P3–021: Visuomotor integration is impaired in early stage AD individuals
Bibliographic record
Abstract
When the sensory information guiding a reach movement is increasingly dissociated from the required motor output, humans must integrate rule–based information in order to reach accurately. Here, we examine the accuracy of movements requiring a visuomotor transformation in neurologically healthy elderly subjects (mean age 71.2 ± 7.3) and patients diagnosed with probable Alzheimer's Disease (mean age 79.7 ± 4.6). Participants made sliding finger movements over a clear touch sensitive screen to displace a cursor from a central target to one of four peripheral target positions. Movements were made in three planes (vertical, horizontal, and lateral).These spatial plane conditions were repeated under conditions where the direction of cursor motion (visual feedback) was rotated 180° from the direction of finger movement. In only one of these six conditions (vertical screen, vertical visual feedback) did the spatial location of the target correspond to the required final location of the finger. Significant main effects were observed between sample populations on reaction time and movement time measures. Also, significant increases in task completion errors were observed in the patient population. Further, performance was affected more by the visual feedback changes relative to the plane location changes. We show that the performance of increasingly complex movements were more difficult across both groups. Notably, however, there were increased performance deficits observed in the patient population, even those with minimal cognitive deficits. We suggest that the integration of eye and hand information may be impaired in these patients. Anatomical evidence suggests that early visuomotor transformations are processed in the posterior parietal cortex. Damage to this area of the brain in early–stage AD patients may be the source of their performance decrement. Our results demonstrate that visuomotor integration dysfunction is evident in early stage AD. This assessment may provide an accessible and sensitive tool for clinicians to gauge the functional capabilities of individuals that are experiencing Alzheimer's related dementia. In addition, this tool could discriminate individuals that have the propensity to move from MCI to AD.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".