Analysis of morphological features of thalamocortical neurons from the ventroposterolateral nucleus of the cat
Bibliographic record
Abstract
Morphological features of the dendritic arborization can affect neuronal responses and thus the input-output function of a particular neuron. In this study, morphological data of eight fully reconstructed thalamocortical (TC) neurons from the ventroposterolateral (VPL) nucleus of adult cats have been analyzed. We examined several geometrical and topological parameters, which have been previously shown to have a high impact on the neuron firing pattern and propagation of signals in the dendritic tree. In addition to well-known morphological parameters such as number of dendritic trees (8.3 +/- 1.5) and number of branching points (80-120), we investigated the distribution of dendritic membrane area, branching points, geometrical ratio, asymmetry index, and mean path length for all subtrees of the TC neurons. We demonstrate that due to extensive branching in proximal and middle dendritic sections, the maximum value of the dendritic area distribution is reached at 120-160 mum from the soma. Our analysis reveals that TC neurons are highly branched cells and their dendritic branching pattern does not follow Rall's 3/2 power rule; average values at proximal vs. distal dendritic sections were different. We also found that the dendritic branching pattern of each subtree of the cell had a wide range in symmetry index, whereas the mean path length did not show a large variation through the dendritic arborizations.
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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".