Lateral prefrontal cortex: architectonic and functional organization
Bibliographic record
Abstract
A comparison of the architecture of the human prefrontal cortex with that of the macaque monkey showed a very similar architectonic organization in these two primate species. There is no doubt that the prefrontal cortical areas of the human brain have undergone considerable development, but it is equally clear that the basic architectonic organization is the same in the two species. Thus, a comparative approach to the study of the functional organization of the primate prefrontal cortex is more likely to reveal the essential aspects of the various complex control processes that are the domain of frontal function. The lateral frontal cortex appears to be functionally organized along both a rostral-caudal axis and a dorsal-ventral axis. The most caudal frontal region, the motor region on the precentral gyrus, is involved in fine motor control and direct sensorimotor mappings, whereas the caudal lateral prefrontal region is involved in higher order control processes that regulate the selection among multiple competing responses and stimuli based on conditional operations. Further rostrally, the mid-lateral prefrontal region plays an even more abstract role in cognitive control. The mid-lateral prefrontal region is itself organized along a dorsal-ventral axis of organization, with the mid-dorsolateral prefrontal cortex being involved in the monitoring of information in working memory and the mid-ventrolateral prefrontal region being involved in active judgments on information held in posterior cortical association regions that are necessary for active retrieval and encoding of information.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".