Abnormal dynamic functional connectivity in the hippocampal subregions of patients with untreated moderate-to-severe obstructive sleep apnea
Bibliographic record
Abstract
OBJECTIVE: To investigate the dynamic change characteristics of dynamic functional connectivity (dFC) between the hippocampal subregions (anterior and posterior) and other brain regions in obstructive sleep apnoea (OSA) and its relationship with cognitive function, and to explore whether these characteristics can be used to distinguish OSA from healthy controls (HCs). METHODS: Eighty-five patients with newly diagnosed moderate-to-severe OSA and 85 HCs were enrolled. All participants underwent resting-state functional magnetic resonance imaging (fMRI). The difference between dFC values between the hippocampal subregions and other brain regions in OSA patients and HCs was compared using the two-sample t tests. Correlation analyses were used to assess the relationship between dFC, clinical data, and cognitive functions in OSA patients. dFC values from different brain regions were used as classification features to distinguish between the two groups using a support vector machine. RESULTS: Compared with HCs, the dFC values between the left anterior hippocampus and right culmen of the cerebellum anterior lobe, right anterior hippocampus and left lingual gyrus, and left posterior hippocampus and left precentral gyrus were significantly lower, and the dFC values between the left posterior hippocampus and precuneus were significantly higher in OSA patients. The dFC values between the left posterior hippocampus and the precuneus of OSA patients were associated with sleep-related indicators and Montreal Cognitive Assessment scores. Support vector machine analysis results showed that dFC values in different brain regions could distinguish OSA patients from HCs. CONCLUSION: dFC patterns between the hippocampal subregions and other brain regions were altered in patients with OSA, including the cerebellum, default mode networks, sensorimotor networks, and visual function networks, which is possibly associated with cognitive decline. In addition, the dFC values of different brain regions could effectively distinguish OSA patients from HCs. These findings provide new perspectives on neurocognition in these patients.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".