Impact of meditation on brain age derived from multimodal neuroimaging in experts and older adults from a randomized trial
Sacha Haudry, Natacha Lambert, Christian Gaser, Bertrand Thirion, Brigitte Landeau, Julie Gonneaud, Géraldine Poisnel, Pierre Champetier, Asrar Lehodey, Natalie L. Marchant, Olga Klimecki, Fabienne Collette, Denis Vivien, Vincent de la Sayette, Antoine Lutz, Gaël Chételat
Scientific Reports October 28, 2025 DOI: 10.1038/s41598-025-21490-9 via OpenAlex
Summary
Older adults with more than 20 years of meditation experience have a younger predicted brain age compared to cognitively unimpaired older adults without such expertise, as measured by a machine learning model trained on brain structure and metabolism data. The difference in brain age was linked to total meditation hours, mental imagery, and prosocialness. However, an 18-month meditation training program did not produce a significant effect on brain age, suggesting that long-term, sustained practice may be necessary to support healthy brain aging.
Study at a glance
| Characteristics | Randomized controlled trial Peer reviewed |
|---|---|
| Sample size | 160 |
| Population | Older adults (25 expert meditators with >20 years practice and 135 cognitively unimpaired older adults) |
| Interventions | meditation training non-native language training |
| Duration | 18-month intervention |
| Topics | Meditation |
| Keywords | Randomized controlled trial Neuroimaging Brain aging Healthy aging |
| Key finding | Long-term meditation expertise is associated with a younger predicted brain age, but an 18-month meditation training intervention did not significantly affect brain age. |
Abstract
Meditation is thought to promote healthy aging by improving mental health, preserving brain integrity and reducing Alzheimer's disease risk. We examined the impact of long-term meditation expertise and an 18-month meditation training on brain aging in older adults using machine learning. We included 25 Older Expert Meditators (OldExpMed) with > 20 years of practice and 135 Cognitively Unimpaired Older Adults (CUOA) from the Age-Well randomized controlled trial. CUOA were randomized (1:1:1) into an 18-month meditation training, a non-native language training, and a no intervention group. Brain age was predicted using a machine learning model trained on gray and white matter volume and glucose metabolism data from ADNI and replicated with a second model. Brain Predicted Age Difference (BrainPAD) was computed as the gap between predicted and chronological age. We assessed meditation expertise effects on BrainPAD, its links with meditation hours, cognitive, and affective measures, and the impact of 18-month training. Compared to CUOA, OldExpMed exhibited significantly lower/more negative BrainPAD, linked to meditation hours, mental imagery, and prosocialness. No significant effect of 18-month training was observed. Results were consistent across the replication model. Long-term meditation is associated with younger brain age, but 18-month training has no effect, emphasizing the need for sustained practice to support healthy brain aging.