Different Patterns of Cortical Inputs to Subregions of the Primary Motor Cortex Hand Representation in<i>Cebus apella</i>
Bibliographic record
Abstract
The primary motor cortex (M1) plays an essential role in the control of hand movements in primates and is part of a complex cortical sensorimotor network involving multiple premotor and parietal areas. In a previous study in squirrel monkeys, we found that the ventral premotor cortex (PMv) projected mainly to 3 regions within the M1 forearm representation [rostro-medial (RM), rostro-lateral (RL), and caudo-lateral (CL)] with very few caudo-medial (CM) projections. These results suggest that projections from premotor areas to M1 are not uniform, but rather segregated into subregions. The goal of the present work was to study how inputs from diverse areas of the ipsilateral cortical network are organized within the M1 hand representation. In Cebus apella, different retrograde neuroanatomical tracers were injected in 4 subregions of the hand area of M1 (RM, RL, CM, and CL). We found a different pattern of input to each subregion of M1. RM receives inputs predominantly from dorsal premotor cortex, RL from PMv, CM from area 5, and CL from area 2. These results support that the M1 hand representation is composed of several subregions, each part of a unique cortical network.
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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 | 0.001 |
| 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".