Connectome-based predictive modeling of functional brain networks produces estimates of brain age that differ structurally between men and women, with distinct network patterns carrying predictive weight in each sex. Modifiable behavioral factors shifted the gap between predicted and chronological brain age, indicating that network-level aging trajectories retain a degree of plasticity. Brain age gap remains one of the more tractable intermediate markers for cognitive longevity.
Key Points
- Brain age predicted from functional connectivity patterns, not structural imaging alone
- Predictive network architecture differs meaningfully between male and female brains
- Behavioral factors modulated the gap between predicted and chronological age
Longevity Analysis
Chronological age explains less about neural function than the organization of communication between brain regions, and that organization responds to how a person lives. Sex-specific network signatures argue against uniform interpretation of brain age estimates, since the same numeric gap may reflect different underlying processes in men and women. For practitioners, the actionable element sits in the behavioral variables — sleep quality, physical activity, cardiovascular and metabolic status — that shape connectivity over years rather than weeks, and in tracking the same individual repeatedly rather than comparing them to a population norm.
Original published by Nature - npj Aging, by Shefali Chaudhary.