Intrinsic default—executive coupling of the creative aging brain
Bibliographic record
Abstract
Creativity refers to the ability to generate novel associations and has been linked to better problem-solving and real-world functional abilities. In younger adults, creative cognition has been associated with functional connectivity among brain networks implicated in executive control [fronto-parietal network (FPN) and salience network (SN)] and associative or elaborative processing default network (DN). Here, we investigate whether creativity is associated with the intrinsic network architecture of the brain and how these associations may differ for younger and older adults. Young (mean age: 24.76, n = 22) and older (mean age: 70.03, n = 44) adults underwent multi-echo functional magnetic resonance image scanning at rest and completed a divergent-thinking task to assess creative cognition outside the scanner. Divergent thinking in older adults, compared to young adults, was associated with functional connectivity between the default and both executive control networks (FPN and SN) as well as more widespread default-executive coupling. Finally, the ventromedial prefrontal cortex appears to be a critical node involved in within- and between-network connectivity associated with creative cognition in older adulthood. Patterns of intrinsic network coupling revealed here suggest a putative neural mechanism underlying a greater role for mnemonic processes in creative cognition in older adulthood.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".