Do emotionally negative events impair working memory as a result of intrusive thoughts?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 it