Creative Control: A Neurocognitive Index of Relationships Between Creativity and Attention
Bibliographic record
Abstract
The relationship between attention and creativity in task-dependent situations is unclear.Previous work has shown that defocused attention is associated with divergent thinking (i.e.Carson, Peterson, & Higgins, 2003) and that focused attention is associated with convergent thinking (i.e.Necka, 1999).To address this discrepancy, we assess relationships between early forms of attention (sensory gating) and standardized creative thinking tasks.Attention is indexed by the P50 ERP component.Creative performance is tested in divergent and convergent thinking domains using the ATTA and CRA, respectively, as well as a convergent thinking, non-creative task.We present a correlational analysis between attentional style and creative performance from 22 participants.Our results show that defocused attention enhances divergent thinking, and that focused attention enhances convergent thinking, in both creative and non-creative domains.Furthermore, we demonstrate the utility of the P50 in creativity studies and suggest a methodological contribution that will extend current approaches to extracting P50 values.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".