Aging and selective sensorimotor strategies in the regulation of upright balance
Bibliographic record
Abstract
BACKGROUND: The maintenance of upright equilibrium is essentially a sensorimotor integration task. The central nervous system (CNS) has to generate appropriate and complex motor responses based on the selective and rapid integration of sensory information from multiple sources. Since each sensory system has its own coordinate framework, specific time delay and reliability, sensory conflicts may arise and represent situations in which the CNS has to recalibrate the weight attributed to each particular sensory input. The resolution of sensory conflicts may represent a particular challenge for older adults given the age-related decline in the integrity of many postural regulating systems, including musculoskeletal and sensory systems, as well as neural processing and conduction of information. The effects of aging and adaptation (by repeated exposures) on the capability of the CNS to select pertinent sensory information and resolve sensory conflicts were thus investigated with virtual reality (VR) in the present study. METHODS: Healthy young and older adults maintained quiet stance while immersed in a virtual environment (VE) for 1 hour during which transient visual and/or surface perturbations were randomly presented. Visual perturbations were induced by sudden pitch or roll plane tilts of the VE viewed through a helmet-mounted display, and combined with or without surface perturbations presented in a direction that was either identical or opposite to the visual perturbations. RESULTS: Results showed a profound influence of aging on postural adjustments measured by electromyographic (EMG) responses and displacements of the center of pressure (COP) and body's center of mass (COM) in the recovery of upright stance, especially in the presence of sensory conflicts. Older adults relied more on vision as compared to young adults. Aging affects the interaction of the somatosensory and visual systems on the control of equilibrium during standing and the ability of CNS to resolve sensory conflicts. However, even with a one-hour immersion in VE and exposure to sensory conflicts, it is possible for the CNS to recalibrate and adapt to the changes, while improving balance capability in older adults. CONCLUSION: Preventive and rehabilitation programs targeting postural control in older adults should take into account the possible impairment of sensory organization or sensorimotor integration and include VE training under conditions of sensory conflicts.
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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) | 0.001 | 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".