Neural systems for reflected and direct self-appraisals in Chinese young adults: Exploring the role of the temporal-parietal junction.
Bibliographic record
Abstract
OBJECTIVES: Although cortical midline structures (CMS) are the most commonly identified neural foundations of self-appraisals, research is beginning to implicate the temporal-parietal junction (TPJ) in more interdependent self-construals. The goal of this study was to extend this research in an understudied population by (a) examining both direct (first-person) and reflected (third-person) self-appraisals across 2 domains (social and academics), and (b) exploring individual differences in recruitment of the TPJ during reflected self-appraisals. METHOD: The neural correlates of direct and reflected self-appraisals in social and academic domains were examined in 16 Chinese young adults (8 males, 8 females; aged 18-23 years) using functional MRI. RESULTS: As expected, when making reflected self-appraisals (i.e., reporting what they believed others thought about them, regardless of domain), Chinese participants recruited both CMSs and the TPJ. Similar to previous research in East Asian and interdependent samples, CMSs and the TPJ were relatively more active during direct self-appraisals in the social than in the academic domain. We additionally found that, to the extent participants reported that reflected academic self-appraisals differed from direct academic self-appraisals, they demonstrated greater engagement of the TPJ during reflected academic self-appraisals. Exploratory cross-national comparisons with previously published data from American participants revealed that Chinese young adults engaged the TPJ relatively more during reflected self-appraisals made from peer perspectives. CONCLUSIONS: In combination with previous research, these findings increase support for a role of the TPJ in self-appraisal processes, particularly when Chinese young adults consider peer perspectives. The possible functional contributions provided by the TPJ are explored and discussed. (PsycINFO Database Record
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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".