Increased Gamma Oscillatory Activity in the Subthalamic Nucleus During Tremor in Parkinson's Disease Patients
Bibliographic record
Abstract
Rest tremor is one of the main symptoms in Parkinson's disease (PD), although in contrast to rigidity and akinesia, the severity of the tremor does not correlate well with the degree of dopamine deficiency or the progression of the disease. Studies suggest that akinesia in PD patients is related to abnormal increased beta (15-30 Hz) and decreased gamma (35-80 Hz) synchronous oscillatory activity in the basal ganglia. Here we investigated the dynamics of oscillatory activity in the subthalamic nucleus (STN) during tremor. We used two adjacent microelectrodes to simultaneously record neuronal firing and local field potential (LFP) activity in nine PD patients who exhibited resting tremor during functional neurosurgery. We found that neurons exhibiting oscillatory activity at tremor frequency are located in the dorsal region of STN, where neurons with beta oscillatory activity are observed, and that their activity is coherent with LFP oscillations in the beta frequency range. Interestingly, in 85% of the 58 sites examined, the LFP exhibited increased oscillatory activity in the low gamma frequency range (35-55 Hz) during periods with stronger tremor. Furthermore, in 17 of 26 cases where two LFPs were recorded simultaneously, their coherence in the gamma range increased with increased tremor. When averaged across subjects, the ratio of the beta to gamma coherence was significantly lower in periods with stronger tremor compared with periods of no or weak tremor. These results suggest that resting tremor in PD is associated with an altered balance between beta and gamma oscillations in the motor circuits of STN.
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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".