Disruption of working memory and contralateral delay activity by nociceptive stimuli is modulated by task demands
Bibliographic record
Abstract
ABSTRACT: Top-down processes allow the selection and prioritization of information by limiting attentional capture by distractors, and these mechanisms depend on task demands such as working memory (WM) load. However, bottom-up processes give salient stimuli a stronger neuronal representation and provoke attentional capture. The aim of this study was to examine the effect of salient nociceptive stimuli on WM while manipulating task demands. Twenty-one healthy participants performed a change detection task during which they had to determine whether 2 successive visual arrays were different or the same. Task demands were modulated by manipulating the WM load (set size included 2 or 4 objects to recall) and by the correspondence between the 2 successive visual arrays (change vs no change). Innocuous stimuli (control) or nociceptive stimuli (distractors) were delivered during the delay period between the 2 visual arrays. Contralateral delay activity and laser-evoked potentials were recorded to examine neural markers of visual WM and nociceptive processes. Nociceptive stimuli decreased WM performance depending on task demands (all P < 0.05). Moreover, compared with control stimuli, nociceptive stimuli abolished the increase in contralateral delay activity amplitude for set size 4 vs set size 2 (P = 0.04). Consistent with these results, laser-evoked potential amplitude was not decreased when task demands were high (P = 0.5). These findings indicate that WM may shield cognition from nociceptive stimuli, but nociceptive stimuli disrupt WM and alter task performance when cognitive resources become insufficient to process all task-relevant information.
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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) | 0.002 | 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".