Towards a neurobiological model of creativity in nonhuman animals
Bibliographic record
Abstract
We propose a cognitive and neurobiological framework for creativity in nonhuman animals based on the framework previously proposed by Kaufman and Kaufman (2004), with additional insight from recent animal behavior research, behavioral neuroscience, and creativity theories. The additional information has lead to three major changes in the 2004 model—the addition of novelty seeking as a subcategory of novelty recognition, the addition of specific neurological processing sites that correspond to each of the processes, and the transformation of the model into a spectrum in which all three levels represent different degrees of the creative process (emphasis on process) and the top level, dubbed innovation, is defined by the creative product. The framework remains a three-level model of creativity. The first level is composed of both the cognitive ability to recognize novelty, a process linked to hippocampal function, and the seeking out of novelty, which is linked to dopamine systems. The next level is observational learning, which can range in complexity from imitation to the cultural transmission of creative behavior. Observational learning may critically depend on the cerebellum, in addition to cortical regions. At the peak of the model is innovative behavior, which can include creating a tool or exhibiting a behavior with the specific understanding that it is new and different. Innovative behavior may be especially dependent upon the prefrontal cortex and/or the balance between left and right hemisphere functions. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.008 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".