Neurophysiological Exploration of Creativity in Engineering
Bibliographic record
Abstract
Creativity plays a crucial role in engineering education by promoting innovative thinking allowing students to go beyond conventional approaches. A profound understanding of creativity requires examining its corresponding brain behavior. Despite prior research, the neural correlates of creativity are still largely unexplored. We explored brain dynamics associated with creativity through electroencephalography (EEG). We employed a reliable dataset from loosely controlled figural creativity experiments and introduced innovative frequency-based features – the alpha power over the other EEG sub-bands. Results, consistent with previous studies, showed: 1) The average and standard deviation of our proposed features are higher in idea generation, 2) The temporal and parietal lobes contain more significant features than the other brain lobes, 3) Gamma and beta bands effectively represent brain activity in creativity. Our novel method offers a new perspective bridging existing gaps and presenting an overview of brain dynamics in creativity, serving as a foundation for future research.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".