Comparison of the Morphological and Electrotonic Properties of Renshaw Cells, Ia Inhibitory Interneurons, and Motoneurons in the Cat
Bibliographic record
Abstract
The morphological and electrotonic properties of 4 motoneurons, 8 Ia inhibitory interneurons, and 4 Renshaw cells were compared. The morphological analysis, based on 3-D reconstructions of the cells, revealed that dendrites of motoneurons are longer and more extensively branched. Renshaw cells have dendrites that are shorter and simpler in structure. Dendrites of Ia inhibitory interneurons could be as long as those of motoneurons but the branching structure resembled that of Renshaw cells. Compartmental models were used to determine the electrotonic properties of the paths from each dendritic terminal to the soma. The attenuations of steady-state voltage changes in motoneurons were 3 and 7 times larger than in Ia inhibitory interneurons and Renshaw cells, respectively. The same relative order was observed for current attenuation and electrotonic length. The dendritic input resistances in Renshaw cells were 2 and 4 times larger than in Ia inhibitory interneurons and motoneurons, respectively. The difference in these electrotonic properties increased during higher synaptic activity as modeled by a decrease of Rm. The peak amplitudes of voltage transients at sites of brief, synaptic-like changes in conductance were highly dependent on cell class and were largest in Renshaw cells and smallest in motoneurons. In combination with class-specific differences in the attenuation of transient voltage signals, this led to large differences in the peak amplitudes of somatic voltage transients. Differences in the rise times and half-widths of the voltage transients were observed as well. Thus, based on passive properties, each cell class has a unique set of input/output properties.
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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) | 0.000 | 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".