Disrupted functional connectivity in PD with probable RBD and its cognitive correlates
Bibliographic record
Abstract
Recent studies associated rapid eye movement sleep behavior disorder (RBD) in Parkinson's disease (PD) with severe cognitive impairment and brain atrophy. However, whole-brain functional connectivity has never been explored in this group of PD patients. In this study, whole-brain network-based statistics and graph-theoretical approaches were used to characterize resting-state interregional functional connectivity in PD with probable RBD (PD-pRBD) and its relationship with cognition. Our sample consisted of 30 healthy controls, 32 PD without probable RBD (PD-non pRBD), and 27 PD-pRBD. The PD-pRBD group showed reduced functional connectivity compared with controls mainly involving cingulate areas with temporal, frontal, insular, and thalamic regions (p < 0.001). Also, the PD-pRBD group showed reduced functional connectivity between right ventral posterior cingulate and left medial precuneus compared with PD-non pRBD (p < 0.05). We found increased normalized characteristic path length in PD-pRBD compared with PD-non pRBD. In the PD-pRBD group, mean connectivity strength from reduced connections correlated with visuoperceptual task and normalized characteristic path length correlated with processing speed and verbal memory tasks. This work demonstrates the existence of disrupted functional connectivity in PD-pRBD, together with abnormal network integrity, that supports its consideration as a severe PD subtype.
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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 | 0.001 | 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".