Large Postural Sways Prevent Foot Tactile Information From Fading: Neurophysiological Evidence
Bibliographic record
Abstract
Abstract Cutaneous foot receptors are important for balance control, and their activation during quiet standing depends on the speed and the amplitude of postural oscillations. We hypothesized that the transmission of cutaneous input to the cortex is reduced during prolonged small postural sways due to receptor adaptation during continued skin compression. Central mechanisms would trigger large sways to reactivate the receptors. We compared the amplitude of positive and negative post-stimulation peaks (P50N90) somatosensory cortical potentials evoked by the electrical stimulation of the foot sole during small and large sways in 16 young adults standing still with their eyes closed. We observed greater P50N90 amplitudes during large sways compared with small sways consistent with increased cutaneous transmission during large sways. Postural oscillations computed 200 ms before large sways had smaller amplitudes than those before small sways, providing sustained compression within a small foot sole area. Cortical source analyses revealed that during this interval, the activity of the somatosensory areas decreased, whereas the activity of cortical areas engaged in motor planning (supplementary motor area, dorsolateral prefrontal cortex) increased. We concluded that large sways during quiet standing represent self-generated functional behavior aiming at releasing skin compression to reactivate mechanoreceptors. Such balance motor commands create sensory reafference that help control postural sway.
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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".