Principles of neocortical organisation and behaviour in primates
Bibliographic record
Abstract
The development and evolution of neocortical organisation is typically explained by the interaction of two fundamental factors: genetics and experience-dependent processes. Morphogens and signalling molecules would orchestrate the formation of neocortical areas and connection networks, which are later refined through exposure to environmental stimuli. Evolutionary changes to these genetic programs are thought to account for the diversity of brains and behaviours observed in extant species. However, our phylogenetic comparative study of primate neuroanatomy and behaviour shows this view is incomplete. Using brain MRI from 70 primate species we observed that not only the degree of folding but also the folding pattern changes continuously with brain volume, independently of phylogenetic position. To better understand the consequences of this continuity we focused on New and Old World monkeys which diverged approximately 47 million years ago. Large New World monkeys, such as capuchins, have a significantly larger and more folded neocortex than many of their close phylogenetic relatives, whose brains are barely folded. Notably, in addition to folding, their thickness and connectivity patterns were almost identical to those of phylogenetically distant Old World monkeys. Combined analyses of MRI and endocasts from 105 primate species indicated that the highly folded neocortex of large New World monkeys evolved independently from a common ancestor with a small, unfolded brain. Remarkably, across all 70 species, behavioural similarity correlated substantially more with neuroanatomical similarity than with phylogenetic similarity. Our results challenge the prevailing explanation of the development and evolution of neocortical organisation. We propose that the "capuchin anomaly" can be resolved by incorporating mechanical morphogenesis, alongside genetics and experience, as a third fundamental factor. Growth-driven mechanical instabilities would produce similar neuroanatomical organisation patterns and behaviours, emerging independently of the specific genetic determinants of that growth.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".