Multimodal cortical connectome in the default mode network across the adult lifespan
Bibliographic record
Abstract
The default mode network (DMN) critically underpins cognitive and affective functions throughout the adult lifespan; however, detailed insights into its complex neuroarchitecture and connectivity patterns across aging remain limited. Leveraging the open-access CamCAN dataset, comprising structural and diffusion magnetic resonance imaging (MRI) alongside magnetoencephalography (MEG) data from 599 adults spanning ages 18 to 88 years, we systematically investigated age-associated changes in multimodal connectomes within the DMN. Our analyses revealed a progressive decline in both structural and functional connectivity among DMN subregions with advancing age. Additionally, MEG-based connectivity assessment demonstrated age-related decreases in high-frequency oscillatory activity (alpha, beta, gamma bands) accompanied by increases in low-frequency oscillations (theta band). Integrating structural data with neurophysiological measures further revealed age-dependent shifts in neurophysiological-structural coupling within the prefrontal cortex, characterized by strengthened coupling at theta frequencies but weakened coupling at higher frequencies. Conversely, coupling within the posterior cingulate cortex consistently declined across all examined frequency bands. Notably, theta-band coupling within the prefrontal cortex significantly correlated with age-related memory performance variations. Collectively, our findings delineate nuanced changes in DMN information transmission dynamics across adulthood, underscoring its promise as a neurobiological biomarker reflective of cognitive aging heterogeneity.
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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) | 0.002 | 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".