A face to remember : an fMRI study of the effects of emotional expression on recognition memory
Bibliographic record
Abstract
Emotion can exert a modulatory role on declarative memory. Several studies have shown that emotional stimuli (e.g., words, pictures) are better remembered than neutral ones. Although facial expressions are powerful emotional stimuli and have been shown to influence perception and attention processes, little is known about their effect on memory. We conducted an event-related fMRI study in 18 healthy individuals (9 men) to investigate the effects of expression on recognition memory for faces. During the encoding phase, participants viewed 84 faces of different individuals, depicting happy, fearful or neutral expressions. Subjects were asked to perform a gender discrimination task and remember the faces for later. In the recognition part subjects performed an old/new decision task on 168 faces (84 new). Both runs were scanned. Our findings highlight the importance of the amygdala, hippocampus and prefrontal cortex on the formation and retrieval of memories with emotional content.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".