Electrophysiological and Pharmacological Properties of Locomotor Activity-Related Neurons in cfos-EGFP Mice
Bibliographic record
Abstract
Although locomotion is known to be generated by networks of spinal neurons, knowledge of the properties of these neurons is limited. Using neonatal transgenic mice that express enhanced green fluorescent protein (EGFP) driven by the c-fos promoter, we visualized EGFP-positive neurons in spinal cord slices from animals that were subjected to a locomotor task or drug cocktail [N-methyl-D-aspartate, serotonin (5-HT), dopamine, and acetylcholine (ACh)]. The activity-dependent expression of EGFP was also induced in dorsal root ganglion neurons with electrical stimulation of the neurons. Following 60-90 min of swimming, whole cell patch-clamp recordings were made from EGFP+ neurons in laminae VII, VIII, and X from slices of segments T(12) to L(4). The EGFP+ neurons (n = 55) could be classified into three types based on their responses to depolarizing step currents: single spike, phasic firing, and tonic firing. Membrane properties observed in these neurons include hyperpolarization-activated inward currents (29/55), postinhibitory rebound (11/55), and persistent-inward currents (31/55). Bath application of 10-40 microM 5-HT and/or ACh increased neuronal excitability or output with hyperpolarization of voltage threshold and changes in membrane potential. 5-HT also increased input resistance, reduced the afterhyperpolarization (AHP), and induced membrane oscillations, whereas ACh reduced the input resistance and increased the AHP. In this study, we demonstrate a new way of identifying neurons active in locomotion. Our results suggest that the EGFP+ neurons are a heterogeneous population of interneurons. The actions of 5-HT and ACh on these neurons provide insights into the neuronal properties modulated by these transmitters for generation of locomotion.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".