Do emotionally negative events impair working memory as a result of intrusive thoughts?
Bibliographic record
Abstract
Individuals exposed to highly stressful negative events show alterations in working memory (WM) function. The correlational nature of these studies makes it impossible to determine whether exposure to negative events itself decreases WM. Such events elicit intrusive thoughts which may cause interference in WM. The main objective of this study was to verify the causal impact of a recent negative event on WM, and to examine the role of intrusive thoughts. One hundred and twenty participants completed a WM task (n-Back). Then, 90 of these participants watched an emotionally negative video and 30 watched a neutral video. The emotional impact of the video was assessed, and the frequency of intrusive thoughts were measured. WM was measured a second time (n-Back) while recording EEG (P300). Contrary to our hypothesis, the negative video did not impair behavioural WM performance compared to the neutral video. However, it disrupted WM neurocognitive processes (lower P300 amplitude) under low WM load. In the high load condition, greater emotional reaction was linked to poorer accuracy and more intrusive thoughts, which in turn slowed response times. Our results suggest that the impact of negative emotions on WM depends on both individual sensitivity and cognitive load.
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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 | 0.002 |
| 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".