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Record W2941739847 · doi:10.1371/journal.pbio.2003880

Glutamatergic neurons of the gigantocellular reticular nucleus shape locomotor pattern and rhythm in the freely behaving mouse

2019· article· en· W2941739847 on OpenAlexafffund
Maxime Lemieux, Frédéric Bretzner

Bibliographic record

VenuePLoS Biology · 2019
Typearticle
Languageen
FieldNeuroscience
TopicPhotoreceptor and optogenetics research
Canadian institutionsUniversité Laval
FundersCanadian Institutes of Health Research
KeywordsGlutamatergicNeurosciencePhotostimulationBiologyOptogeneticsBrainstemCentral pattern generatorReticular formationRhythmGlutamate receptorNucleusMedicineInternal medicine

Abstract

fetched live from OpenAlex

Because of their intermediate position between supraspinal locomotor centers and spinal circuits, gigantocellular reticular nucleus (GRN) neurons play a key role in motor command. However, the functional contribution of glutamatergic GRN neurons in initiating, maintaining, and stopping locomotion is still unclear. Combining electromyographic recordings with optogenetic manipulations in freely behaving mice, we investigate the functional contribution of glutamatergic brainstem neurons of the GRN to motor and locomotor activity. Short-pulse photostimulation of one side of the glutamatergic GRN did not elicit locomotion but evoked distinct motor responses in flexor and extensor muscles at rest and during locomotion. Glutamatergic GRN outputs to the spinal cord appear to be gated according to the spinal locomotor network state. Increasing the duration of photostimulation increased motor and postural tone at rest and reset locomotor rhythm during ongoing locomotion. In contrast, photoinhibition impaired locomotor pattern and rhythm. We conclude that unilateral activation of glutamatergic GRN neurons triggered motor activity and modified ongoing locomotor pattern and rhythm.

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 score0.079
Threshold uncertainty score0.272

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 science0.0010.000
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 head0.034
GPT teacher head0.263
Teacher spread0.229 · 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

Citations47
Published2019
Admission routes2
Has abstractyes

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