Single unit and beta oscillatory activities in subthalamic nucleus are modulated during visual choice preference
Bibliographic record
Abstract
Parkinson's disease is a neurodegenerative disease affecting the supply of dopamine to basal ganglia nuclei, leading to pathological beta band (13-35 Hz) oscillations in the subthalamic nucleus (STN). STN and beta activity are recognized in motoric functions but their role in cognitive functions remains elusive. We examined single unit and beta local field potential (LFP) activity in the STN during a visual choice preference task in PD patients (n = 12) undergoing deep brain stimulation surgery. Patients viewed 2 of 5 possible animal picture-pairs and were instructed to choose their favorite ("fav") picture by clicking the left or right mouse key. A block of trials consisted of 50-75 picture-pair presentations. Single unit histograms and LFP spectrograms were aligned to picture presentation and point of decision for pairs that included the fav and non-fav pictures, respectively. A total of 58 neurons from 26 blocks of trials were analyzed. Thirty of 58 neurons showed a selective change in spiking activity 0.20-0.65 s to fav picture presentation, which preceded the shortest recorded reaction time (=0.7 s), and 17/58 neurons showed no significant response in our task. Beta LFP significantly desynchronized in response to fav but not non-fav pictures in all trials, and in 14/26 blocks of trials, the desynchronization was followed by a "beta burst" and ramp-up to baseline activity. Neurons with choice preference responses were found throughout the dorsoventral extent of the STN. STN single units and beta activity are modulated during visual choice preference, and this suggests a role for STN beta activity in cognitive processing.
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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) | 0.000 | 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".