Superficially Located White Matter Structures Commonly Seen in the Human and the Macaque Brain with Diffusion Tensor Imaging
Bibliographic record
Abstract
The white matter of the brain consists of fiber tracts that connect different regions of the brain. Among these tracts, the intrahemispheric cortico-cortical connections are called association fibers. The U-fibers are short association fibers that connect adjacent gyri. These fibers were thought to work as part of the cortico-cortical networks to execute associative brain functions. However, their anatomy and functions have not been documented in detail for the human brain. In past studies, U-fibers have been characterized in the human brain with diffusion tensor imaging (DTI). However, the validity of such findings remains unclear. In this study, DTI of the macaque brain was performed, and the anatomy of U-fibers was compared with that of the human brain reported in a previous study. The macaque brain was chosen because it is the most commonly used animal model for exploring cognitive functions and the U-fibers of the macaque brain have been already identified by axonal tracing studies, which makes it an ideal system for confirming the DTI findings. Ten U-fibers found in the macaque brain were also identified in the human brain, with a similar organization and topology. The delineation of these species-conserved white matter structures may provide new options for understanding brain anatomy and function.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".