A New Anatomical Landmark for Reliable Identification of Human Area V5/MT: a Quantitative Analysis of Sulcal Patterning
Bibliographic record
Abstract
The location of human area V5 (or MT) has been correlated with the intersection of the ascending limb of the inferior temporal sulcus (ALITS) and the lateral occipital sulcus (LO). This study was undertaken to attempt a replication and quantification of these observations using functional magnetic resonance imaging. V5 was significantly activated in 19 hemispheres with alternating, low contrast, random checkerboard patterns. We confirmed the stereotaxic location of V5 and were able to describe a fairly consistent sulcal pattern in the parieto-temporo-occipital cortex. V5 was usually (95%) buried within a sulcus, most commonly within the inferior temporal sulcus (ITS) (11%), the ascending limb of the ITS (ALITS) (53%) and the posterior continuation of the ITS (26%). The average distance from V5 of two identified anatomical landmarks of V5, the junctions of the LO and the ALITS, and the ITS and ALITS, were both 1 cm. However, the LO-ALITS junction often had to be determined by interpolation (47%), and was not always present even with interpolation (21%). In contrast, the ITS-ALITS junction was always present and V5 was usually (90%) located in a sulcus intersecting with this junction, making it a more reliable landmark for localizing V5 with respect to gross morphological features on individual cortical surfaces.
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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 | 0.002 | 0.001 |
| 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) | 0.002 | 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".