Anatomical insights into the superior longitudinal system from integrative in- vivo and ex-vivo mapping
Bibliographic record
Abstract
Charting the organization of white matter (WM) pathways is essential for understanding the functioning of the human brain. This study provides a comprehensive, anatomically enhanced characterization of the superior longitudinal system (SLS) by integrating in-vivo tractography with ex-vivo dissection within the same radiological space. Using a data-driven cortex-to-cortex pairing approach leveraging gyral-sulcal macroanatomical landmarks, we reconstructed the dorsal associative connectivity of the frontal cortex in 39 healthy participants. We identified 45 SLS components, of which (i) 22 were validated and refined through ex-vivo dissection, (ii) 17 were deemed anatomically plausible despite lacking ex-vivo confirmation, and (iii) 6 were classified as anatomically implausible. The anatomical description of plausible sub-SLS templates revealed fundamental organizational principles of the system: (i) a medio-lateral and dorso-ventral hierarchy, where dorsal regions connect dorsally and ventral regions ventrally, and (ii) a depth-dependent organization, with shorter, superficial fibers linking proximal areas and longer, deeper fibers connecting distal regions. Pearson's correlation confirmed a significant positive relationship between streamline length and distance from the cortex (r = 0.689, p < 0.001). This study emphasizes the need for a distributed and integrated understanding of brain connectivity beyond classical bundle definition, and provides a robust anatomical foundation for future population-based WM atlases using bundle-specific tractography.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".