Need fulfillment and the modulation of medial prefrontal activity when judging remembered past, perceived present, and imagined future identities
Bibliographic record
Abstract
People’s abilities to integrate temporally distant identities are known to be facilitated by the fulfillment of basic psychological needs. However, the neural systems that support the integrative functions of need fulfillment are not well understood. Neuroimaging studies indicate that the medial prefrontal cortex (MPFC) differentiates remembered past, perceived present, and imagined future identities, possibly on the basis of the self-relevance attributed to specific identity representations. Using optical neuroimaging, we examined the relationship between need fulfillment and activity within the MPFC when young adults (N = 110) made trait judgments about their past, present, and future identities. Participants reporting higher need fulfillment evidenced similarly high levels of activity in the right-MPFC across the conditions; in contrast, those reporting lower need fulfillment evidenced markedly reduced activity when judging past and future identities. Results thus suggest that, among people who experience higher need fulfillment, the MPFC processes temporally distant identities in a similarly self-relevant manner. These findings provide a new type of evidence of the relationship between need fulfillment and identity integration and provide future studies with a point of entry for further examining the neural basis of identity integration.
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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".