Bilateral differences in structural connectivity of the afferent visual pathways of children with perinatal stroke
Bibliographic record
Abstract
Objective Characterize the structural organization of the afferent visual system in children with perinatal stroke (PS). Background PS is a leading cause of lifelong disability, including cerebral palsy. Cerebral visual impairment (CVI) is another common outcome, yet mechanisms and developmental plasticity of the visual system after PS are not well understood. CVI can negatively impact how children engage with their environments, consequently affecting development, learning, therapy, play, and future independence. Methods Fifty-one children with PS (22 arterial ischemic stroke (AIS), 29 periventricular venous infarction (PVI), mean 10.4 SD 2.5 years) were recruited from a large population-based sample along with 43 typically developing controls (TDC; mean age 11.3, SD 3.5 years). Diffusion weighted images were acquired from all children and the afferent visual tracts (optic chiasm to primary visual cortex) of both hemispheres were isolated using constrained spherical deconvolution (CSD)-based probabilistic tractography. Diffusion metrics of fractional anisotropy (FA) and mean diffusivity (MD) were extracted. Differences in visual pathway microstructure were examined between hemispheres and compared to TDCs. Results Both stroke subtypes showed higher MD and lower FA compared to TDC (p<0.001) in the lesioned hemisphere and lower FA (p<0.001) in the non-lesioned hemisphere. Between-hemisphere differences showed lower FA in the AIS group (p<0.001) and higher MD (p<0.001) in children with PS. Conclusion Visual pathway microstructure is altered in both hemispheres of children with PS, particularly those with AIS. Understanding the structural development of the visual pathways after PS may inform diagnostic, prognostic, and therapeutic strategies.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".