Role of Amygdala Connectivity in the Persistence of Emotional Memories Over Time: An Event-Related fMRI Investigation
Bibliographic record
Abstract
According to the consolidation hypothesis, enhanced memory for emotional information reflects the modulatory effect of the amygdala on the medial temporal lobe (MTL) memory system during consolidation. Although there is evidence that amygdala-MTL connectivity enhances memory for emotional stimuli, it remains unclear whether this enhancement increases over time, as consolidation processes unfold. To investigate this, we used functional magnetic resonance imaging to measure encoding activity predicting memory for emotionally negative and neutral pictures after short (20-min) versus long (1-week) delays. Memory measures distinguished between vivid remembering (recollection) and feelings of knowing (familiarity). Consistent with the consolidation hypothesis, the persistence of recollection over time (long divided by short) was greater for emotional than neutral pictures. Activity in the amygdala predicted subsequent memory to a greater extent for emotional than neutral pictures. Although this advantage did not vary with delay, the contribution of amygdala-MTL connectivity to subsequent memory for emotional items increased over time. Moreover, both this increase in connectivity and amygdala activity itself were correlated with individual differences in recollection persistence for emotional but not neutral pictures. These results suggest that the amygdala and its connectivity with the MTL are critical to sustaining emotional memories over time, consistent with the consolidation hypothesis.
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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".