How spontaneous brain activity and narcissistic features shape social interaction
Bibliographic record
Abstract
There is an increasing interest in how ongoing spontaneous brain activity and personality provide a predisposition for the processing of environmental demands. It further has been suggested that the brain has an inherent sensitivity to the social environment. Here we tested in healthy volunteers if spontaneous brain activity contributes to a predisposition for social behavior and how this is modulated by narcissistic personality features associated with poor interpersonal functioning. Functional magnetic resonance imaging included a resting state and an experimental paradigm focusing on the anticipation of actively touching an animate (human hand) versus an inanimate target (mannequin hand). The experimental task induced a significant modulation of neural activity in left postcentral gyrus (PostCG), right culmen and, co-varying with narcissistic features, in right anterior insula (AI). Neural activity in anticipation of the animate target significantly correlated with spontaneous activity during the resting state indexed by the Power Law Exponent (PLE) in PostCG and AI. Finally, the correlation between spontaneous and task-induced activity in AI was mediated by narcissistic features. These findings provide novel evidence for a relationship between intrinsic brain activity and social behavior and show how personality could contribute to individual differences in our predisposition to approach the animate world.
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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".