Quantitative demonstration of comparable architectonic areas within the ventromedial and lateral orbital frontal cortex in the human and the macaque monkey brains
Bibliographic record
Abstract
The orbital and ventromedial frontal cortical regions of the human and the macaque monkey brains include several spatially discrete areas which are defined histologically by their distinctive laminar architecture. Although considerable information has been collected on the function and anatomical connections of specific architectonic areas within the orbital and ventromedial frontal cortex of the macaque monkey, the location of comparable areas in the human brain remains controversial. We re-examined the comparability of orbital and ventromedial frontal areas across these two species and provide the first quantitative demonstration of architectonically comparable cortical areas in the human and the macaque brains. Images of Nissl-stained sections of the cortex were obtained at low magnification. Differences in the typical size of neurons in alternating pyramidal and granule cell layers were exploited to segregate the cortical layers before sampling. Profiles of areal neuronal density were sampled across the width of the cortex. The location of individual cortical layers was identified on each profile by sampling a set of equally sized images on which the cortical layers had been manually traced. The rank order of sampled architectonic features in comparable architectonic areas in the two species was significantly correlated. The differences in measured features between gyral and sulcal parts of the same architectonic area are at a minimum 3-4 times smaller than the differences between architectonic areas for the areas examined. Furthermore, the quantified architectonic features arrange areas within the orbital and ventromedial frontal cortex along two dimensions: an anterior-to-posterior and a medial-to-lateral dimension. On the basis of these findings, and in light of known anatomical connections in the macaque, this region of the human cortex appears to comprise at least two hierarchically structured networks of areas.
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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 | 0.000 |
| 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".