Application of amplitude of low frequency fluctuation to cognitive impaired patients with Parkinson's disease: a resting state fMRI study
Bibliographic record
Abstract
Objective To investigate the changes of amplitude of low frequency fluctuation (ALFF) of the resting state fMRI in cognitively impaired Parkinson’s disease patients and discuss its underling neurophysiological mechanism. Methods Blood oxygen level-dependent low-frequency amplitude (ALFF) in resting-state functional magnetic resonance imaging were calculated in 16 healthy controls(HC) and 29 idiopathic Parkinson's disease patients (16 of which were patients with cognitive normal, PDCN and 13 with cognitive impairment, PDCI). The brain regions showing increased and decreased ALFF in patients were demonstrated by comparing normal subjects with 2-sample t-test with threshold of P<0.05 and the analysis of the relationship between the different regions of the brain activity and cognitive function tests scores were also analyzed. Results Compared with PDCN, the PDCI patients showed decreased activity in the caudate nucleus(-3, 9, 12), occipital lobe(0, -78, -15)and medial temporal lobe(42, 9, -27) and increased activity in the superior frontal gyrus(9, 63, 24). PDCI patients showed increased activity mainly in the precuneus and inferior parietal lobules compared with controls. Additionally, the regions with ALFF changes had significant correlations with the cognitive performance of patients as measured by Montreal cognitive test(Beijing Version) and neuropsychological tests (including memory, attention, visuospatial functions and executive function). Conclusion The results demonstrate that there is a specific pattern of intrinsic activity in PDCI providing insights into neurophysiological mechanisms of the Parkinson’s disease dementia. Key words: Parkinson's disease; Cognitive impairment; Resting state; Low frequency fluctuation
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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 | 0.000 | 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) | 0.000 | 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 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".