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A neuronal substrate for a state‐dependent modulation of sensory inputs in the brainstem

2010· article· en· W1902667587 on OpenAlexafffund
D. Le Ray, Laurent Juvin, Tanguy Boutin, François Auclair, Réjean Dubuc

Bibliographic record

VenueEuropean Journal of Neuroscience · 2010
Typearticle
Languageen
FieldNeuroscience
TopicNeural dynamics and brain function
Canadian institutionsUniversité du Québec à MontréalUniversité de Montréal
FundersCanadian Institutes of Health Research
KeywordsNeuroscienceBrainstemSensory systemStimulationContext (archaeology)NeurotransmissionSensory stimulation therapyMuscarinic acetylcholine receptorChemistryBiologyReceptor

Abstract

fetched live from OpenAlex

Central networks modulate sensory transmission during motor behavior. Sensory inputs may thus have distinct impacts according to the state of activity of the central networks. Using an in-vitro isolated lamprey brainstem preparation, we investigated whether a brainstem locomotor center, the mesencephalic locomotor region (MLR), modulates sensory transmission. The synaptic responses of brainstem reticulospinal (RS) cells to electrical stimulation of the sensory trigeminal nerve were recorded before and after electrical stimulation of the MLR. The RS cell synaptic responses were significantly reduced by MLR stimulation and the reduction of the response increased with the stimulation intensity of the MLR. Bath perfusion of atropine prevented the depression of sensory transmission, indicating that muscarinic receptor activation is involved. Previous studies have shown that, upon stimulation of the MLR, behavioral activity switches from a resting state to an active-locomotor state. Therefore, our results suggest that a state-dependent modulation of sensory transmission to RS cells occurs in the behavioral context of locomotion and that muscarinic inputs from the MLR are involved.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
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)0.0010.000

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 head0.048
GPT teacher head0.266
Teacher spread0.218 · 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 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

Citations17
Published2010
Admission routes2
Has abstractyes

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