The Striatum and Subthalamic Nucleus as Independent and Collaborative Structures in Motor Control
Bibliographic record
Abstract
The striatum and the subthalamic nucleus (STN) are two separate input structures into the basal ganglia (BG). Accordingly, research to date has primarily focused on the distinct roles of these structures in motor control and cognition, often through investigation of Parkinson's disease (PD). Both structures are divided into sensorimotor, associative, and limbic subdivisions based on cortical connectivity. The more recent discovery of the STN as an input structure into the BG drives comparison of these two structures and their respective roles in cognition and motor control. This review compares the role of the striatum and STN in motor response inhibition and execution, competing motor programs, feedback based learning, and response planning. Through comparison, it is found that the striatum and STN have highly independent roles in motor control but also collaborate in order to execute desired actions. There is also the possibility that inhibition or activation of one of these structures indirectly contributes to the function of other connected anatomical structures. Both structures contribute to selective motor response inhibition, which forms the basis of many tasks, but the STN additionally contributes to global inhibition through the hyperdirect pathway. Research is warranted on the functional connectivity of the network for inhibition involving the rIFG, preSMA, striatum, and 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".