Personality Goes a Long a Way: An Interhemispheric Connectivity Study
Bibliographic record
Abstract
Throughout the development of psychology the delineation of personality has played a central role. Together with the NEO-PI-R, a questionnaire derived from the Five Factor Model of Personality, and recent advances in research technology it is now possible to investigate the relationship between personality features and neurophysiological brain processes. The NEO-FFI, the short version of the NEO-PI-R, reliably measures five main personality traits: Neuroticism, Extraversion, Openness to experience, Agreeableness, and Conscientiousness. As behavior and some psychiatric disorders have been related to interhemispheric connectivity, the present study used the combination of transcranial magnetic stimulation (TMS) and electroencephalography (EEG) to measure frontal interhemispheric connectivity and its association with personality as indexed by the NEO-FFI. Results demonstrated that prefrontal interhemispheric connectivity between the left and right dorsolateral prefrontal cortex correlates with Agreeableness in healthy subjects. This is the first study to relate personality features to interhemispheric connectivity through TMS-EEG and suggests that Agreeableness relates to the effectiveness of prefrontal communication between hemispheres.
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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 | 0.001 |
| 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) | 0.001 | 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".