The influence of indirect and direct emotional processing on memory for facial expressions
Bibliographic record
Abstract
We used the remember-know procedure (Tulving, 1985 ) to test the behavioural expression of memory following indirect and direct forms of emotional processing at encoding. Participants (N=32) viewed a series of facial expressions (happy, fearful, angry, and neutral) while performing tasks involving either indirect (gender discrimination) or direct (emotion discrimination) emotion processing. After a delay, participants completed a surprise recognition memory test. Our results revealed that indirect encoding of emotion produced enhanced memory for fearful faces whereas direct encoding of emotion produced enhanced memory for angry faces. In contrast, happy faces were better remembered than neutral faces after both indirect and direct encoding tasks. These findings suggest that fearful and angry faces benefit from a recollective advantage when they are encoded in a way that is consistent with the predictive nature of their threat. We propose that the broad memory advantage for happy faces may reflect a form of cognitive flexibility that is specific to positive emotions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".