The neural basis of creative production: A cross-modal ALE meta-analysis
Bibliographic record
Abstract
One of the central questions about the cognitive neuroscience of creativity is the extent to which creativity depends on either domain-specific or domain-general mechanisms. To address this question, we carried out two parallel activation likelihood estimation meta-analyses of creativity: 1) a motoric analysis that combined studies across five domains of creative production (verbalizing, music, movement, writing, and drawing), and 2) an analysis of the Alternate Uses divergent-thinking task. All experiments contained a contrast between a creative task and a matched non-creative or less-creative task that controlled for the sensorimotor demands of task performance. The activation profiles of the two meta-analyses were non-overlapping, but both pointed to a domain-specific interpretation in which creative production is, at least in part, an enhancement of sensorimotor brain areas involved in non-creative production. The most concordant areas of activation in the motoric meta-analysis were high-level motor areas such as the pre-supplementary motor area and inferior frontal gyrus that interface motor planning and executive control, suggesting a means of uniting domain-specificity and -generality in creative production.
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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 | 0.024 | 0.039 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.032 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| 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".