Altered spatiotemporal consistency of local neural activities in Parkinson's disease
Bibliographic record
Abstract
The present study aims to explore the local spatiotemporal consistency of brain connectivity in PD patients. In total, 30 PD patients and 20 health controls (HC) were collected from the Parkinson’s progression markers initiative (PPMI) and their resting state functional MRI images are acquired. FOur-dimensional Consistency of local neural Activities (FOCA) was employed for the first time to explore local brain activity differences between the two groups. To explore the relationship between FOCA values and neuropsychological indices, the Pearson correlation analysis was performed. And receiver operating characteristic (ROC) analysis was carried out to distinguish PD from HC. Compared with HC, PD patients demonstrated decreased FOCA values in the right inferior temporal gyrus (ITG.R), right middle temporal gyrus (MTG.R), right middle occipital gyrus (MOG.R), right superior occipital gyrus, right inferior occipital gyrus, left precentral gyrus (PreCG.L), left postcentral gyrus (PoCG.L) and left rolandic operculum. The FOCA values in MTG.R and ITG.R were positively related to Montreal Cognitive Assessment (MoCA) values. Negative relationships had been found in FOCA values of PreCG.L and MOG.R and Unified Parkinson’s Disease Rating Scale (UPDRS) III scores. What’s more, the ROC analysis showed that the FOCA values of altered brain regions can be used to distinguish PD patients from HC with high performance. PD patients demonstrated disrupted local brain activity in several brain regions. These brain regions are mainly involved in motor, cognitive and emotional functions. The current study provides important insights into understanding the pathophysiological mechanism of PD symptoms.
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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".