MétaCan
Menu
Back to cohort

Tonic and Rhythmic Spinal Activity Underlying Locomotion

2017· review· en· W2584720888 on OpenAlexaff
Yuri P. Ivanenko, V. S. Gurfinkel, В. А. Селионов, И. А. Солопова, Francesca Sylos‐Labini, Pierre A. Guertin, Francesco Lacquaniti

Bibliographic record

VenueCurrent Pharmaceutical Design · 2017
Typereview
Languageen
FieldNeuroscience
TopicEEG and Brain-Computer Interfaces
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsTonic (physiology)NeuroscienceSpinal cordCentral pattern generatorRhythmReflexSensory systemMuscle toneLumbosacral jointCentral nervous systemMedicinePsychology

Abstract

fetched live from OpenAlex

In recent years, many researches put significant efforts into understanding and assessing the functional state of the spinal locomotor circuits in humans. Various techniques have been developed to stimulate the spinal cord circuitries, which may include both diffuse and quite specific tuning effects. Overall, the findings indicate that tonic and rhythmic spinal activity control are not separate phenomena but are closely integrated to properly initiate and sustain stepping. The spinal cord does not simply transmit information to and from the brain. Its physiologic state determines reflex, postural and locomotor control and, therefore, may affect the recovery of the locomotor function in individuals with spinal cord and brain injuries. This review summarizes studies that examine the rhythmogenesis capacity of cervical and lumbosacral neuronal circuitries in humans and its importance in developing central pattern generator-modulating therapies. Keywords: Central pattern generator, spinal cord, rhythmogenesis, muscle tone, neuromodulators, sensory input, Kohnstamm phenomenon, electromagnetic stimulation, locomotion.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.992
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.676
GPT teacher head0.545
Teacher spread0.131 · 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.

Study designOther design
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

Citations23
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueCurrent Pharmaceutical DesignSame topicEEG and Brain-Computer InterfacesFrench-language works237,207