A longitudinal study of the relationship between personality traits and the annual rate of volume changes in regional gray matter in healthy adults
Bibliographic record
Abstract
To investigate whether personality traits affect the rate of decline of gray matter volume, we analyzed the relationships between personality traits and the annual rate of changes of gray matter volume in 274 healthy community dwelling subjects with a large age range by applying a longitudinal design over 6 years, using brain magnetic resonance images (MRI) and the Revised NEO Personality Inventory (NEO-PI-R) at baseline. Brain MRI data were processed using voxel-based morphometry with a custom template by applying the DARTEL diffeomorphic registration tool. For each subject, we used NEO-PI-R to evaluate the five major personality traits, including neuroticism, extraversion, openness, agreeableness, and conscientiousness. The results show that the annual rate of change in regional gray matter volume in the right inferior parietal lobule was correlated significantly and negatively with a personality of openness, which is known to be related to intellect, intellectual curiosity, and creativity adjusting for age, gender, and intracranial volume. This result indicates that subjects with a personality trait of less openness have an accelerated loss of gray matter volume in the right inferior parietal lobule, compared with subjects with a personality trait of more openness. Because the right inferior parietal lobule is involved in higher cognitive function such as working memory and creativity, a personality trait of openness is thought to be important for preserving gray matter volume and cognitive function of the right inferior parietal lobule in healthy adults.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".