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Record W4307092063 · doi:10.1113/jp283181

The brain integrates proprioceptive information to ensure robust locomotion

2022· article· en· W4307092063 on OpenAlexafffund
Alessandro Santuz, Olivier D. Laflamme, Turgay Akay

Bibliographic record

VenueThe Journal of Physiology · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicZebrafish Biomedical Research Applications
Canadian institutionsDalhousie University
FundersCanadian Institutes of Health ResearchDeutsche Forschungsgemeinschaft
KeywordsProprioceptionNeuroscienceSpinal cordSensory systemAnatomyBiologyPhysical medicine and rehabilitationMedicine

Abstract

fetched live from OpenAlex

Robust locomotion relies on information from proprioceptors: sensory organs that communicate the position of body parts to the spinal cord and brain. Proprioceptive circuits in the spinal cord are known to coarsely regulate locomotion in the presence of perturbations. Yet, the regulatory importance of the brain in maintaining robust locomotion remains less clear. Here, through mouse genetic studies and in vivo electrophysiology, we examined the role of the brain in integrating proprioceptive information during perturbed locomotion. The systemic removal of proprioceptors left the mice in a constantly perturbed state, similar to that observed during mechanically perturbed locomotion in wild-type mice and characterised by longer and less accurate synergistic activation patterns. By contrast, after surgically interrupting the ascending proprioceptive projection to the brain through the dorsal column of the spinal cord, wild-type mice showed normal walking behaviour, yet lost the ability to respond to external perturbations. Our findings provide direct evidence of a pivotal role for ascending proprioceptive information in achieving robust, safe locomotion. KEY POINTS: Whether brain integration of proprioceptive feedback is crucial for coping with perturbed locomotion is not clear. We showed a crucial role of the brain for responding to external perturbations and ensure robust locomotion. We used mouse genetics to remove proprioceptors and a spinal lesion model to interrupt the flow of proprioceptive information to the brain through the dorsal column in wild-type animals. Using a custom-built treadmill, we administered sudden and random mechanical perturbations to mice during walking. External perturbations affected locomotion in wild-type mice similar to the absence of proprioceptors in genetically modified mice. Proprioceptive feedback from muscle spindles and Golgi tendon organs contributed to locomotor robustness. Wild-type mice lost the ability to respond to external perturbations after interruption of the ascending proprioceptive projection to the brainstem.

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)0.001
metaresearch head score (Gemma)0.001
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.808
Threshold uncertainty score0.265

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0010.000
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 head0.010
GPT teacher head0.268
Teacher spread0.258 · 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
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

Citations31
Published2022
Admission routes2
Has abstractyes

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