Compensatory striatal–cerebellar connectivity in mild–moderate Parkinson's disease
Bibliographic record
Abstract
Dopamine depletion in the putamen is associated with altered motor network functional connectivity in people with Parkinson's disease (PD), but the functional significance of these changes remains unclear, attributed to either pathological or compensatory mechanisms in different studies. Here, we examined the effects of PD on dorsal caudal putamen functional connectivity, off and on dopamine replacement therapy (DRT), using resting state fMRI. Motor performance was assessed with the Purdue pegboard task. Twenty-one patients with mild-moderate Parkinson's disease were studied twice, once after an overnight DRT washout and once after the administration of a standard dose of levodopa (Sinemet), and compared to 20 demographically-matched healthy control participants. PD patients off DRT showed increased putamen functional connectivity with both the cerebellum (lobule V) and primary motor cortex (M1), relative to healthy controls. Greater putamen-cerebellar functional connectivity was significantly correlated with better motor performance, whereas greater putamen-M1 functional connectivity was predictive of poorer motor performance. The administration of levodopa improved motor performance in the PD group, as expected, and reduced putamen-cerebellar connectivity to levels comparable to the healthy control group. The strength of putamen-cerebellar functional connectivity continued to predict motor performance in the PD group while on levodopa. These findings argue that increased putamen-M1 functional connectivity reflects a pathological change, deleterious to motor performance. In contrast, increased putamen-cerebellar connectivity reflects a compensatory mechanism.
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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".