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Transformation of Vestibular Signals for the Control of Standing in Humans

2016· article· en· W2552356337 on OpenAlexafffund
Patrick A. Forbes, Billy L. Luu, H. F. Machiel Van der Loos, Elizabeth A. Croft, J. Timothy Inglis, Jean‐Sébastien Blouin

Bibliographic record

VenueJournal of Neuroscience · 2016
Typearticle
Languageen
FieldNeuroscience
TopicVestibular and auditory disorders
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaEuropean Commission
KeywordsVestibular systemTransformation (genetics)Control (management)AudiologyPsychologyNeuroscienceCommunicationComputer scienceBiologyArtificial intelligenceMedicine

Abstract

fetched live from OpenAlex

During standing balance, vestibular signals encode head movement and are transformed into coordinates that are relevant to maintaining upright posture of the whole body. This transformation must account for head-on-body orientation as well as the muscle actions generating the postural response. Here, we investigate whether this transformation is dependent upon a muscle's ability to stabilize the body along the direction of a vestibular disturbance. Subjects were braced on top of a robotic balance system that simulated the mechanics of standing while being exposed to an electrical vestibular stimulus that evoked a craniocentric vestibular error of head roll. The balance system was limited to move in a single plane while the vestibular error direction was manipulated by having subjects rotate their head in yaw. Vestibular-evoked muscle responses were greatest when the vestibular error was aligned with the balance direction and decreased to zero as the two directions became orthogonal. This demonstrates that muscles respond only to the component of the error that is aligned with the balance direction and thus relevant to the balance task, not to the cumulative afferent activity, as expected for vestibulospinal reflex loops. When we reversed the relationship between balancing motor commands and associated vestibular sensory feedback, the direction of vestibular-evoked ankle compensatory responses was also reversed. This implies that the nervous system quickly reassociates new relationships between vestibular sensory signals and motor commands related to maintaining balance. These results indicate that vestibular-evoked muscle activity is a highly flexible balance response organized to compensate for vestibular disturbances. SIGNIFICANCE STATEMENT: The postural corrections critical to standing balance and navigation rely on transformation of sensory information into reference frames that are relevant for the required motor actions. Here, we demonstrate that the nervous system transforms vestibular sensory signals of head motion according to a muscle's ability to stabilize the body along the direction of a vestibular-evoked disturbance. By manipulating the direction of the imposed vestibular signal relative to a muscle's action, we show that the vestibular contribution to muscle activity is a highly flexible and organized balance response. This study provides insight into the neural integration and central processing associated with transformed vestibulomotor relationships that are essential to standing upright.

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 score0.003
Threshold uncertainty score0.011

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.042
GPT teacher head0.292
Teacher spread0.250 · 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

Citations81
Published2016
Admission routes2
Has abstractyes

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