Neural Correlates of Mild Behavioral Impairment: A Functional Brain Connectivity Study Using Resting-State Functional Magnetic Resonance Imaging
Bibliographic record
Abstract
BACKGROUND: Mild behavioral impairment (MBI) is associated with accelerated cognitive decline and greater risk of dementia. However, the neural correlates of MBI have not been completely elucidated. OBJECTIVE: The study aimed to investigate the correlation between cognitively normal participants and participants with amnestic mild cognitive impairment (aMCI) using resting-state functional magnetic resonance imaging. METHODS: The study included 30 cognitively normal participants and 13 participants with aMCI (20 men and 23 women; mean age, 76.9 years). The MBI was assessed using the MBI checklist (MBI-C). Region of interest (ROI)-to-ROI analysis was performed to examine the correlation between MBI-C scores and functional connectivity (FC) of the default mode network, salience network, and frontoparietal control network (FPCN). Age, Mini-Mental State Examination score, sex, and education were used as covariates. A p-value of 0.05, with false discovery rate correction, was considered significant. RESULTS: A negative correlation was observed between the MBI-C total score and FC of the left posterior parietal cortex with the right middle frontal gyrus. A similar result was obtained for the MBI-C affective dysregulation domain score. CONCLUSION: FPCN dysfunction was detected as a neural correlate of MBI, especially in the affective dysregulation domain. This dysfunction may be associated with cognitive impairment in MBI and conversion of MBI to dementia; however, further longitudinal data are needed to examine this relationship.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".