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Record W3127661488 · doi:10.3390/ijms22031467

Relative Contribution of Proprioceptive and Vestibular Sensory Systems to Locomotion: Opportunities for Discovery in the Age of Molecular Science

2021· review· en· W3127661488 on OpenAlexafffund
Turgay Akay, Andrew Murray

Bibliographic record

VenueInternational Journal of Molecular Sciences · 2021
Typereview
Languageen
FieldNeuroscience
TopicVestibular and auditory disorders
Canadian institutionsDalhousie University
FundersNational Institute of Neurological Disorders and StrokeWellcome TrustCanadian Institutes of Health ResearchGeorgia Institute of Technology
KeywordsVestibular systemSomatosensory systemNeuroscienceSensory systemProprioceptionCentral pattern generatorRhythmBiologyPsychologyComputer scienceMedicine

Abstract

fetched live from OpenAlex

Locomotion is a fundamental animal behavior required for survival and has been the subject of neuroscience research for centuries. In terrestrial mammals, the rhythmic and coordinated leg movements during locomotion are controlled by a combination of interconnected neurons in the spinal cord, referred as to the central pattern generator, and sensory feedback from the segmental somatosensory system and supraspinal centers such as the vestibular system. How segmental somatosensory and the vestibular systems work in parallel to enable terrestrial mammals to locomote in a natural environment is still relatively obscure. In this review, we first briefly describe what is known about how the two sensory systems control locomotion and use this information to formulate a hypothesis that the weight of the role of segmental feedback is less important at slower speeds but increases at higher speeds, whereas the weight of the role of vestibular system has the opposite relation. The new avenues presented by the latest developments in molecular sciences using the mouse as the model system allow the direct testing of the hypothesis.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.494
Threshold uncertainty score0.589

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.098
GPT teacher head0.364
Teacher spread0.265 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreReview

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

Citations42
Published2021
Admission routes2
Has abstractyes

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