Dopaminergic Modulation of Spinal Neuronal Excitability
Bibliographic record
Abstract
It is well recognized that dopamine (DA) can modulate spinal networks and reflexes. DA fibers and receptors are present in the spinal cord, and evidence for DA release within the spinal cord has been published. A critical gap is the lack of data regarding dopaminergic modulation of intrinsic and synaptic properties of motoneurons and ventral interneurons in the mammalian spinal cord. In this paper, we address this issue by examining the cellular mechanisms underlying the excitatory effect of DA on motor systems. We examine the effects of DA on two classes of cells important for motor control, motoneurons and Hb9 interneurons, located in lamina VIII. We show that DA can boost excitability in spinal motoneurons by decreasing the first spike latency and the afterhyperpolarization. Collectively, this leads to an increase in the frequency-current slope likely attributable to modulation of I(A) and SK(Ca) (small-conductance calcium-activated K+ channel) currents. We also demonstrate that DA increases glutamatergic transmission onto motoneurons. Our data also suggest that DA stabilizes the rhythmic output of conditionally bursting interneurons. Collectively, these data indicate that DA has widespread actions on intrinsic and synaptic properties of ventral spinal neurons.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".