Associations between brain structures, cognition and dual-task performance in patients with mild cognitive impairment: A study based on voxel-based morphology
Bibliographic record
Abstract
BACKGROUND: This study aimed to explore the associations between brain structures, cognition, and motor control in participants with mild cognitive impairment (MCI), with a focus on dual-task performance. METHODS: Thirty MCI patients and thirty healthy controls were enrolled. Cognitive function was assessed using the Montreal Cognitive Assessment (MoCA). Structural magnetic resonance imaging data were analyzed using voxel-based morphometry (VBM) to calculate brain parenchyma volume and gray matter volume (GMV). Participants performed single- and dual-task Timed Up and Go (TUG) tests, and the correlations between significant GMV differences and task execution time was analyzed. RESULTS: MCI patients showed significantly lower MoCA scores, particularly in visuospatial/executive, attention, and delayed recall domains (p < 0.05). Dual-task TUG execution time was significantly increased in MCI patients (p < 0.05). The GMV in the right anterior lobe of the cerebellum and both insulae was positively correlated with visuospatial/executive scores (FDR-corrected, p < 0.05). The GMV of the right cerebellar anterior lobe and insula were significantly reduced in MCI patients (p < 0.05). The GMV of the right cerebellar anterior lobe was negatively correlated with dual-task execution time (r = -0.32, p = 0.012). CONCLUSION: Smaller GMV in the right anterior lobe of the cerebellum was associated with impaired dual-task performance, which may provide more evidence for the neural mechanisms of cognitive and motor function impairments in MCI.
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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 | 0.001 | 0.000 |
| 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 | 0.000 | 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 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".