Structural Brain Volume Covariance Associated with Gait Speed in Patients with Amnestic and Non-Amnestic Mild Cognitive Impairment: A Double Dissociation
Bibliographic record
Abstract
BACKGROUND: Gait impairment is observed in early stages of dementia, such as mild cognitive impairment (MCI), and is associated with morphological brain volume changes like atrophy. OBJECTIVE: This study aims to characterize the brain's grey matter (GM) volume covariance associated with gait speed in patients with amnestic mild cognitive impairment (aMCI) and non-amnestic MCI (naMCI). METHODS: Gait speed was measured in 171 patients with MCI (age 72.0±5.1; 36.8% female; 41 with aMCI and 130 naMCI) at normal and rapid gait speeds. Brain GM covariance networks were computed using voxel-based morphometry, using the main neural correlates of gait speed in each group and for each walking condition as seed regions. RESULTS: Normal gait speed correlated with GM volume in the left frontal cortex in patients with aMCI, and in bilateral caudate and left putamen in those with naMCI. Rapid gait speed correlated with GM volume in the bilateral caudate and right cerebellum in naMCI, but without any GM region in aMCI. For normal gait speed, the left caudate nucleus volume in naMCI covaried with subcortico-frontal regions, while the left frontal cortex covaried with cortical regions involving the frontal cortex in aMCI. For rapid gait speed, subcortico-frontal regions were similar as for normal speed in naMCI. CONCLUSION: Brain GM volume covariance associated with gait speed varies according to the type of MCI; it involved subcortico-frontal regions for patients with naMCI and the frontal cortex in those with aMCI.
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".