P4‐132: WHITE MATTER ABNORMALITIES AND STRUCTURAL PARIETAL DISCONNECTIONS IN ALZHEIMER'S DISEASE
Bibliographic record
Abstract
Previous studies in Alzheimer's disease (AD) show that white matter (WM) anisotropic abnormalities result in reduced hippocampal connectivity to temporal, inferior parietal, posterior cingulate and frontal regions. Here we aim to extend these investigations by evaluating the impact of alterations in WM anisotropy on temporo-parietal structural connectivity. WM fractional anisotropy (FA), mean diffusivity (MD) and parietal structural connectivity (PSC) were calculated from diffusion weighted images obtained from the McGill Centre for Studies in Aging (MCSA) cohort (AD N= 6, healthy controls, HC, N=24). All subjects underwent clinical and neuropsychological assessment in addition to diffusion and FLAIR and T1 weighted MRI (Siemens MAGNETOM Trio 3T system). Individuals with vascular load were excluded. Individual FA and MD maps were generated using FSL-DTIFIT. PSC maps expressing the probability of connectivity between the angular or supramarginal cortices with other cortical areas were generated using a pipeline based on FSL-probtrackx. Voxel-based group comparisons of FA, MD and PSC were estimated using Tract-Based Spatial Statistics. The proportion of abnormal to total WM volume was estimated using Wilcoxon test, corrected for multiple comparisons using False Discovery Rate. The groups were age and gender matched. As expected, MMSE was different between groups. Left angular gyrus showed reduced connectivity to the ipsilateral temporal and parietal lobe and also in contralateral projections to the superior temporal lobe. Right angular gyrus showed connectivity reduction to ipsilateral frontal lobe, parietal operculum and bilateral projections to motor cortex. Left supramarginal gyrus showed a reduction in the projections to the ipsilateral thalamus and temporal cortex. Right supramarginal connectivity was decreased to ipsilateral frontal lobe.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.005 | 0.001 |
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".