Inhibition has negative affective consequences for task-irrelevant stimuli that are similar to the active contents of visual working memory
Bibliographic record
Abstract
Ignoring a visual stimulus causes it to subsequently receive more negative affective ratings than novel items or prior targets of attention. This has been taken as evidence that attentional inhibition alters the coding of stimulus-associated value to ensure that previously distracting stimuli can be effectively avoided in future encounters. Previous results have suggested that this ‘inhibitory devaluation’ effect may operate through affective associations with specific perceptual features that allow distractors to be differentiated from targets. Prior inhibition can thereby impact the affective value both of specific items that have appeared as distractors and of novel items that share a previously ignored feature. But what happens when a distractor shares the same perceptual features as a target being held in visual working memory? Recent electrophysiological evidence suggests that while the similarity may initially cause selective attention to be biased toward such task-irrelevant items, active inhibition may then be triggered to prevent them from interfering with the ongoing task. If inhibition causes affective devaluation, then such findings predict greater devaluation of task-irrelevant stimuli that share the same perceptual features as a target being held in visual working memory than those that do not. To test this, we utilized delayed-match-to-sample trials that required participants to maintain a uniquely-coloured stimulus in working memory while task-irrelevant probe arrays were presented. The probe arrays contained abstract shapes whose colour either matched or did not match that of the stimulus being held in memory. Subsequent affective-evaluation trials revealed that prior memory-matching distractors received more negative ratings than non-matching distractors or a set of previously-unseen shapes. These results converge with prior electrophysiological evidence to suggest that distractors matching the contents of visual working memory are subjected to greater levels of attentional inhibition than other task-irrelevant stimuli, and that the consequences of this inhibition include alterations in affective value. Meeting abstract presented at VSS 2015
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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 | 0.003 |
| 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 | 0.001 |
| 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".