Four cell types with distinctive membrane properties and morphologies in lamina I of the spinal dorsal horn of the adult rat
Bibliographic record
Abstract
Lamina I of the spinal dorsal horn plays an important role in the processing and relay of nociceptive information. Signal processing depends, in part, on neuronal membrane properties. Intrinsic membrane properties of lamina I neurons were therefore investigated using whole cell patch clamp recordings in a slice preparation of adult rat spinal cord. Based on responses to somatic current injection, four cell types were identified: tonic, which fire comparatively slowly but continuously throughout stimulation; phasic, which fire a high frequency burst of variable duration; delayed onset, which fire irregularly and with a marked delay to the first spike; and single spike, which typically fire only one action potential even when strongly depolarised. Classification by spiking pattern was further refined by identification of characteristic stimulus-response curves and quantification of several response parameters. Objectivity of the classification was confirmed by cluster analysis. Responses to stimulus trains and synaptic input as well as the kinetics of spontaneous synaptic events revealed differences in the signal processing characteristics of the cell types: tonic and delayed onset cells appeared to act predominantly as integrators whereas phasic and single spike cells acted as coincidence detectors. Intracellular labelling revealed a significant correlation between morphological and physiological cell types: tonic cells were typically fusiform, phasic cells were pyramidal, and delayed onset and single spike cells were multipolar. Thus, there are multiple physiological cells types in lamina I with specific morphological correlates and distinctive signal processing characteristics that confer significant differences in the transduction of input into spike trains.
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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 | 0.000 |
| 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".