SUBJECTIVE COGNITIVE DECLINE: FINE MOTOR DUAL-TASK OUTCOMES AND CHANGES IN CEREBRAL OXYGENATION
Bibliographic record
Abstract
Abstract Subjective cognitive decline (SCD) describes individuals who report cognitive complaints but perform normally on neuropsychological assessments. While the trajectory between SCD and objective cognitive impairments remains unclear, cognitive complaints are an important diagnostic criterion for mild cognitive impairment and dementia. An alternate method to measure cognitive function is dual-tasking. Dual-tasks, composed of a cognitive and motor component, may be more sensitive at detecting early cognitive declines and when paired with neuroimaging, capture changes in brain function. This study recruited older adults (70.0 ± 6.6 years) with SCD (n=24) and controls (n=18) who completed a working memory and finger tapping dual-task. In addition to completing a neuropsychological battery, finger tapping accuracy, cognitive response accuracy, and prefrontal cortex activity using functional near-infrared spectroscopy (fNIRS) were measured. Repeated measures ANOVAs were used to compare each variable across cognitive status (SCD, controls) and condition (single, dual-task). Findings revealed no differences in global cognition between the SCD and control group (p=.588). Despite this, greater prefrontal cortex activation was observed in the SCD group compared to the controls during the dual-task condition (p=.016). Cognitive and motor performance were worse in both groups as measured by lower tapping accuracy (p=.041) and response accuracy (p <.001) during the dual- compared to single task condition. Dual-tasks may be more sensitive than neuropsychological tests at detecting subtle changes in cognitive function between SCD and controls. Additional studies are needed to determine whether dual-task brain activity can complement existing measures of SCD to better identify older adults at risk of cognitive declines.
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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 | 0.001 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".