Neural Correlates of Opposing Effects of Emotional Distraction on Working Memory and Episodic Memory: An Event-Related fMRI Investigation
Bibliographic record
Abstract
A fundamental question in the emotional memory literature is why emotion enhances memory in some conditions but disrupts memory in other conditions. For example, separate studies have shown that emotional stimuli tend to be better remembered in long-term episodic memory (EM), whereas emotional distracters tend to impair working memory (WM) maintenance. The first goal of this study was to directly compare the neural correlates of EM enhancement (EME) and WM impairing (WMI) effects, and the second goal was to explore individual differences in these mechanisms. During event-related functional magnetic resonance imaging (fMRI), participants maintained faces in WM while being distracted by emotional or neutral pictures presented during the delay period. EM for the distracting pictures was tested after scanning and was used to identify successful encoding activity for the picture distracters. The first goal yielded two findings: (1) emotional pictures that disrupted face WM but enhanced subsequent EM were associated with increased amygdala (AMY) and hippocampal activity (ventral system) coupled with reduced dorsolateral PFC (dlPFC) activity (dorsal system); (2) trials in which emotion enhanced EM without disrupting WM were associated with increased ventrolateral PFC activity. The ventral-dorsal switch can explain EME and WMI, while the ventrolateral PFC effect suggests a coping mechanism. The second goal yielded two additional findings: (3) participants who were more susceptible to WMI showed greater amygdala increases and PFC reductions; (4) AMY activity increased and dlPFC activity decreased with measures of attentional impulsivity. Taken together, these results clarify the mechanisms linking the enhancing and impairing effects of emotion on memory, and provide insights into the role of individual differences in the impact of emotional distraction.
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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".