Tremor cells in the human thalamus: differences among neurological disorders
Bibliographic record
Abstract
OBJECT: Thalamic neurons firing at frequencies synchronous with tremor are thought to play a critical role in the generation and maintenance of tremor. The authors studied the incidence and locations of neurons with tremor-related activity (TRA) in the thalamus of patients with varied pathological conditions-including Parkinson disease (PD), essential tremor (ET), multiple sclerosis (MS), and cerebellar disorders--to determine whether known differences in the effectiveness of thalamic stereotactic procedures for these tremors could be correlated to differences in the incidence or locations of TRA cells. METHODS: Seventy-five operations were performed in 61 patients during which 686 TRA cells were recorded from 440 microelectrode trajectories in the thalamus. The locations of the TRA cells in relation to electrophysiologically defined thalamic nuclei and the commissural coordinates were compared among patient groups. The authors found that TRA cells are present in patients with each of these disorders and that these cells populate several nuclei in the ventral lateral tier of the thalamus. There were no large differences in the locations of TRA cells among the different diagnostic classes, although there was a difference in the incidence of TRA cells in patients with PD, who had greater than 3.8 times more cells per thalamic trajectory than patients with ET and approximately five times more cells than patients with MS or cerebellar disorders. CONCLUSIONS: There was an increased incidence of TRA in the thalamus of patients with PD. The location of thalamic TRA cells in patients with basal ganglia and other tremor disorders was similar.
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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 | 0.001 | 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".