Do You See What Eye See: The Effect of Psychopathic Traits on Memory and Attention to Emotional Images
Bibliographic record
Abstract
Numerous studies have found a central/peripheral trade-off in memory for negative stimuli.This pattern has been supported by eye-tracking studies showing that participants fixate more often on central rather than peripheral details.Only one study to date has examined this in relation to psychopathy and found that psychopaths equally remembered central and peripheral details for negative stimuli (Christianson et al., 1996).The present study investigated the relationship between psychopathic traits, the central/peripheral trade-off, and eye-tracking patterns upon viewing emotional images.Eye movements of 68 undergraduates scoring high or low on the Self-Report Psychopathy Scale were tracked while viewing a negative, positive, and neutral image.Memory for these images was subsequently tested.A central/peripheral trade-off was found only for the positive and neutral image.Eye-tracking patterns did not support the attentional narrowing hypothesis and were unrelated to memory.There was no effect of psychopathy on emotional memory, however differences in eye fixation count and duration were found between those high versus low in psychopathy when viewing the positive image.The results suggest that the relationship between attention and memory is much more complicated than previously believed.
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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 | 0.005 |
| 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) | 0.005 | 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".