Cytoarchitecture and Probabilistic Maps of the Human Posterior Insular Cortex
Bibliographic record
Abstract
The human posterior insula was shown to respond to a wide variety of stimulation paradigms (e.g. pain, somatosensory, or auditory processing) in functional imaging experiments. Although various anatomical maps of this region have been published over the last century, these schemes show variable results. Moreover, none can directly be integrated with functional imaging data. Hence, our current knowledge about the structure-function relationships in this region remains limited. We therefore remapped the posterior part of the human insular cortex in 10 postmortem brains using an observer-independent approach. This analysis revealed the existence of 3 cytoarchitectonically distinct areas in the posterior insula. The examined brains were then 3D reconstructed and spatially normalized to the Montreal Neurological Institute single-subject template. Probabilistic maps for each area were calculated by superimposing the individual delineations, and a cytoarchitectonic summary map was computed to chart the regional architectonic organization. These maps can be used to identify the anatomical correlates of functional activations observed in neuroimaging studies and to understand the microstructural correlates of the functional segregation of the human posterior insula.
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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 | 0.001 |
| 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".