Motor Cortex Neural Correlates of Output Kinematics and Kinetics During Isometric-Force and Arm-Reaching Tasks
Bibliographic record
Abstract
We recorded the activity of 132 proximal-arm-related neurons in caudal primary motor cortex (M1) of two monkeys while they generated either isometric forces against a rigid handle or arm movements with a heavy movable handle, in the same eight directions in a horizontal plane. The isometric forces increased in monotonic fashion in the direction of the force target. The forces exerted against the handle in the movement task were more complex, including an initial accelerating force in the direction of movement followed by a transient decelerating force opposite to the direction of movement as the hand approached the target. EMG activity of proximal-arm muscles reflected the difference in task dynamics, showing directional ramplike activity changes in the isometric task and reciprocally tuned "triphasic" patterns in the movement task. The apparent instantaneous directionality of muscle activity, when expressed in hand-centered spatial coordinates, remained relatively stable during the isometric ramps but often showed a large transient shift during deceleration of the arm movements. Single-neuron and population-level activity in M1 showed similar task-dependent changes in temporal pattern and instantaneous directionality. The momentary dissociation of the directionality of neuronal discharge and movement kinematics during deceleration indicated that the activity of many arm-related M1 neurons is not coupled only to the direction and speed of hand motion. These results also demonstrate that population-level signals reflecting the dynamics of motor tasks and of interactions with objects in the environment are available in caudal M1. This task-dynamics signal could greatly enhance the performance capabilities of neuroprosthetic controllers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".