Modulation of Motor Cortex Excitability by Physical Similarity with an Observed Hand Action
Bibliographic record
Abstract
The passive observation of hand actions is associated with increased motor cortex excitability, presumably reflecting activity within the human mirror neuron system (MNS). Recent data show that in-group ethnic membership increases motor cortex excitability during observation of culturally relevant hand gestures, suggesting that physical similarity with an observed body part may modulate MNS responses. Here, we ask whether the MNS is preferentially activated by passive observation of hand actions that are similar or dissimilar to self in terms of sex and skin color. Transcranial magnetic stimulation-induced motor evoked potentials were recorded from the first dorsal interosseus muscle while participants viewed videos depicting index finger movements made by female or male participants with black or white skin color. Forty-eight participants equally distributed in terms of sex and skin color participated in the study. Results show an interaction between self-attributes and physical attributes of the observed hand in the right motor cortex of female participants, where corticospinal excitability is increased during observation of hand actions in a different skin color than that of the observer. Our data show that specific physical properties of an observed action modulate motor cortex excitability and we hypothesize that in-group/out-group membership and self-related processes underlie these effects.
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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".