ArticleImaging neuroscience (Cambridge, Mass.)2025
Weak and unstable prediction of personality from the structural connectome.
Article in Imaging neuroscience (Cambridge, Mass.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Structural Connectivity of Functionally Defined Episodic Memory Networks: A Large-Scale Connectome-Behavior Study.Brain and behavior · 2026Article
- Trait-Relevant Tasks Improve Personality Prediction From Structural-Functional Brain Network Coupling.Human brain mapping · 2026Article
- White Matter Bundle Reconstruction From Single-Shell Diffusion Magnetic Resonance Imaging: Test-Retest Reliability and Predictive Capability Across Orientation Distribution Function Reconstruction Methods.Human brain mapping · 2025Article
- Multimodal neuroimaging data boosts the prediction of multifaceted cognition.Research square · 2025Article
- Effective workflow from multimodal MRI data to model-based prediction.Scientific reports · 2025Article
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7 authors.
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Abstract
Personality neuroscience aims to discover links between personality traits and features of the brain. Previous neuroimaging studies have investigated the connection between the brain structure, microstructural properties of brain tissue, or the functional connectivity (FC) and these personality traits. Analyses relating personality to diffusion-weighted MRI measures were limited to investigating the voxel-wise or tract-wise association of microstructural properties with trait scores. The main goal of our study was to determine whether there is an individual predictive relationship between the structural connectome (SC) and the big five personality traits. To that end, we expanded past work in two ways: First, by focusing on the entire structural connectome (SC) instead of separate voxels and tracts; and second, by predicting personality trait scores instead of performing a statistical correlation analysis to assess an out-of-sample performance. Prediction of personality from the SC is, however, not yet as established as prediction of behavior from the FC, and sparse studies in this field so far delivered rather heterogeneous results. We, therefore, further dedicated our study to investigate whether and how different pipeline settings influence prediction performance. In a sample of 426 unrelated subjects with high-quality MRI acquisitions from the Human Connectome Project, we analyzed 19 different brain parcellations, 3 SC weightings, 3 groups of subjects, and 4 feature classes for the prediction of the 5 personality traits using a ridge regression. From the large number of evaluated pipelines, only very few lead to promising results of prediction accuracy
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