Subthalamic Nucleus Stimulation Modulates Cognitive Theory of Mind in Parkinson's Disease
Bibliographic record
Abstract
BACKGROUND: Theory of mind (ToM), the ability to infer others' mental state, is essential for social interaction among human beings. It has been widely reported that both cognitive (inference of knowledge) and affective (inference of emotion) components of ToM are disrupted in Parkinson's disease (PD). Previous studies usually focused on the involvement of the prefrontal cortex. OBJECTIVE: This study investigated the causal role of the subthalamic nucleus (STN), a key hub of the fronto-basal ganglia loops, in ToM. METHODS: Thirty-four patients with idiopathic PD (15 women, aged 62.2 ± 8.3 years) completed a Yoni task with deep brain stimulation (DBS) ON and OFF. The Yoni task was designed to separate the cognitive and affective components of ToM. Volumes of tissue activated (VTA) were computed for three subregions of the STN. RESULTS: DBS showed insignificant effects on ToM inference costs at the group level, which may be due to the large interindividual variability. The associative VTA correlated with the cognitive inference cost change but not the affective inference cost change. Patients with greater associative STN stimulation infer more slowly on cognitive ToM. Stimulating associative STN can adversely affect cognitive ToM in PD patients, especially in patients with a wide range of stimulation (≥0.157) or cognitive decline (Montreal Cognitive Assessment < 26). CONCLUSIONS: The associative STN plays a causal role in cognitive ToM in patients with PD. However, stimulating the associative STN likely impairs cognitive ToM and potentially leads to social interaction deficits in PD. © 2024 International Parkinson and Movement Disorder Society.
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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".