The organization of inter-hemispheric projections from areas 17 and 18 in the human splenium, studied with DTI probabilistic fiber tracking
Bibliographic record
Abstract
Animal tracer studies show a clear pattern of organization of intercortical callosal connections between early visual areas of the left and right hemisphere. To investigate if a similar organization is evident for human occipital cortex we performed diffusion tensor imaging with probabilistic fiber tracking in 10 healthy volunteers. Areas 17 and 18 were defined in two different ways, using high-resolution structural T1-weighted MRI scans: (1) anatomically through defined masks of upper and lower early visual cortex around the calcarine fissure, and (2) through masks of areas 17 and 18 from histological probability maps. Diffusion-tensor imaging data were analyzed by probabilistic tracking methods in FSL. Our results first confirm through cortical-connectivity-based hard segmentation of the entire corpus callosum that connections between areas 17 and 18 of both hemispheres are confined to the lower part of the splenium. Second, there is an orderly representation of the callosal projections of the upper and lower hemifields of both areas 17 and 18 in the splenium. This mirrors the anatomic relations of these regions in the occipital lobe: fibers from dorsal area 18, inferior bank of area 17, superior bank of area 17, and ventral area 18 are layered from antero-dorsal to postero-ventral. We conclude that the quadrantic organization of areas 17 and 18 is preserved in their callosal projections through the splenium.
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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".