MétaCan
Menu
Back to cohort
Record W3136786274 · doi:10.1126/scitranslmed.abb4422

An intracortical neuroprosthesis immediately alleviates walking deficits and improves recovery of leg control after spinal cord injury

2021· article· en· W3136786274 on OpenAlexafffund
Marco Bonizzato, Marina Martinez

Bibliographic record

VenueScience Translational Medicine · 2021
Typearticle
Languageen
FieldMedicine
TopicSpinal Cord Injury Research
Canadian institutionsUniversité de MontréalCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal
FundersInstitut TransMedTechFonds de Recherche du Québec - SantéInstitut de Valorisation des DonnéesNatural Sciences and Engineering Research Council of CanadaCraig H. Neilsen Foundation
KeywordsNeuroprostheticsSpinal cord injuryMedicineSpinal cordFoot dropPhysical medicine and rehabilitationFunctional electrical stimulationParaplegiaStimulationAnesthesia

Abstract

fetched live from OpenAlex

Most rehabilitation interventions after spinal cord injury (SCI) only target the sublesional spinal networks, peripheral nerves, and muscles. However, mammalian locomotion is not a mere act of rhythmic pattern generation. Recovery of cortical control is essential for voluntary movement and modulation of gait. We developed an intracortical neuroprosthetic intervention to SCI, with the goal to condition cortical locomotor control. Neurostimulation delivered in phase coherence with ongoing locomotion immediately alleviated primary SCI deficits, such as leg dragging, in rats with incomplete SCI. Cortical neurostimulation achieved high fidelity and markedly proportional online control of leg trajectories in both healthy and SCI rats. Long-term neuroprosthetic training lastingly improved cortical control of locomotion, whereas short training held transient improvements. We performed longitudinal awake cortical motor mapping, unveiling that recovery of cortico-spinal transmission tightly parallels return of locomotor function in rats. These results advocate directly targeting the motor cortex in clinical neuroprosthetic approaches.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.930
Threshold uncertainty score0.666

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
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 head0.031
GPT teacher head0.368
Teacher spread0.337 · 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 designObservational
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

Citations59
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueScience Translational MedicineSame topicSpinal Cord Injury ResearchFrench-language works237,207