Abnormal Intrinsic Brain Activity Patterns in Patients with Subcortical Ischemic Vascular Dementia
Bibliographic record
Abstract
OBJECTIVES: To investigate the amplitude of low-frequency fluctuations (ALFF) alteration of whole brain in patients with subcortical ischemic vascular dementia (SIVD). MATERIALS AND METHODS: Thirty patients with SIVD and 35 control subjects were included in this study. All of them underwent structural MRI and rs-fMRI scan. The structural data were processed using the voxel-based morphometry 8 toolbox (VBM8). The rs-fMRI data were processed using Statistical Parametric Mapping (SPM8) and Data Processing Assistant for Resting-State fMRI (DPARSF) software. Within-group analysis was performed with a one-sample Student's t-test to identify brain regions with ALFF value larger than the mean. Intergroup analysis was performed with a two-sample Student's t-test to identify ALFF differences of whole brain between SIVD and control subjects. Partial correlations between ALFF values and Montreal Cognitive Assessment (MoCA) and Mini-Mental State Examination (MMSE) scores were analyzed in the SIVD group across the parameters of age, gender, years of education, and GM volume. RESULTS: Within-group analysis showed that the bilateral anterior cingulate cortex (ACC), posterior cingulate cortex, medial prefrontal cortex (MPFC), inferior parietal lobe (IPL), occipital lobe, and adjacent precuneus had significantly higher standardized ALFF values than the global mean ALFF value in both groups. Compared to the controls, patients with SIVD presented lower ALFF values in the bilateral precuneus and higher ALFF values in the bilateral ACC, left insula and hippocampus. Including GM volume as an extra covariate, the ALFF inter-group difference exhibited highly similar spatial patterns to those without GM volume correcting. Close negative correlations were found between the ALFF values of left insula and the MoCA and MMSE scores of SIVD patients. CONCLUSION: SIVD is associated with a unique spontaneous aberrant activity of rs-fMRI signals, and measurement of ALFF in the precuneus, ACC, insula, and hippocampus may aid in the detection of SIVD.
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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".