Quantitative Mapping of Human Brain Vertical‐Occipital Fasciculus
Bibliographic record
Abstract
PURPOSE: The vertical-occipital fasciculus (VOF), historically named as "the fasciculus occipitalis verticalis of Wernicke," has been recently brought to the attention of the neuroscience community. In this study, we delineated and quantified this tract with deterministic diffusion tensor imaging protocol. METHODS: Five (all males aged 24-37 years) and 10 (7 males and 3 females aged 20-51 years) right-handed healthy subjects were studied with 1 and 2 mm DT-MRI data sets, respectively. The DTI attributes of this pathway along with its cortical representation (Brodmann areas) were presented in standard Montréal Neurological Institute space. Nearby pathways such as inferior fronto-occipital (IFOF) and inferior longitudinal fasciculi (ILF) were used as reference pathways. RESULTS: The total volume of VOF has been found to be approximately .8-1% of whole brain in both data sets. The fractional anisotropy and axial diffusivity of this tract have been found to be relatively 10-15% lower than adjacent pathways such as IFOF and ILF in both data sets. Although IFOF and ILF showed somewhat leftward asymmetry in diffusivity, no right-left asymmetry has been observed in VOF. CONCLUSION: We believe that our work will pave the way for future imaging studies investigating VOF in different conditions such as stroke, traumatic brain injury, and multiple sclerosis.
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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".