Fear not! Anxiety biases attentional enhancement of threat without impairing working memory filtering
Bibliographic record
Abstract
Individuals with anxiety have attentional biases toward threat-related distractors. This deficit in attentional control has been shown to impact visual working memory (VWM) filtering efficiency, as anxious individuals inappropriately store threatening distractors in VWM. It remains unclear, however, whether this mis-allocation of memory resources is due to inappropriate attentional enhancement of threatening distractors, or to a failure in suppression. Here, we used a systematically lateralized VWM task with fearful and neutral faces to examine event-related potentials related to attentional selection (N2pc), suppression (PD), and working memory maintenance (CDA). We found that state anxiety correlated with attentional enhancement of threat-related distractors, such that more anxious individuals had larger N2pc amplitudes toward fearful distractors than neutral distractors. However, there was no correlation between anxiety and memory storage of fearful distractors (CDA). These findings demonstrate that anxiety biases attention toward fearful distractors, but that this bias does not always guarantee increased memory storage of threat-related distractors.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".