Emotion and personal space: Neural correlates of approach‐avoidance tendencies to different facial expressions as a function of coldhearted psychopathic traits
Bibliographic record
Abstract
In social interactions, humans are expected to regulate interpersonal distance in response to the emotion displayed by others. Yet, the neural mechanisms implicated in approach-avoidance tendencies to distinct emotional expressions have not been fully described. Here, we investigated the neural systems implicated in regulating the distance to different emotions, and how they vary as a function of empathy. Twenty-three healthy participants assessed for psychopathic traits underwent fMRI scanning while they viewed approaching and withdrawing angry, fearful, happy, sad and neutral faces. Participants were also asked to set the distance to those faces on a computer screen, and to adjust the physical distance from the experimenter outside the scanner. Participants kept the greatest distances from angry faces, and shortest from happy expressions. This was accompanied by increased activation in the dorsomedial prefrontal and orbitofrontal cortices, inferior frontal gyrus, and temporoparietal junction for angry and happy expressions relative to the other emotions. Irrespective of emotion, longer distances were kept from approaching faces, which was associated with increased activation in the amygdala and insula, as well as parietal and prefrontal regions. Amygdala activation was positively correlated with greater preferred distances to angry, fearful and sad expressions. Moreover, participants scoring higher on coldhearted psychopathic traits (lower empathy) showed reduced amygdala activation to sad expressions. These findings elucidate the neural mechanisms underlying social approach-avoidance, and how they are related to variations in empathy. Hum Brain Mapp 38:1492-1506, 2017. © 2016 Wiley Periodicals, Inc.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".