Do Emotional Faces Affect Inhibition of Return? An ERP Study
Bibliographic record
Abstract
Inhibition of Return (IOR) refers to an individual's slowed localization or discrimination performance for targets that appear in previously cued versus uncued location after a relatively long delay after cue (∼300-500 ms). The current study adopted a cue-target paradigm and used behavioral and event-related potential (ERP) measures to investigate whether IOR would be modulated by emotional faces during an emotion recognition task. For reaction time measure, we found IOR effect and the magnitude of IOR effect were comparable for fearful face target and neutral face target. For ERP measures, valid cues were associated with smaller P1 and larger N1 waveform than that for invalid cues. Fearful faces were associated with a larger N170 than neutral faces. The onset latency of the stimulus-locked lateralised readiness potential (LRP) in the valid cue condition was longer than that in the invalid cue condition, while there was no significant difference on the onset latency of the response-locked LRP between the valid cue and invalid cue condition. These results support the notion that, regardless the emotion component of the stimulus, the inhibitory bias of attention to previous visited location before response contributes to the IOR.
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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".