On the Nature of the Intrinsic Connectivity of the Cat Motor Cortex: Evidence for a Recurrent Neural Network Topology
Bibliographic record
Abstract
The details and functional significance of the intrinsic horizontal connections between neurons in the motor cortex (MCx) remain to be clarified. To further elucidate the nature of this intracortical connectivity pattern, experiments were done on the MCx of three cats. The anterograde tracer biocytin was ejected iontophoretically in layers II, III, and V. Some 30–50 neurons within a radius of ∼250 μm were thus stained. The functional output of the motor cortical point at which biocytin was injected, and of the surrounding points, was identified by microstimulation and electromyographic recordings. The axonal arborizations of the stained neurons were traced under camera lucida. The axon collaterals were extensive, reaching distances of ≤7 mm from the injection site. More importantly, the axonal branches were studded all along their course with boutons. The vast majority of boutons formed synaptic contacts on the target cells as identified by electron microscopy. The majority of these boutons made asymmetric (type I, excitatory) synapses mainly on dendritic spines. The bouton density decreased approximately monotonically with distance from the center of the injection. Cluster analysis, lagged covariance analysis, and eigenvalue decomposition showed the bouton distribution map to be unimodal. Superposition of the synaptic bouton distribution map and the motor output map revealed that motor cortical neurons don't make point-to-point connections but rather bind together the representations of a variety of muscles within a large neighborhood. This recurrent-network type connectivity strongly supports the hypothesis that the MCx controls the musculature in an integrated manner.
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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 | 0.001 |
| 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".