Subjective memory ability correlates with functional connectivity between the medial temporal lobe and posterior default mode network in cognitively normal older adults
Bibliographic record
Abstract
Abstract Background Subjective cognitive decline (SCD) increases the risk of developing Alzheimer's disease (AD) but the neural mechanisms underlying this association remain unclear. Multimodal neuroimaging studies suggest that large‐scale network disruptions occur before amyloid plaques appear in the brain, beginning with alterations in the posterior default mode network (DMN). Here we investigated the association between subjective report of memory ability and functional connectivity between the posterior DMN and medial temporal lobe structures. We hypothesized that self‐report of greater memory ability would be positively correlated with functional connectivity between the posterior DMN and the medial temporal lobe. Methods Participants were 46 older adults [27 females, mean age=71.2 (6.5)] free of psychiatric or neurological illnesses, and normal cognition based on neuropsychological assessment. Subjective memory was evaluated using the Memory Functioning Questionnaire (MFQ). Resting state functional magnetic resonance imaging was acquired using gradient‐echo EPI BOLD at 3T and processed using CONN toolbox. A seed‐based analysis using the posterior cingulate cortex, a key node within the posterior DMN (x=‐6, y=‐52, z=40), as the seed was conducted to measure functional connectivity between the PCC and the hippocampus and parahippocampal regions. Correlations between functional connectivity measures and subjective memory [MFQ Frequency of Forgeting (MFQ‐FF)] as well as objective memory (California Verbal Learning Test‐II delayed recall) were performed. Results MFQ‐FF scores were significantly correlated with functional connectivity between the PCC and left parahippocampal gyrus (r = .52, p < .001). MFQ‐FF scores were similarly correlated with functional connectivity between the PCC and hippocampus (r=.34, p=.02) but this finding was not statistically significantly after applying a Bonferroni correction. In contrast, CVLT delayed recall scores were not correlated with functional connectivity of the posterior DMN and the medial temporal lobe. Conclusions Disruption of functional connectivity between the posterior DMN and the medial temporal lobe may mediate the association between SCD and AD risk.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".