Decoupling of global brain activity and cerebrospinal fluid flow in Parkinson’s cognitive decline
Bibliographic record
Abstract
Abstract Background Deposition and spreading of misfolded proteins (α-synuclein and tau) have been linked to Parkinson’s cognitive dysfunction. The glymphatic system may play an important role in the clearance of these toxic proteins via cerebrospinal fluid (CSF) flow through perivascular and interstitial spaces. Recent studies discovered that sleep-dependent global brain activity is coupled to CSF flow that may reflect glymphatic function. Objective To determine if the decoupling of brain activity-CSF flow is linked to Parkinson’s cognitive dysfunction. Methods Functional and structural MRI data, clinical motor (Unified Parkinson's Disease Rating Scale), and cognitive (Montreal Cognitive Assessment, MoCA) scores were collected from 60 Parkinson’s and 58 control subjects. Parkinson’s patients were subgrouped into those with (MoCA < 26; N = 29) and without (MoCA ≥ 26; N = 31) mild cognitive impairment (MCI). The coupling strength between the resting-state global blood-oxygen-level-dependent signal (gBOLD) and associated CSF flow was quantified, compared among groups, and associated with clinical and structural measurements. Results gBOLD-CSF coupling decreased significantly ( p < 0.006) in Parkinson’s patients showing MCI, compared to those without MCI and controls. Reduced gBOLD-CSF coupling was associated with decreased MoCA scores that was present in Parkinson’s patients ( p = 0.005) but not in controls ( p = 0.65). Weaker gBOLD-CSF coupling in Parkinson’s patients also was associated with a thinner right entorhinal cortex (Spearman’s correlation = − 0.36; p = 0.012), an early structural change often seen in Alzheimer’s. Conclusions The decoupling between global brain activity and associated CSF flow is related to Parkinson’s cognitive impairment.
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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".