The human subthalamic nucleus and globus pallidus internus differentially encode reward during action control
Bibliographic record
Abstract
The subthalamic nucleus (STN) and globus pallidus internus (GPi) have recently been shown to encode reward, but few studies have been performed in humans. We investigated STN and GPi encoding of reward and loss (i.e., valence) in humans with Parkinson's disease. To test the hypothesis that STN and GPi neurons would change their firing rate in response to reward- and loss-related stimuli, we recorded the activity of individual neurons while participants performed a behavioral task. In the task, action choices were associated with potential rewarding, punitive, or neutral outcomes. We found that STN and GPi neurons encode valence-related information during action control, but the proportion of valence-responsive neurons was greater in the STN compared to the GPi. In the STN, reward-related stimuli mobilized a greater proportion of neurons than loss-related stimuli. We also found surprising limbic overlap with the sensorimotor regions in both the STN and GPi, and this overlap was greater than has been previously reported. These findings may help to explain alterations in limbic function that have been observed following deep brain stimulation therapy of the STN and GPi. Hum Brain Mapp 38:1952-1964, 2017. © 2017 Wiley Periodicals, Inc.
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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) | 0.001 | 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".