Action-type mapping principles extend beyond evolutionarily conserved actions, even in people born without hands
Bibliographic record
Abstract
How are actions represented in the motor system? Although the sensorimotor system is broadly organized somatotopically, higher-level sensorimotor areas encode action-type information for reaching and grasping actions-regardless of the acting body part. Does the brain similarly support generalization across acting body parts for more evolutionarily recent actions, such as tool-use? We tested whether there is a body-part-independent action-type organization in sensorimotor areas by examining fMRI responses for tool-use actions that participants performed with their hands or feet. We additionally included individuals born without hands to test whether hand sensorimotor experience is necessary for the development of this action-type organization. Across analyses, we found a consistent dissociation in the motor system. The primary sensorimotor cortices encoded concrete, body-part specific information in both groups. In contrast, higher-level motor areas within the tool-use network represent abstract, action-type information independent of the body part for both groups. Together, our results suggest that the hierarchical organization of the motor system is not dependent on a long evolutionary history of an action. Further, this organization is not dependent on an individual's manual sensorimotor experience. Our results also show that the functional reorganization in congenital handlessness follows the hierarchical organization of the intact cortex, revealing the limitations of brain plasticity. Finally, the results support using a readout of a more abstract code for hierarchical brain-computer interfaces.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".