Primary motor cortex neurons classified in a postural task predict muscle activation patterns in a reaching task
Bibliographic record
Abstract
Primary motor cortex (M1) activity correlates with many motor variables, making it difficult to demonstrate how it participates in motor control. We developed a two-stage process to separate the process of classifying the motor field of M1 neurons from the process of predicting the spatiotemporal patterns of its motor field during reaching. We tested our approach with a neural network model that controlled a two-joint arm to show the statistical relationship between network connectivity and neural activity across different motor tasks. In rhesus monkeys, M1 neurons classified by this method showed preferred reaching directions similar to their associated muscle groups. Importantly, the neural population signals predicted the spatiotemporal dynamics of their associated muscle groups, although a subgroup of atypical neurons reversed their directional preference, suggesting a selective role in antagonist control. These results highlight that M1 provides important details on the spatiotemporal patterns of muscle activity during motor skills such as reaching.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".