Abnormal Spontaneous Brain Activity in Early Parkinson’s Disease With Mild Cognitive Impairment: A Resting-State fMRI Study
Bibliographic record
Abstract
Mild cognitive impairment (MCI) is a common symptom at the baseline of early Parkinson’s disease (PD) diagnosis, but the neural mechanism is unclear. To address the issue, the present study employed resting-state functional magnetic resonance imaging data of 19 drug-naïve PD patients with normal cognition (PD-NC), 10 PD patients with MCI (PD-MCI) and 13 age- and gender-matched healthy controls (HC) from the Parkinson's progression markers initiative (PPMI) (http://www.ppmi-info.org/), and examined abnormal spontaneous brain activities in the PD-MCI. The pattern of spontaneous brain activity was measured by examining the amplitude of low-frequency fluctuations (ALFF) of blood oxygen level dependent signal. Voxel-wise one-way analysis of covariance and post-hoc analyses of ALFF were performed under non-parametric permutation tests in a general linear model among the three groups, with age, gender and data center as additional covariates. Statistical significances in the post-hoc analysis were corrected by a small volume correction with a cluster-level threshold of p < 0.05 (n = 10000 permutations, FWE-corrected). Correlations of clinical and neuropsychological assessments (i.e., Unified Parkinson's Disease Rating Scale (UPDRS) total score, Montreal Cognitive Assessment (MoCA) and cognitive domains) with the regional ALFF were performed in the PD-MCI group. Compared with the HC, both PD groups exhibited reduced ALFF in the occipital area (Calcarine_R/Cuneus_R). Specially, the PD-MCI group additionally exhibited increased ALFF in the opercular part of right inferior frontal gyrus (Frontal_Inf_Oper_R). Comparing with the PD-NC, the PD-MCI group exhibited significantly higher ALFF in the Frontal_Inf_Oper_R and left fusiform gyus (ps < 0.05). The correlation analysis revealed that the ALFF in the Frontal_Inf_Oper_R was positively correlated with the UPDRS total score (p < 0.05), but marginally negatively correlated with the MoCA score. For cognitive domains, the ALFF in the region also showed a significantly negative correlation with the score of SF test (p < 0.01) and a marginally negative correlation with the score of SDMT. Together, we concluded hyperactivity in the right inferior frontal gyrus in early PD with MCI, suggesting a compensatory recruitment in response to cognitive decline, which may shed light on thought of dementia progression and potentially comprehensive treatment in PD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".