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Record W2048465591 · doi:10.1152/jn.00073.2012

Incomplete spinal cord injury promotes durable functional changes within the spinal locomotor circuitry

2012· article· en· W2048465591 on OpenAlexafffund
Marina Martinez, Hugo Delivet-Mongrain, Hugues Leblond, Serge Rossignol

Bibliographic record

VenueJournal of Neurophysiology · 2012
Typearticle
Languageen
FieldMedicine
TopicSpinal Cord Injury Research
Canadian institutionsUniversité de Montréal
FundersCanadian Institutes of Health Research
KeywordsCentral pattern generatorNeuroscienceSpinal cordSpinal cord injurySwingKinematicsPhysical medicine and rehabilitationPsychologyTreadmillBiological neural networkMedicineRhythmPhysical therapyPhysics

Abstract

fetched live from OpenAlex

While walking in a straight path, changes in speed result mainly from adjustments in the duration of the stance phase while the swing phase remains relatively invariant, a basic feature of the spinal central pattern generator (CPG). To produce a broad range of locomotor behaviors, the CPG has to integrate modulatory inputs from the brain and the periphery and alter these swing/stance characteristics. In the present work we raise the issue as to whether the CPG can adapt or reorganize in response to a chronic change of supraspinal inputs, as is the case after spinal cord injury (SCI). Kinematic data obtained from six adult cats walking at different treadmill speeds were collected to calculate the cycle and subphase duration at different stages after a first spinal hemisection at T(10) and after a subsequent complete SCI at T(13) respectively aimed at disconnecting unilaterally and then totally the spinal cord from its supraspinal inputs. The results show, first, that the neural control of locomotion is flexible and responsive to a partial or total loss of supraspinal inputs. Second, we demonstrate that a hemisection induces durable plastic changes within the spinal locomotor circuitry below the lesion. In addition, this study gives new insights into the organization of the spinal CPG for locomotion such that phases of the step cycle (swing, stance) can be independently regulated for adapting to speed and also that the CPGs controlling the left and right hindlimbs can, up to a point, be regulated independently.

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)0.000
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 score0.944
Threshold uncertainty score0.603

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.099
GPT teacher head0.368
Teacher spread0.270 · 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

Citations67
Published2012
Admission routes2
Has abstractyes

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