Cholinergic system changes in Parkinson's disease: emerging therapeutic approaches
Bibliographic record
Abstract
In patients with Parkinson's disease, heterogeneous cholinergic system changes can occur in different brain regions. These changes correlate with a range of clinical features, both motor and non-motor, that are refractory to dopaminergic therapy, and can be conceptualised within a systems-level framework in which nodal deficits can produce circuit dysfunctions. The topographies of cholinergic changes overlap with neural circuitries involved in sleep and cognitive, motor, visuo-auditory perceptual, and autonomic functions. Cholinergic deficits within cognition network hubs predict cognitive deficits better than do total brain cholinergic changes. Postural instability and gait difficulties are associated with cholinergic system changes in thalamic, caudate, limbic, neocortical, and cerebellar nodes. Cholinergic system deficits can involve also peripheral organs. Hypercholinergic activity of mesopontine cholinergic neurons in people with isolated rapid eye movement (REM) sleep behaviour disorder, as well as in the hippocampi of cognitively normal patients with Parkinson's disease, suggests early compensation during the prodromal and early stages of Parkinson's disease. Novel pharmacological and neurostimulation approaches could target the cholinergic system to treat motor and non-motor features of Parkinson's disease.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".