White matter tract correlations with spoken language in cerebrovascular disease
Bibliographic record
Abstract
Abstract Assessment of spoken language is a promising marker for cognitive impairment in individuals with cerebrovascular disease. However, the underlying neurological basis for spoken language beyond single words and sentences remains poorly defined in this cohort, particularly with respect to white matter. This study aimed to examine and compare white matter hyperintensity volumes and diffusion tensor metrics in normal-appearing white matter (NAWM) as potential correlates of spoken language performance. Baseline imaging and spoken language data were obtained from the cerebrovascular disease cohort of the Ontario Neurodegenerative Disease Research Initiative (n = 127; age: 55–85 years). Most participants had subclinical or very mild strokes, with very little to no aphasia symptoms. Spoken language samples were analysed to compute 10 different measures related to syntax, productivity, lexical diversity, fluency, and information content. Structural and diffusion MRI data were analysed to segment white matter hyperintensities and tracts. Normalized white matter hyperintensity volume, as well as average fractional anisotropy and mean diffusivity in the normal-appearing portion of eight white matter tracts, were correlated with the 10 spoken language measures using canonical correlation analyses. White matter and spoken language variate scores for individual participants then were correlated separately in male (n = 86) and female (n = 41) participants to probe potential sex differences. Spoken language performance was significantly associated with the fractional anisotropy (rc = 0.51, P = 0.041) and mean diffusivity (rc = 0.56, P = 0.011) of NAWM, particularly in the left superior longitudinal fasciculus, but not with white matter hyperintensity volumes (rc = 0.41, P = 0.80) in the same tracts. Measures related to syntax, fluency, and information content loaded most strongly in the spoken language variate. No significant sex differences were found in NAWM microstructure, and female and male participants exhibited similarly strong associations between spoken language and NAWM microstructure (fractional anisotropy: z = 1.44, P = 0.15; mean diffusivity: z = 1.03, P = 0.30). These results suggest that diffusion MRI in NAWM may be superior to white matter hyperintensity volumetrics when evaluating the role of white matter tract integrity on cognitive outcomes in people with relatively mild cerebrovascular pathology. These results also demonstrate that multi-domain spoken language analysis is sensitive to underlying white matter microstructure in participants with cerebrovascular disease without significant aphasia, supporting its value as a tool for assessing cognitive status.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".