Widespread associations between trait conscientiousness and thickness of brain cortical regions
Bibliographic record
Abstract
The neural correlates of human personality have been of longstanding interest; however, most studies in the field have relied on modest sample sizes and few replicable results have been reported to date. We investigated relationships between personality and brain gray matter in a sample of generally healthy, older (mean age 73 years) adults from Scotland drawn from the Lothian Birth Cohort 1936. Participants (N = 578) completed a brain MRI scan and self-reported Big Five personality trait measures. Conscientiousness trait scores were positively related to brain cortical thickness in a range of regions, including bilateral parahippocampal gyrus, bilateral fusiform gyrus, left cingulate gyrus, right medial orbitofrontal cortex, and left dorsomedial prefrontal cortex. These associations - most notably in frontal regions - were modestly-to-moderately attenuated by the inclusion of biomarker variables assessing allostatic load and smoking status. None of the other personality traits showed robust associations with brain cortical thickness, nor did we observe any personality trait associations with cortical surface area and gray matter volume. These findings indicate that brain cortical thickness is associated with conscientiousness, perhaps partly accounted for by allostatic load and smoking status.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".