The default mode network (DMN) is linked to self-referential thinking, memory, and goal-directed cognition. Its functional connectivity with frontoparietal networks involved in attention and executive control may indicate cognitive health. This review examines DMN connectivity metrics as potential biomarkers across states like attention, mind wandering, and meditation, and in conditions such as Alzheimer's disease, Parkinson's disease, depression, and ADHD. It also addresses the reliability of network estimation and offers recommendations for using functional connectivity measures as biomarkers of cognitive health.
Using multivariate predictive models to identify brain mechanisms underlying the benefits of mindfulness meditation is a promising methodology that departs from conventional brain mapping. Two strategies—state induction and neuromarker identification—are highlighted, with examples distinguishing focused attention from mind wandering and showing effects of mindfulness interventions on somatic pain and drug-related cravings. Future research must address tradeoffs between personalized and population-based predictive modeling.