Elucidating functional connectivity differences amongst older adults with mild cognitive impairment, subjective cognitive decline or normal cognition
Bibliographic record
Abstract
Reduced ability of the salience network (SN) to control switching between the central executive and default mode network (DMN) is linked to deterioration of cognitive functioning in normal aging, mild cognitive impairment (MCI) and AD dementia (He et al., 2014). In the current study, we compared functional connectivity between SN and the anterior DMN amongst older adults with subjective cognitive decline (SCD), MCI, and normal cognition (NC). Participants were 72 older adults [39 females, mean age=71.5] who were classified as either NC (n=26), SCD (n=29), or MCI (n=17). Participants underwent a 6-minute resting state functional magnetic resonance imaging using gradient-echo EPI BOLD at 3T (TR=2000ms, TE=30ms). Seed-based analysis using CONN with an anterior cingulate cortex (ACC; [0, 22,35]) seed, a key node in the SN, was conducted to assess functional connectivity between the SN and the anterior DMN within each group. Groups did not differ in age, years of education, or sex distribution [F(2,69)=0.415, p=0.66; F(2,69)=2.20, p=0.12; X² (2, N=72)=1.89, p=0.39, respectively]. Significant functional connectivity was found between ACC and medial prefrontal cortex (mPFC) in SCD and MCI groups (T(28)=2.39, p-FDR=0.04; T(16)=2.89, p-FDR=0.02, respectively) but not in the NC group. These findings show support for increased functional connectivity in SCD and MCI between SN and anterior DMN compared to NC. This finding is consistent with evidence of increased functional connectivity between the posterior DMN and mPFC in individuals with MCI and AD, an alteration that is believed to be a compensatory response to decreased functional connectivity between the posterior DMN and other brain regions such as the medial temporal lobe, responsible for memory formation and processing.
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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".