Sense and timing: Localizing objects during emotional distraction.
Bibliographic record
Abstract
There is substantial evidence demonstrating that emotional information influences perception. Yet across studies, findings of how it does so have been highly inconsistent. In particular, emotional context (task-unrelated emotional information in the environment) has a variable influence on spatial perceptual accuracy, sometimes improving and sometimes impairing the ability to localize objects. Here, we tested the hypothesis that the heterogenous nature of emotional influences on target localization is influenced by the specific combination of sensory modalities used in the task. In the present series of experiments, we used a cross-modal localization task to identify how emotional context influences the accuracy of spatial perception. By presenting nonemotional target stimuli alongside emotional nonspatial distractor items (facial expressions or vocalizations), we were able to systematically investigate how emotional stimuli presented to individual sensory modalities acted to modulate spatial perception at distinct stages of perception and action. In three separate experiments, distractor items were presented prior to or during target presentation or after presentation during the localization response. Intramodal emotional distractors influenced localization accuracy when they overlapped in timing with targets, and the direction of this effect was both modality and valence specific (Experiment I). Additionally, targeted contrasts revealed that auditory but not visual emotional distractors influenced localization of visual targets when presented during the behavioral response, with negative cues improving localization accuracy compared to neutral or positive cues (Experiment II). We suggest such effects reflect distinct patterns of unimodal versus multimodal processing in brain regions involved in early versus late stages of perceptual processing. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
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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 | 0.001 |
| 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".