Effects of emotion and emotional ambiguity on early visual event-related potentials.
Bibliographic record
Abstract
The modulation of early sensory event-related potentials such as the P1, N1, and N170 by emotion and emotional ambiguity is still controversial. Some studies have found a modulation of one or all of these components by one or both of these factors, whereas others have failed to show such results. The objective of this study was to investigate the effects of emotion and ambiguity on the behavioral and electrophysiological responses to a morphed emotion recognition task. Thirty-seven healthy participants (19 men) completed an emotion recognition task where photographs of a male face expressing the six basic emotions morphed with another emotion (in a proportion ranging from 26% to 74%) were randomly presented while electroencephalography was recorded. After each face presentation, participants were asked to identify the facial emotion. We found an emotional effect on the P1, N1, and N170, with greater amplitudes for some emotional facial expressions than for others. However, we found no significant emotional ambiguity effect or interaction between emotion and ambiguity for any of these components. These findings suggest that computation of emotional facial expressions (regardless of their ambiguity) occurs from the early stages of brain processing. (PsycInfo Database Record (c) 2023 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 | 0.001 | 0.008 |
| 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) | 0.003 | 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".