Deep brain stimulation and recordings: Insights into the contributions of subthalamic nucleus in cognition
Bibliographic record
Abstract
Recent progress in targeted interrogation of basal ganglia structures and networks with deep brain stimulation in humans has provided insights into the complex functions the subthalamic nucleus (STN). Beyond the traditional role of the STN in modulating motor function, recognition of its role in cognition was initially fueled by side effects seen with STN DBS and later revealed with behavioral and electrophysiological studies. Anatomical, clinical, and electrophysiological data converge on the view that the STN is a pivotal node linking cognitive and motor processes. The goal of this review is to synthesize the literature to date that used DBS to examine the contributions of the STN to motor and non-motor cognitive functions and control. Multiple modalities of research have provided us with an enhanced understanding of the STN and reveal that it is critically involved in motor and non-motor inhibition, decision-making, motivation and emotion. Understanding the role of the STN in cognition can enhance the therapeutic efficacy and selectivity not only for existing applications of DBS, but also in the development of therapeutic strategies to stimulate aberrant circuits to treat non-motor symptoms of Parkinson's disease and other disorders.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".