Neural responses to shared positive and negative experiences: unveiling the social feedback processing dynamics
Bibliographic record
Abstract
This study examined the impacts of shared experience valence on the dynamic processing of social feedback. Electroencephalography (EEG) was recorded when participants performed an adapted social judgment paradigm with three stages: social feedback expectation, social feedback evaluation, and expectation updating. Behavioral analysis revealed higher acceptance expectation and lower rejection expectation in the shared positive experience (SPE) condition than in the shared negative experience (SNE) condition; receiving acceptance feedback increased acceptance expectation in the subsequent trial. EEG results revealed that at the social feedback expectation stage, rejection evoked a larger stimulus-preceding negativity magnitude than acceptance in the SNE but not SPE condition. At the social feedback evaluation stage, rejection feedback evoked a smaller early frontal theta than acceptance feedback in the SNE but not SPE condition; unexpected acceptance evoked a larger P300 than unexpected rejection in the SPE but not SNE condition. At the expectation updating stage, unexpected acceptance elicited larger late posterior theta than expected acceptance in the SNE but not SPE condition. These results suggest that shared positive experiences reduce vigilance toward impending rejection and increase sensitivity to pleasantness, whereas shared negative experiences blunt reactivity to rejection feedback and foster social learning from unexpected acceptance to enhance positive expectation.
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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".