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Record W2793341813 · doi:10.1016/j.celrep.2018.02.093

Kv1.2 Channels Promote Nonlinear Spiking Motoneurons for Powering Up Locomotion

2018· article· en· W2793341813 on OpenAlexfundno aff
Rémi Bos, Ronald M. Harris‐Warrick, Cécile Brocard, L. E. Demianenko, Marin Manuel, Daniel Zytnicki, S. М. Коrogod, Frédéric Brocard

Bibliographic record

VenueCell Reports · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicIon channel regulation and function
Canadian institutionsnot available
FundersInstitut pour la Recherche sur la Moelle épinière et l’EncéphaleNational Institutes of HealthAgence Nationale de la RechercheNational Institute of Neurological Disorders and StrokeInstitut national de la recherche scientifique
KeywordsNeuroscienceNonlinear systemBiologyChemistryComputer sciencePhysics

Abstract

fetched live from OpenAlex

Spinal motoneurons are endowed with nonlinear spiking behaviors manifested by a spike acceleration whose functional significance remains uncertain. Here, we show in rodent lumbar motoneurons that these nonlinear spiking properties do not rely only on activation of dendritic nifedipine-sensitive L-type Ca 2+ channels, as assumed for decades, but also on the slow inactivation of a nifedipine-sensitive K + current mediated by Kv1.2 channels that are highly expressed in axon initial segments. Specifically, the pharmacological and computational inhibition of Kv1.2 channels occluded the spike acceleration of rhythmically active motoneurons and the correlated slow buildup of rhythmic motor output recorded at the onset of locomotor-like activity. This study demonstrates that slow inactivation of Kv1.2 channels provides a potent gain control mechanism in mammalian spinal motoneurons and has a behavioral role in enhancing locomotor drive during the transition from immobility to steady-state 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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.216
Threshold uncertainty score0.481

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 head0.016
GPT teacher head0.259
Teacher spread0.244 · 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

Citations39
Published2018
Admission routes1
Has abstractyes

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