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Record W2033763684 · doi:10.1152/jn.00482.2012

Dopamine exerts activation-dependent modulation of spinal locomotor circuits in the neonatal mouse

2012· article· en· W2033763684 on OpenAlexafffund
Jennifer M. Humphreys, Patrick J. Whelan

Bibliographic record

VenueJournal of Neurophysiology · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicZebrafish Biomedical Research Applications
Canadian institutionsUniversity of Calgary
FundersCanadian Institutes of Health Research
KeywordsNeuroscienceExcitatory postsynaptic potentialBurstingSpinal cordRhythmDopamineGlutamatergicMonoamine neurotransmitterBiological neural networkSerotoninCentral pattern generatorStimulationBiologyGlutamate receptorPsychologyChemistryInhibitory postsynaptic potentialReceptorMedicineInternal medicine

Abstract

fetched live from OpenAlex

Monoamines can modulate the output of a variety of invertebrate and vertebrate networks, including the spinal cord networks that control walking. Here we examined the multiple changes in the output of locomotor networks induced by dopamine (DA). We found that DA can depress the activation of locomotor networks in the neonatal mouse spinal cord following ventral root stimulation. By examining disinhibited rhythms, where the Renshaw cell pathway was blocked, we found that DA depresses a putative recurrent excitatory pathway that projects onto rhythm-generating circuitry of the spinal cord. This depression was D(2) but not D(1) receptor dependent and was not due exclusively to depression of excitatory drive to motoneurons. Furthermore, the depression in excitation was not dependent on network activity. We next compared the modulatory effects of DA on network function by focusing on a serotonin and a N-methyl-dl-aspartate-evoked rhythm. In contrast to the depressive effects on a ventral root-evoked rhythm, we found that DA stabilized a drug-evoked rhythm, reduced the frequency of bursting, and increased amplitude. Overall, these data demonstrate that DA can potentiate network activity while at the same time reducing the gain of recurrent excitatory feedback loops from motoneurons onto the network.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.612
Threshold uncertainty score0.213

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 head0.020
GPT teacher head0.295
Teacher spread0.275 · 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

Citations41
Published2012
Admission routes2
Has abstractyes

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