Saturday, November 01, 2014

Buddhist Geeks 336: How to HEAL the Brain’s Negativity Bias (w/ Rick Hanson)

A while ago I posted part one of this Buddhist Geeks Conference keynote address by Dr. Rick Hanson, and now the second part is available.

Rick Hanson, Ph.D., is a neuropsychologist and New York Times best-selling author of Hardwiring Happiness: The New Brain Science of Contentment, Calm, and Confidence (2013), Buddha's Brain: The Practical Neuroscience of Happiness, Love, and Wisdom (2009), Just One Thing: Developing a Buddha Brain One Simple Practice at a Time (2011), and Mother Nurture: A Mother's Guide to Health in Body, Mind, and Intimate Relationships (2002). Hansom is also Founder of the Wellspring Institute for Neuroscience and Contemplative Wisdom.

BG 336: How to HEAL the Brain’s Negativity Bias


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Episode Description:


Rick Hanson, Ph.D., is a neuropsychologist, Senior Fellow of the Greater Good Science Center at UC Berkeley, and New York Times best-selling author. He’s been an invited speaker at Oxford, Stanford, and Harvard, and taught in meditation centers worldwide.

In the conclusion to his 2013 Buddhist Geeks Conference keynote address, Rick answers questions from the audience and leads them through the HEAL exercise, a process which trains the brain to reprogram its natural negativity bias towards the positive.
This is part two of a two part series.

Listen to part one BG 335: Practicing with the Brain in Mind.

Episode Links:

Rick Hanson
 
Rick Hanson, Ph.D., is a neuropsychologist and New York Times best-selling author. His books include Hardwiring Happiness, Buddha's Brain, Just One Thing, and Mother Nurture. Founder of the Wellspring Institute for Neuroscience and Contemplative Wisdom, and on the Advisory Board of the Greater Good Science Center at UC Berkeley, he's been an invited speaker at Oxford, Stanford, and Harvard, and taught in meditation centers worldwide. He has several audio programs and his free Just One Thing newsletter has over 100,000 subscribers.

Website: RickHanson.net
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