Does Aging Impair the Capacity to Use Stored Visuospatial Information or Online Visual Control to Guide Reach-to-Grasp Reactions Evoked by Unpredictable Balance Perturbation?
Bibliographic record
Abstract
BACKGROUND: Rapid reach-to-grasp reactions are a prevalent response to sudden loss of balance and play an important role in preventing falls. A previous study indicated that young adults are able to guide functionally effective grasping reactions using visuospatial information (VSI) stored in working memory. The present study addressed whether healthy older adults are also able to use "stored" VSI in this manner or are more dependent on "online" visual control. METHODS: Liquid-crystal goggles were used to force reliance on either stored or online VSI while reaching to grasp a small handhold in response to unpredictable platform perturbations. A motor-driven device varied the handhold location unpredictably for each trial. Twelve healthy older adults (65-79 years) were compared with 12 young adults (19-29 years) tested in a previous study. RESULTS: Reach-to-grasp reactions were slower and more variable in older adults, regardless of the nature of the available VSI. When forced to rely on stored VSI, both age groups showed a reduction in reach accuracy; however, a tendency to undershoot the handhold was exacerbated in the older adults. Forced reliance on online VSI led to similar delays in both age groups; however, the older adults were more likely to reach with the "wrong" limb (contralateral to the handhold) and/or raise both arms initially (possibly to "buy" more time for final limb selection). CONCLUSION: Situations that force the central nervous system to rely on either stored or online VSI tend to exacerbate age-related reductions in speed and accuracy of reach-to-grasp balance-recovery reactions. Further work is needed to determine if this increases risk of falling in daily life.
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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 | 0.000 | 0.000 |
| 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".