Structural and neurophysiological alterations in Parkinson’s disease are aligned with cortical neurochemical systems
Bibliographic record
Abstract
Summary Parkinson’s disease (PD) affects cortical structures and neurophysiology. How these deviations from normative variants relate to the neurochemical systems of the cortex in a manner corresponding to motor and cognitive symptoms is unknown. We measured cortical thickness and spectral neurophysiological alterations from structural magnetic resonance imaging and task-free magnetoencephalography in patients with idiopathic PD (N MEG = 79; N MRI = 65), contrasted with similar data from matched healthy controls (N MEG = 65; N MRI = 37). Using linear mixed-effects models and cortical atlases of 19 neurochemical systems, we found that the structural and neurophysiological alterations of PD align with several receptor and transporter systems (acetylcholine, serotonin, glutamate, and noradrenaline) albeit with different implications for motor and non-motor symptoms. Some neurophysiological alignments are protective of cognitive functions: the alignment of broadband power increases with acetylcholinergic systems is related to better attention function. However, neurochemical alignment with structural and other neurophysiological alterations is associated with motor and psychiatric impairments, respectively. Collectively, the present data advance understanding of the association between the nature of neurophysiological and structural cortical alterations in PD and the symptoms that are characteristic of the disease. They also demonstrate the value of a new nested atlas modeling approach to advance research on neurological and neuropsychiatric diseases.
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".