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Record W2770429290 · doi:10.7554/elife.31050

Computational modeling of spinal circuits controlling limb coordination and gaits in quadrupeds

2017· article· en· W2770429290 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueeLife · 2017
Typearticle
Languageen
FieldEngineering
TopicRobotic Locomotion and Control
Canadian institutionsUniversité de Sherbrooke
FundersNational Institute of Neurological Disorders and StrokeNational Institutes of Health
KeywordsHindlimbGaitNeuroscienceAlternation (linguistics)Sensory systemComputer scienceBiologyAnatomyPhysical medicine and rehabilitationMedicine

Abstract

fetched live from OpenAlex

Interactions between cervical and lumbar spinal circuits are mediated by long propriospinal neurons (LPNs). Ablation of descending LPNs in mice disturbs left-right coordination at high speeds without affecting fore-hind alternation. We developed a computational model of spinal circuits consisting of four rhythm generators coupled by commissural interneurons (CINs), providing left-right interactions, and LPNs, mediating homolateral and diagonal interactions. The proposed CIN and diagonal LPN connections contribute to speed-dependent gait transition from walk, to trot, and then to gallop and bound; the homolateral LPN connections ensure fore-hind alternation in all gaits. The model reproduces speed-dependent gait expression in intact and genetically transformed mice and the disruption of hindlimb coordination following ablation of descending LPNs. Inputs to CINs and LPNs can affect interlimb coordination and change gait independent of speed. We suggest that these interneurons represent the main targets for supraspinal and sensory afferent signals adjusting gait.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.339
Threshold uncertainty score0.291

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.021
GPT teacher head0.252
Teacher spread0.232 · 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