Activity in Rostral Motor Cortex in Response to Predictable Force-Pulse Perturbations in a Precision Grip Task
Bibliographic record
Abstract
The purpose of this investigation was to characterize the discharge of neurons in the rostral area 4 motor cortex (MI) during performance of a precision grip task. Three monkeys were trained to grasp an object between the thumb and index finger and to lift and hold it stationary for 2-2.5 s within a narrow position window. The grip and load forces and the vertical displacement of the object were recorded on each trial. On some trials a downward force-pulse perturbation generating a shear force and slip on the skin was applied to the object after 1.5 s of static holding. In total, 72 neurons were recorded near the rostral limit of the hand area of the motor cortex, located close to the premotor areas. Of these, 30 neurons were examined for receptive fields, and all 30 were found to receive proprioceptive inputs from finger muscles. Intracortical microstimulation applied to 38 recording sites evoked brief hand movements, most frequently involving the thumb and index finger with an average threshold of 12 microA. Slightly more than one-half of the neurons (38/72) demonstrated significant increases in firing rate that on average began 284 +/- 186 ms before grip onset. Of 54 neurons tested with predictable force-pulse perturbations, 29 (53.7%) responded with a reflexlike reaction at a mean latency of 54.2 +/- 16.8 ms. This latency was 16 ms longer than the mean latency of reflexlike activity evoked in neurons with proprioceptive receptive fields in the more caudal motor cortex. No neurons exhibited anticipatory activity that preceded the perturbation even when the perturbations were delivered randomly and signaled by a warning stimulus. The results indicate the presence of a strong proprioceptive input to the rostral motor cortex, but raise the possibility that the afferent pathway or intracortical processing may be different because of the slightly longer latency.
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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".