The comparable size and overlapping nature of upper limb distal and proximal muscle representations in the human motor cortex
Bibliographic record
Abstract
The purpose of this study was to determine the relative size and location of proximal and distal upper limb muscle representations in the human motor cortex. Motor-evoked potentials (MEPs) evoked by transcranial magnetic stimulation were recorded in the proximal muscle anterior deltoid (AD) and in the distal muscles extensor carpi radialis (ECR) and first dorsal interosseus (1DI). The coil was moved in steps of 1 cm along a grid drawn on a tight-fitting polyester cap placed on the subject's head. At each location, four stimuli were delivered at 1.2 times the active motor threshold (AMT), and MEPs averaged in real-time. The peak-to-peak amplitude of each muscle's mean MEP was measured at each stimulation site. The area of a muscle's representation was measured by a pixel-counting algorithm. The optimal point of each muscle's areal representation, which corresponds to the locus near which the largest MEPs are obtained, was determined by fitting a 3D Lorentzian function to the data points. The optimal point of distal muscles tended to be situated more laterally along the motor strip than that of proximal muscles. However, there was no statistically significant difference between the size of the areal representations and they overlapped considerably. Additionally, in another five subjects, using a small 45-mm coil placed in a hyper-focal orientation, maps were obtained at a stimulus intensity of 1.1-1.15 times the AMT of the muscle with the lowest threshold, usually the 1DI. Even in this very stringent condition, the mapped representations of the AD, ECR and 1DI overlapped, notwithstanding that sharp demarcations between borders were also apparent. These observations demonstrate that stimulus spread alone does not explain the overlap of muscle representations. These results show that commonly used proximal and distal upper-limb muscles, taken individually, are controlled by motor cortical territories of approximately equal size that significantly overlap despite differences in the location of their optimal points.
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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 | 0.002 |
| 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) | 0.002 | 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".