Separating neural activity associated with emotion and implied motion: An fMRI study.
Bibliographic record
Abstract
Previous research provides evidence for an emo-motoric neural network allowing emotion to modulate activity in regions of the nervous system related to movement. However, recent research suggests that these results may be due to the movement depicted in the stimuli. The purpose of the current study was to differentiate the unique neural activity of emotion and implied motion using functional MRI. Thirteen healthy participants viewed 4 sets of images: (a) negative stimuli implying movement, (b) negative stimuli not implying movement, (c) neutral stimuli implying movement, and (d) neutral stimuli not implying movement. A main effect for implied motion was found, primarily in regions associated with multimodal integration (bilateral insula and cingulate), and visual areas that process motion (bilateral middle temporal gyrus). A main effect for emotion was found primarily in occipital and parietal regions, indicating that emotion enhances visual perception. Surprisingly, emotion also activated the left precentral gyrus, a motor region. These results demonstrate that emotion elicits activity above and beyond that evoked by the perception of implied movement, but that the neural representations of these characteristics overlap. (PsycINFO Database Record
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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".