Pace of movement: the role of single neurons in the subthalamic nucleus
Bibliographic record
Abstract
OBJECTIVE: The ability to modulate the pace of movement is a critical factor in the smooth operation of the motor system. The authors recently described distinct and overlapping representations of movement kinematics in the subthalamic nucleus (STN), but it is still unclear how movement pace is modulated according to the demands of the task at the neuronal level in this area. The goal of this study was to clarify how different movement paces are being controlled by neurons in the STN. METHODS: The authors performed direct recording of the electrical activity of single neurons in the STN of neurosurgical patients with Parkinson's disease undergoing implantation of a deep brain stimulator under local anesthesia while the patients performed repetitive foot and hand movements intraoperatively at multiple paces. RESULTS: A change was observed in the neuronal population controlling the movement for each pace. The mechanism for switching between these controlling populations differs for hand and foot movements. CONCLUSIONS: These findings suggest that disparate schemes are utilized in the STN for neuronal recruitment for motor control of the upper and lower extremities. The results indicate a distributed model of motor control within the STN, where the active neuronal population changes when modifying the task condition and pace.
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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 | 0.000 | 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".