Cortical structure of left superior parietal cortex is associated with cognition and dual tasking: A cross-sectional preliminary study between mild cognitive impairment and healthy controls
Bibliographic record
Abstract
BACKGROUND: Individuals with mild cognitive impairment (MCI) exhibit poorer performance in cognition and dual-task paradigm, while the related cortical thickness and surface area alterations remains unclear. METHODS: Thirty participants with MCI and thirty healthy controls (HC) were recruited. Magnetic resonance imaging, cognitive assessments and dual-task Timed Up and Go test (DT-TUG) were performed to assess cerebral cortical thickness and surface area, cognitive functions, and dual-task cost (DTC) of the execution time in TUG. Spearman correlations were conducted to assess the relationships between the cognitive, TUG performance with the cortical morphological measures. RESULTS: MCI participants performed worse in the Montreal cognitive assessment (MoCA), WAIS Digit Span, TMT and the modified Posner peripheral cuing task. Their execution time on the DT-TUG was also prolonged. WAIS Digit Span Backwards was correlated with DT-TUG in HC group. A significant between-group difference was observed in the surface area of the left SPC. The cortical thickness of this brain region was positively correlated with the total scores and attention subdomain of MoCA in HC group. The cortical thickness and the surface area were correlated with the time of DT-TUG in HC group only. CONCLUSIONS: Individuals with MCI demonstrated declines in both cognitive function and dual-task walking performance. This study provides further evidence of surface-based structural differences in the left SPC in individuals with and without MCI, and supports the role of the left SPC in cognition and dual-task walking.
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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 | 0.001 |
| 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) | 0.002 | 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".