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Record W4414149244 · doi:10.1113/jp288632

Learning to stand with delays alters sensorimotor control but does not cause instability when returning to natural balance

2025· article· en· W4414149244 on OpenAlexafffund
Liam H. Foulger, Xiyao Liu, Amin M. Nasrabadi, Calvin Z. Qiao, Mark G. Carpenter, Lyndia C. Wu, Jean‐Sébastien Blouin

Bibliographic record

VenueThe Journal of Physiology · 2025
Typearticle
Languageen
FieldNeuroscience
TopicMotor Control and Adaptation
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBalance (ability)Control theory (sociology)Motor controlSensory systemAdaptabilityDynamic balanceControl (management)Ankle

Abstract

fetched live from OpenAlex

To maintain a bipedal posture, humans must compensate for inherent sensorimotor delays from neural conduction times and electromechanical delays. Ageing and certain neurological disorders increase these delays, so it is crucial that we adapt our control of balance to compensate for the uncertainty associated with acting on sensory information from the past. Although humans can adapt to imposed delays of 400 ms, the mechanisms underlying the adaptation process remain unknown because gross balance instability or errors are absent when returning to balancing without delays. To investigate this, we used a robotic balance simulator to impose delays of 250 ms while participants balanced upright. We characterized and modelled the adjustments in motor commands required to adapt to the addition and removal of delays. Following 20 min of adaptation, participants successfully maintained their balance with the imposed delay. When the delay was abruptly removed, participants remained upright with minimal changes in their whole-body oscillations, but we observed transient (5-20 s) spectral power increases between 1 and 2 Hz in the net ankle torque and lower limb muscle activity. Our computational model revealed that increased sensorimotor gains led to spectral changes in the balance motor commands. Our results indicate that increased sensorimotor gains are necessary to adapt balance control to longer delays and that these gains remained transiently elevated after the removal of the delays without resulting in postural instability. This highlights the remarkable adaptability of human balance control, revealing that the nervous system can flexibly adjust sensorimotor strategies to maintain balance under changing conditions. KEY POINTS: The human nervous system can adapt to sensorimotor delays, allowing us to maintain balance even though there are delays between sensed stimuli and our corrective motor actions. While balancing on a robotic simulator, participants exposed to a 250 ms delay between their self-generated motor commands and resulting whole-body motion exhibited initial difficulty maintaining balance and increased muscle (co)activation but adapted within minutes of exposure. Despite no postural instability following the abrupt removal of the 250 ms delay, participants exhibited transient (5-20 s) increases in leg muscle activation and ankle torque power (1-2 Hz). These changes in the neuromuscular control of balance after delay removal suggest increased sensitivity to sensory feedback, as supported by a computational model representing key physiological features of balance control. By revealing how the brain adapts when facing rapidly changing environments, our results highlight the flexibility of the neural control of balance to ensure robust bipedal stability.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.013
GPT teacher head0.251
Teacher spread0.238 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2025
Admission routes2
Has abstractyes

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