An Event-Related Potential (ERP) Examination of the Neural Responses to Emotional and Movement-Related Images
Bibliographic record
Abstract
Previous research has suggested that the perception of emotional images may also activate brain regions related to the preparation of motoric plans. However, little research has investigated whether these emotion-movement interactions occur at early or later stages of visual perception. In the current research, event-related potentials (ERPs) were used to examine the time course of the independent - and combined - effects of perceiving emotions and implied movement. Twenty-five participants viewed images from four categories: 1) emotional with implied movement, 2) emotional with no implied movement, 3) neutral with implied movement, and 4) neutral with no implied movement. Both emotional stimuli and movement-related stimuli led to larger N200 (200-300 ms) waveforms. Furthermore, at frontal sites, there was a marginal interaction between emotion and implied movement, such that negative stimuli showed greater N200 amplitudes vs. neutral stimuli, but only for images with implied movement. At posterior sites, a similar effect was observed for images without implied movement. The late positive potential (LPP; 500-1000 ms) was significant for emotion (at frontal sites) and movement (at frontal, central, and posterior sites), as well as for their interaction (at parietal sites), with larger LPPs for negative vs. neutral images with movement only. Together, these results suggest that the perception of emotion and movement interact at later stages of visual perception.
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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 | 0.000 |
| 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".