Exploring the consistency of the affective consequences of cognitive-control for visual stimuli across tasks and individuals.
Bibliographic record
Abstract
Mechanisms of visual selective attention and motor-response control have affective consequences for associated stimuli. For example, images that are ignored or from which a response is withheld subsequently receive more negative affective ratings than the targets of attention/response. Although such effects have been observed in a variety of cognitive-behavioural paradigms (e.g., visual search, visual-memory search, Go/No-go, Think/No-Think, task-switching), leading accounts posit that the difference in stimulus ratings across experimental conditions is due to the effects of just one or two mechanisms that operate to either enhance or suppress visual stimulus/response representations (and thereby enhance or depress affective ratings) in each of these tasks. This suggests that there should be a reliable correspondence in the difference between ratings of stimuli from conditions involving active attending/responding and those involving ignoring/response-avoidance across alternate visual tasks. To test this, we asked participants to complete in a single session the two different tasks most commonly used to assess the affective consequences of cognitive control—visual search and Go/No-go. Visual ‘monster’ cartoons that were ignored (search distractors) or from which a response had been withheld (No-go items) were rated more negatively than those that were the focus of attention (search targets) or response (Go-items). And there was a significant (albeit modest) correlation between the magnitude of the target vs. distractor rating difference and the Go vs. No-go rating difference obtained in the different tasks. Our investigation also examined the extent to which these visually-evoked affective responses are linked to common cognitive-control mechanisms or other distinct factors by including a series of cognitive and affective individual-difference measures. Taken together, our results are consistent with the view that affective ratings of visual stimuli are determined primarily by the influences of one or two cognitive-control mechanisms that remain consistent across task-types, but may also be influenced by additional cognitive and affective factors that may be unique to specific tasks.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".