psychology, Yale University, New Haven, CT 06520, USA.
Resting-state functional connectivity patterns can predict personality traits like neuroticism and extraversion. This brain imaging study shows how brain activity during rest reveals individual differences in personality.
Area of Science:
- Neuroscience
- Psychology
- Brain Imaging
Background:
- Neuroticism and extraversion are linked to emotional experiences and affective disorders.
- Previous research identified functional magnetic resonance imaging (fMRI) activity correlates of these personality traits.
- No prior studies have utilized brain-based measures to predict these personality dimensions.
Purpose of the Study:
- To predict individual levels of neuroticism and extraversion using resting-state functional connectivity (FC) data.
- To investigate if brain activity patterns during rest can serve as biomarkers for personality traits.
- To identify specific brain networks associated with neuroticism and extraversion.
Main Methods:
- Applied connectome-based predictive modeling (CPM), a data-driven technique, to resting-state fMRI data.
- Utilized FC matrices derived from 114 participants' brain activity during rest.
- Correlated functional connections with self-reported neuroticism and extraversion scores (NEO Five Factor Inventory).
Main Results:
- CPM successfully predicted neuroticism and extraversion scores in novel individuals with high accuracy.
- Identified specific functional brain networks correlated with these personality traits.
- Revealed predictive networks with anatomical patterns aligning with previous research and suggesting new brain regions of interest.
Conclusions:
- Resting-state functional connectivity patterns contain predictive information about trait-level personality.
- Brain-based measures, specifically FC during rest, can predict individual differences in neuroticism and extraversion.
- This approach offers a novel way to understand the neural underpinnings of personality.
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