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Record W2030246288 · doi:10.1073/pnas.0611134104

Spinal cholinergic interneurons regulate the excitability of motoneurons during locomotion

2007· article· en· W2030246288 on OpenAlexafffund
Gareth B. Miles, Robert W. Hartley, Andrew J. Todd, Robert M. Brownstone

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2007
Typearticle
Languageen
FieldMedicine
TopicSpinal Cord Injury Research
Canadian institutionsDalhousie University
FundersCanadian Institutes of Health ResearchCentre National de la Recherche ScientifiqueNova Scotia Health Research FoundationWellcome Trust
KeywordsNeuroscienceCholinergicSpinal cordAfterhyperpolarizationMotor neuronBiologyInterneuronCholinergic neuronMuscarinic acetylcholine receptorElectrophysiologyInhibitory postsynaptic potentialReceptor

Abstract

fetched live from OpenAlex

To effect movement, motoneurons must respond appropriately to motor commands. Their responsiveness to these inputs, or excitability, is regulated by neuromodulators. Possible sources of modulation include the abundant cholinergic "C boutons" that surround motoneuron somata. In the present study, recordings from motoneurons in spinal cord slices demonstrated that cholinergic activation of m2-type muscarinic receptors increases excitability by reducing the action potential afterhyperpolarization. Analyses of isolated spinal cord preparations in which fictive locomotion was elicited demonstrated that endogenous cholinergic inputs increase motoneuron excitability during locomotion. Anatomical data indicate that C boutons originate from a discrete group of interneurons lateral to the central canal, the medial partition neurons. These results highlight a unique component of spinal motor networks that is critical in ensuring that sufficient output is generated by motoneurons to drive motor behavior.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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 head0.080
GPT teacher head0.404
Teacher spread0.323 · 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 source (direct Gemma or distilled Codex), 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

Citations310
Published2007
Admission routes2
Has abstractyes

Explore more

Same venueProceedings of the National Academy of SciencesSame topicSpinal Cord Injury ResearchFrench-language works237,207