MEDIAL FOREBRAIN BUNDLE STIMULATION AS A PATHOPHYSIOLOGICAL MECHANISM FOR HYPOMANIA IN SUBTHALAMIC NUCLEUS DEEP BRAIN STIMULATION FOR PARKINSON'S DISEASE
Bibliographic record
Abstract
OBJECTIVE: Hypomania accounts for approximately 4% to 13% of psychotropic adverse events during subthalamic nucleus (STN) deep brain stimulation (DBS) for Parkinson's disease. Diffusion of current into the inferior and medial "limbic" STN is often reported to be the cause. We suggest a different explanation, in which the coactivation of the medial forebrain bundle (MFB), outside the STN, leads to hypomania during STN DBS. METHODS: Six patients with advanced Parkinson's disease (age, 54 +/- 11 years) underwent bilateral STN DBS surgery. Preoperative diffusion tensor imaging scans for fiber tracking of the MFB were conducted on a 3T magnetic resonance imaging scanner. After implantation, the electrode positions were determined with computed tomography and integrated in a diffusion tensor imaging software environment. RESULTS: The medial STN was shown to send tributaries to the MFB using it as a pathway to connect to the reward circuitry. One patient, who had a transient, stimulation-induced acute hypomanic episode, showed a direct contact between 1 active electrode contact and these putative limbic STN tributaries to the MFB unilaterally on the left. In 5 asymptomatic patients, the active contacts were between 2.9 and 7.5 mm distant from the MFB or its limbic STN tributaries. CONCLUSION: We hypothesize that STN DBS-induced reversible acute hypomania might be elicited by inadvertent and unilateral coactivation of putative limbic STN tributaries to the MFB. These findings may provide insight into the neural pathways of hypomania and may facilitate future investigations of the pathophysiology of mood 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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".