Movement-related neurons of the subthalamic nucleus in patients with Parkinson disease
Bibliographic record
Abstract
OBJECT: The subthalamic nucleus (STN) is a target in the surgical treatment of Parkinson disease (PD). Little is known about the neurons within the human STN that modulate movement. The authors' goal was to examine the distribution of movement-related neurons within the STN of humans by using microelectrode recording to identify neuronal receptive fields. METHODS: Data were retrospectively collected from microelectrode recordings that had been obtained in 38 patients with PD during surgery for placement of STN deep brain stimulation electrodes. The recordings had been obtained in awake, nonsedated patients. Antiparkinsonian medications were withheld the night before surgery. Neuronal discharges were amplified, filtered, and displayed on an oscilloscope and fed to an audio monitor. The receptive fields were identified by the presence of reproducible, audible changes in the firing rate that were time-locked to the movement of specific joint(s). The median number of electrode tracks per patient was six (range two-nine). The receptive fields were identified in 278 (55%) of 510 STN neurons studied. One hundred one tracks yielded receptive field data. Fourteen percent of 64 cells tested positive for face receptive fields, 32% of 687 cells tested positive for upper-extremity receptive fields, and 21% of 242 cells tested positive for lower-extremity receptive fields. Sixty-eight cells (24%) demonstrated multiple-joint receptive fields. Ninety-three cells (65%) with movement-related receptive fields were located in the dorsal half of the STN, and 96.8% of these were located in the rostral two thirds of the STN. Analysis of receptive field locations from pooled data and along individual electrode tracks failed to reveal a consistent somatotopic organization. CONCLUSIONS: Data from this study demonstrate a regional compartmentalization of neurons with movement-related receptive fields within the STN, supporting the existence of specific motor territories within the STN in patients suffering from PD.
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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".