Human mirror neuron system responsivity to unimodal and multimodal presentations of action
Bibliographic record
Abstract
This study aims to clarify unresolved questions from two earlier studies (McGarry et al., 2012; Kaplan & Iacoboni, 2007) on human mirror neuron system (hMNS) responsivity to multimodal presentations of actions. These questions are: (1) whether the two frontal areas originally identified by Kaplan and Iacoboni (ventral premotor cortex [vPMC] and inferior frontal gyrus [IFG]) are both part of the hMNS (i.e., do they respond to execution as well as observation), (2) whether both areas yield effects of biologicalness (biological, control) and modality (audio, visual, audiovisual), and (3) whether the vPMC is preferentially responsive to multimodal input. To resolve these questions about the hMNS, we replicated and extended McGarry et al.’s electroencephalography (EEG) study, while incorporating advanced source localization methods. Participants were asked to execute movements (ripping paper) as well as observe those movements across the same three modalities (audio, visual, and audiovisual), all while 64-channel EEG data was recorded. Two frontal sources consistent with those identified in prior studies showed mu event-related desynchronization (mu-ERD) under execution and observation conditions. These sources also showed a greater response to biological movement than to control stimuli as well as a distinct visual advantage, with greater responsivity to visual and audiovisual compared to audio conditions. Exploratory analyses of mu-ERD in the vPMC under visual and audiovisual observation conditions suggests that the hMNS tracks the magnitude of visual movement over time.
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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) | 0.002 | 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".