Lateralization of the Aberrant Amplitude of Low-Frequency Fluctuation within the Default Mode Network in Patients with Mild Cognitive Impairment
Bibliographic record
Abstract
RATIONALE AND OBJECTIVES: Alzheimer's disease (AD) is the most common pathogenesis of dementia, and mild cognitive impairment (MCI) is considered as the intermediate stage from normal elderly to AD. Early detection of MCI is an essential step for the timely intervention of AD to slow the progression of this disease. Different form previous studies in the whole-brain spontaneous activities, this research aimed to explore the low-frequency amplitude spectrum activities of patients with MCI within the default mode network (DMN), which has been involved in the process of maintaining normal cognitive function. MATERIALS AND METHODS: Based on resting-state functional magnetic resonance imaging, the amplitude of low-frequency fluctuation (ALFF) was used to analyze alterations in brain regions. The Mini-Mental State Examination and Montreal Cognitive Assessment were used for cognitive assessments. The correlation between imaging and behavioral results was analyzed among patients with MCI (n=36) and normal controls (n=26). RESULTS: The DMN is the highest coverage of brain network regarding changes in local brain activity in patients with MCI. And the MCI group showed significant aberrant lateralization of the ALFF value. CONCLUSION: The current results of our study has confirmed the hypothesis of cerebral functional impairment and compensation, and suggests that functional changes in the brain regions with reduced values of the ALFF occurred earlier than those with increased values. In a word, it suggested that the aberrant spontaneous brain activity in the DMN might be a specific imaging marker for improving MCI diagnoses.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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 | 0.000 |
| 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 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".