The human mirror neuron system in a population with deficient self‐awareness: An fMRI study in alexithymia
Bibliographic record
Abstract
The mirror neuron system (MNS) is considered crucial for human imitation and language learning and provides the basis for the development of empathy and mentalizing. Alexithymia (ALEX), which refers to deficiencies in the self-awareness of emotional states, has been reported to be associated with poor ability in various aspects of social cognition such as mentalizing, cognitive empathy, and perspective-taking. Using functional magnetic resonance imaging (fMRI), we measured the hemodynamic signal to examine whether there are functional differences in the MNS activity between participants with ALEX (n = 16) and without ALEX (n = 13), in response to a classic MNS task (i.e., the observation of video clips depicting goal-directed hand movements). Both groups showed increased neural activity in the premotor and the parietal cortices during observation of hand actions. However, activation was greater for the ALEX group than the non-ALEX group. Furthermore, activation in the left premotor area was negatively correlated with perspective-taking ability as assessed with the interpersonal reactivity index. The signal in parietal cortices was negatively correlated with cognitive facets assessed by the stress coping inventory and positively correlated with the neuroticism scale from the NEO five factor personality scale. In addition, in the ALEX group, activation in the right superior parietal region showed a positive correlation with the severity of ALEX as measured by a structured interview. These results suggest that the stronger MNS-related neural response in individuals scoring high on ALEX is associated with their insufficient self-other differentiation.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".