The Cambridge Handbook of the Neuroscience of Creativity
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This chapter takes as its departure point a neural level theory of insight that arose from studies of the sparse, distributed, content-addressable architecture of associative memory. It is argued that convergent thought is most fruitfully characterized in terms of, not the generation of a single correct solution (as it is conventionally construed), but using concepts in their most compact form by activating neural cell assemblies that respond to their most typical properties. This allows them to be deployed in a conventional manner such that effort is reserved for exploring causal relationships. Conversely, it is argued that divergent thought is most fruitfully characterized in terms of, not the generation of multiple solutions (as it is conventionally construed), but using concepts in a form that is, albeit expanded, constrained by the situation, by activating neural cell assemblies that respond to context-specific atypical properties. This allows them to be deployed in a manner that is conducive to exploring unconventional yet potentially relevant associations, and unearthing potentially useful relationships of correlation. Thus, divergent thought can involve as few as one idea. This proposal is compatible with widespread beliefs that (1) most creative tasks require not many solutions but one, yet entail both divergent and convergent thinking, and (2) not all problems with multiple solutions require creative thinking, and conversely, some problems with single solution do require creative thought. The chapter discusses how the ability to shift between convergent and divergent modes of thought may have evolved, and it concludes with educational and vocational implications.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| 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 it