Mild Cognitive Impairment Is Associated with Impaired Visual-Motor Planning When Visual Stimuli and Actions Are Incongruent
Bibliographic record
Abstract
BACKGROUND/AIMS: This study examined cognitive-motor integration in adults with mild cognitive impairment (MCI). Previously, we showed that the performance of early-stage Alzheimer's disease patients declined significantly as a visually-guided movement went from having a standard mapping (vision and action spatially aligned) to having a non-standard mapping (vision and action incongruent). The present study extends this line of research by examining the performance of individuals affected by MCI. METHODS: The participants made finger movements over a clear touchscreen placed in two separate spatial planes to either constantly present or remembered visual targets. These spatial plane conditions were repeated with the direction of cursor motion rotated 180° from that of hand motion. We also tested an 'arbitrary' condition where symbols instructed the participants to move their hand in certain directions. RESULTS: We observe that adults with MCI took significantly longer to plan movements requiring intermediate levels of non-standard mapping, relative to healthy older adults. CONCLUSIONS: These data suggest that movements requiring rule integration is affected even in individuals at a very early stage of cognitive decline. Cognitive-motor integration may provide a sensitive means to detect functional difficulty in early cognitive impairment.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".