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Estimating brain age using high-resolution pattern recognition: Younger brains in long-term meditation practitioners.

Abstract：

:Normal aging is known to be accompanied by loss of brain substance. The present study was designed to examine whether the practice of meditation is associated with a reduced brain age. Specific focus was directed at age fifty and beyond, as mid-life is a time when aging processes are known to become more prominent. We applied a recently developed machine learning algorithm trained to identify anatomical correlates of age in the brain translating those into one single score: the BrainAGE index (in years). Using this validated approach based on high-dimensional pattern recognition, we re-analyzed a large sample of 50 long-term meditators and 50 control subjects estimating and comparing their brain ages. We observed that, at age fifty, brains of meditators were estimated to be 7.5years younger than those of controls. In addition, we examined if the brain age estimates change with increasing age. While brain age estimates varied only little in controls, significant changes were detected in meditators: for every additional year over fifty, meditators' brains were estimated to be an additional 1month and 22days younger than their chronological age. Altogether, these findings seem to suggest that meditation is beneficial for brain preservation, effectively protecting against age-related atrophy with a consistently slower rate of brain aging throughout life.

journal_name

Neuroimage

journal_title

NeuroImage

authors

Luders E,Cherbuin N,Gaser C

doi

10.1016/j.neuroimage.2016.04.007

subject

Has Abstract

pub_date

2016-07-01 00:00:00

pages

508-513

eissn

1053-8119

issn

1095-9572

pii

S1053-8119(16)30040-4

journal_volume

134

pub_type

杂志文章

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