Whole‐brain white matter disruption in semantic and nonfluent variants of primary progressive aphasia
Why this work is in the frame
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Bibliographic record
Abstract
Semantic (svPPA) and nonfluent (nfPPA) variants of primary progressive aphasia are associated with distinct patterns of cortical atrophy and underlying pathology. Little is known, however, about their contrasting spread of white matter disruption and how this relates to grey matter (GM) loss. We undertook a structural MRI study to investigate this relationship. We used diffusion tensor imaging, tract-based spatial statistics, and voxel-based morphometry to examine fractional anisotropy (FA) and directional diffusivities in nine patients with svPPA and nine patients with nfPPA, and compared them to 16 matched controls after accounting for global GM atrophy. Significant differences in topography of white matter changes were found, with more ventral involvement in svPPA patients and more widespread frontal involvement in nfPPA individuals. However, each group had both ventral and dorsal tract changes, and both showed spread of diffusion abnormalities beyond sites of local atrophy. There was a clear dissociation in sensitivity of diffusion tensor imaging measures between groups. SvPPA patients showed widespread changes in FA and radial diffusivity, whereas changes in axial diffusivity were more restricted and proximal to sites of GM atrophy. NfPPA patients showed isolated changes in FA, but widespread axial and radial diffusivity changes. These findings reveal the extent of white matter disruption in these variants of PPA after accounting for GM loss. Further, they suggest that differences in the relative sensitivity of diffusion metrics may reflect differences in the nature of underlying white matter pathology in these two subtypes.
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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 it