The role of the motor system in generating creative thoughts
Bibliographic record
Abstract
Neurocognitive research is pertinent to developing mechanistic models of how humans generate creative thoughts. Such models usually overlook the role of the motor cortex in creative thinking. The framework of embodied or grounded cognition suggests that creative thoughts (e.g. using a shoe as a hammer, improvising a piano solo) are partially served by simulations of motor activity associated with tools and their use. The major hypothesis stemming from the embodied or grounded account is that, while the motor system is used to execute actions, simulations within this system also support higher-order cognition, creativity included. That is, the cognitive process of generating creative output, not just executing it, is deeply embedded in motor processes. Here, we highlight a collection of neuroimaging research that implicates the motor system in generating creative thoughts, including some evidence for its functionally necessary role in generating creative output. Specifically, the grounded or embodied framework suggests that generating creative output may, in part, rely on motor simulations of possible actions, and that these simulations may by partially implemented in the motor regions themselves. In such cases, action simulations (i.e. reactivating or re-using the motor system), do not result in overt action but instead are used to support higher-order cognitive goals like generating creative uses or improvising.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".