Microstructural Characterization of Short Association Fibers Related to Long‐Range White Matter Tracts in Normative Development
Bibliographic record
Abstract
Short association fibers (SAFs) in the superficial white matter play a key role in mediating local cortical connections but have not been well-studied as innovations in whole-brain diffusion tractography have only recently been developed to study superficial white matter. Characterizing SAFs and their relationship to long-range white matter tracts is crucial to advance our understanding of neurodevelopment during the period from childhood to young adulthood. This study aims to (1) map SAFs in relation to long-range white matter tracts, (2) characterize typical neurodevelopmental changes across these white matter pathways, and (3) investigate the relationship between microstructural changes in SAFs and long-range white matter tracts. Leveraging a cohort of 616 participants ranging in age from 5.6 to 21.9 years old, we performed quantitative diffusion tractography and advanced diffusion modeling with diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI). Robust linear regression models were applied to analyze microstructural features, including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), radial diffusivity (RD), intracellular volume fraction (ICVF), isotropic volume fraction (ISOVF), and orientation dispersion index (ODI). Our results reveal that both SAFs and long-range tracts exhibit similar overall developmental patterns, characterized by negative associations of MD, AD, and RD with age and positive associations of FA, ICVF, ISOVF, and ODI with age. Notably, FA, AD, and ODI exhibit significant differences between SAFs and long-range tracts, suggesting distinct neurodevelopmental trajectories between superficial and deep white matter. In addition, significant differences were found in MD, RD, and ICVF between males and females, highlighting variations in neurodevelopment. This normative study provides insights into typical microstructural changes of SAFs and long-range white matter tracts during development, laying a foundation for future research to investigate atypical development and dysfunction in disease pathology.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".