Cerebellar microstructural and functional connectivity changes in patients with neuromyelitis optica spectrum disorders and their correlation with cognitive function: a female-dominated multimodal MRI study
Bibliographic record
Abstract
Background The cerebellum’s role in neuromyelitis optica spectrum disorder (NMOSD) remains inadequately explored, despite its known contributions to cognition and motor function. Methods This multimodal neuroimaging study integrated voxel-based morphometry (VBM), resting-state functional MRI (fMRI), and diffusion tensor imaging (DTI) to characterize cerebellar gray matter volume (GMV), microstructure, and functional connectivity (FC) in 29 NMOSD patients and 25 matched healthy controls. Clinical assessments included the Expanded Disability Status Scale (EDSS) and Montreal Cognitive Assessment (MoCA). Results Patients exhibited significant cerebellar alterations, including GMV reduction in bilateral lobules VI/VIII and the vermis, decreased fractional anisotropy in Crus I, and altered FC between Crus I and occipital/frontal regions. Critically, the structural and microstructural impairments correlated with higher EDSS scores ( * p < 0.05), while FC changes were associated with lower MoCA scores. Conclusion These findings implicate the cerebellum in both motor disability and cognitive impairment in NMOSD, providing novel evidence for cerebellar pathology as a contributor to disease progression.
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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".