A Neuroimaging Strategy for the Three-Dimensional in vivo Anatomical Visualization and Characterization of Insular Gyri
Bibliographic record
Abstract
BACKGROUND: Interest in the anatomy of the insula is driven by its multifunctionality and the need for accurate visualization for surgical purposes. Few in vivo studies of human insular anatomy have been conducted due to methodological and anatomical challenges. OBJECTIVE: We used brain cortical morphometry tools to accurately reconstruct insular topology and permit a detailed visualization of its gyri in 3 dimensions. METHODS: Sixty healthy subjects (33 females; 37.8 ± 12.8 years) underwent 3-tesla MRI scans. The strategy for characterizing the insula was: (1) create 3-dimensional (3-D) insula representations for visual analysis; (2) rate topological features using a gyral conspicuity index; (3) identify individual variations across subjects/between groups; (4) compare to prior findings. RESULTS: Insular reconstruction was achieved in 113/120 cases. The anterior short, posterior short, anterior long gyri and central sulcus were easily identified. In contrast, middle short (MSG), posterior long (PLG) and accessory gyri (AG) were highly variable. The MSG, but not the PLG or AG, was clearer in males and in the left hemisphere, suggesting sex- and laterality-related differences. CONCLUSIONS: A noninvasive in vivo 3-D visualization strategy revealed anatomical variations of the insula in a healthy cohort. This methodological approach can be adopted for broad clinical and/or research purposes.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".