Social interaction alters neural representations of self-identity: Evidence of possible neural precursors to social learning
Bibliographic record
Abstract
Social interaction requires enough social flexibility to accommodate an interlocutor’s perspective. Our previous research demonstrated that suppression of self-identity may be necessary during a social interaction with a friendly stranger if they have different social values. The present study examines neurobiological mechanisms responsible for suppressing self-identity and entertaining the stranger’s perspective. This study takes a semi-naturalistic neuroscience approach. Eighteen participants underwent an fMRI scan immediately after having a social interaction with a stranger. We hypothesized that pairing of activation in the inferior frontal gyrus (IFG) and dorsomedial prefrontal cortex (dmPFC) because they reflect activation of self-regulation and changes in self-identity. Brain activity in the IFG and dmPFC emerged, supporting our hypothesis and previous behavioral findings, and the precuneus played a key role. Evidence of social learning also emerged, which demonstrated that neural changes may occur before behavioral changes do. These findings suggest that social interaction influences self-identity on a neurobiological level and that neurobehavioral suppression of the social self may be a precursor to social learning. This study is the first to directly compare neural activation associated with active and stable self-concepts in an fMRI scanner after a social interaction. Findings will act as a foundation for future fully-naturalistic neuroscience studies to base hypotheses upon.
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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".