Author: Adluru N1, Korponay CH2, Norton DL3, Goldman RI4, Davidson RJ4,5
Affiliation: <sup>1</sup>Waisman Center, UW-Madison, USA.
<sup>2</sup>McLean Hospital, Harvard Medical School, USA.
<sup>3</sup>Department of Biostatistics and Medical Informatics, UW-Madison, USA.
<sup>4</sup>Center for Healthy Minds, UW-Madison, USA.
<sup>5</sup>Departments of Psychology and Psychiatry, UW-Madison, USA.
Conference/Journal: Neurocase.
Date published: 2020 Feb 26
Other:
Volume ID: 1-12 , Special Notes: doi: 10.1080/13554794.2020.1731553. [Epub ahead of print] , Word Count: 114
Yongey Mingyur Rinpoche (YMR) is a Tibetan Buddhist monk, and renowned meditation practitioner and teacher who has spent an extraordinary number of hours of his life meditating. The brain-aging profile of this expert meditator in comparison to a control population was examined using a machine learning framework, which estimates "brain-age" from brain imaging. YMR's brain-aging rate appeared slower than that of controls suggesting early maturation and delayed aging. At 41 years, his brain resembled that of a 33-year-old. Specific regional changes did not differentiate YMR from controls, suggesting that the brain-aging differences may arise from coordinated changes spread throughout the gray matter.
KEYWORDS: Buddhist monk; MRI case study; long-term meditator; machine learning
PMID: 32100616 DOI: 10.1080/13554794.2020.1731553