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The Science of Compassion: Kindness Is a Fundamental Human Trait
Thupten Jinpa explains how recent advances in neuroscience have allowed for a better understanding of the science of compassion.
Thupten Jinpa Langri has been a principal English translator to the Dalai Lama since 1985. He has translated and edited more than ten books by the Dalai Lama including The World of Tibetan Buddhism (Wisdom Publications, 1993), A Good Heart: A Buddhist Perspective on the Teachings of Jesus (Wisdom Publications, 1996), and the New York Times bestseller Ethics for the New Millennium (Riverhead, 1999).
Thupten Jinpa Langri was born in Tibet in 1958. He received his early education and training as a monk at Zongkar Choede Monastery in Hunsur near Mysore, Karnataka, South India and later joined the Shartse College of Ganden monastic university, in Mundgod, Karnataka, South India, where he received the Geshe Lharam degree. He taught Buddhist epistemology, metaphysics, Middle Way philosophy and Buddhist psychology at Ganden for five years. Jinpa also holds a B.A. Honors degree in Western Philosophy and a Ph.D. degree in Religious Studies, both from Cambridge University, UK.
From 1996 to 1999, he was the Margaret Smith Research Fellow in Eastern Religion at Girton College, Cambridge and he has now established the Institute of Tibetan Classics where he is both president and editor-in-chief of the Institute's translation series Classics in Tibet. He is also a member of the advisory board of the Mind and Life Institute, dedicated to fostering creative dialogue between the Buddhist tradition and Western science.
He is a Visiting Research Scholar at the Stanford Institute for Neuro-Innovation and Translational Neurosciences at Stanford University.
Geshe Thupten Jinpa has written many books and articles. His latest is A Fearless Heart: How the Courage to Be Compassionate Can Transform Our Lives.
Thupten Jinpa: When we talk about the science of compassion, it’s also tied down with science of empathy. Empathy is compassion, altruism, kindness. They are all very interrelated and much of the current scientific studies really fall into two main categories. One is the study of altruistic behavior, particularly in animals and very young children. And the thinking is that if we can see altruistic behavior in animals and very, very young children, that it must have very deep biological roots. So that’s the kind of logic behind why they are focusing more on animal studies and children. The other important area that overlaps the science of compassion is the study of empathy. And again here, a lot of the work has been done on nonhuman primate studies and there is an American professor at Emory by the name of Frans de Waal and he was one of the pioneers. Many people might have seen the video of apes, you know; there were two juvenile apes fighting and one of them loses and another ape who’s not a blood relation comes over and hugs him and consoles him. So it clearly is an indication that empathy can be found in nonhuman primates as well.
And then there are some interesting studies coming from the studies of meditators who meditate many hours on compassion and then looking at their brain. You can actually see the brain’s expression in action. So this is called functioning in an MRI, which has the ability to look at a brain in action as it were. At least the claim is that the meditators are, unlike novices like us, have some ability to consciously direct their attention and thoughts so in the scanner, the brain-imaging scanner, you can ask the meditator: Can you do this? Can you do that? Can you just stay on the level of empathy and feel the pain? Now can you move onto compassion, wishing the other person to be free of suffering or wanting to do something about it. And try to tease out what brain signature, brain regions get activated when you are just in empathy feeling and when you are moving onto compassion when you are wishing to see the relief. In this way, the whole mapping of the brain regions that are involved in something like compassion is beginning to be done.
Throughout his life, Thupten Jinpa (the Dalai Lama's primary English translator) has studied the connections between science and compassion. In his latest book, A Fearless Heart, Jinpa builds off a landmark lecture given at Stanford Medical School to explain how we can take a scientific approach to train our compassion muscle to relieve stress, fight depression, improve our health, achieve our goals, and change our world.
If machines develop consciousness, or if we manage to give it to them, the human-robot dynamic will forever be different.
- Does AI—and, more specifically, conscious AI—deserve moral rights? In this thought exploration, evolutionary biologist Richard Dawkins, ethics and tech professor Joanna Bryson, philosopher and cognitive scientist Susan Schneider, physicist Max Tegmark, philosopher Peter Singer, and bioethicist Glenn Cohen all weigh in on the question of AI rights.
- Given the grave tragedy of slavery throughout human history, philosophers and technologists must answer this question ahead of technological development to avoid humanity creating a slave class of conscious beings.
- One potential safeguard against that? Regulation. Once we define the context in which AI requires rights, the simplest solution may be to not build that thing.
Duke University researchers might have solved a half-century old problem.
- Duke University researchers created a hydrogel that appears to be as strong and flexible as human cartilage.
- The blend of three polymers provides enough flexibility and durability to mimic the knee.
- The next step is to test this hydrogel in sheep; human use can take at least three years.
Duke researchers have developed the first gel-based synthetic cartilage with the strength of the real thing. A quarter-sized disc of the material can withstand the weight of a 100-pound kettlebell without tearing or losing its shape.
Photo: Feichen Yang.<p>That's the word from a team in the Department of Chemistry and Department of Mechanical Engineering and Materials Science at Duke University. Their <a href="https://onlinelibrary.wiley.com/doi/abs/10.1002/adfm.202003451" target="_blank">new paper</a>, published in the journal,<em> Advanced Functional Materials</em>, details this exciting evolution of this frustrating joint.<br></p><p>Researchers have sought materials strong and versatile enough to repair a knee since at least the seventies. This new hydrogel, comprised of three polymers, might be it. When two of the polymers are stretched, a third keeps the entire structure intact. When pulled 100,000 times, the cartilage held up as well as materials used in bone implants. The team also rubbed the hydrogel against natural cartilage a million times and found it to be as wear-resistant as the real thing. </p><p>The hydrogel has the appearance of Jell-O and is comprised of 60 percent water. Co-author, Feichen Yang, <a href="https://today.duke.edu/2020/06/lab-first-cartilage-mimicking-gel-strong-enough-knees" target="_blank">says</a> this network of polymers is particularly durable: "Only this combination of all three components is both flexible and stiff and therefore strong." </p><p> As with any new material, a lot of testing must be conducted. They don't foresee this hydrogel being implanted into human bodies for at least three years. The next step is to test it out in sheep. </p><p>Still, this is an exciting step forward in the rehabilitation of one of our trickiest joints. Given the potential reward, the wait is worth it. </p><p><span></span>--</p><p><em>Stay in touch with Derek on <a href="http://www.twitter.com/derekberes" target="_blank">Twitter</a>, <a href="https://www.facebook.com/DerekBeresdotcom" target="_blank">Facebook</a> and <a href="https://derekberes.substack.com/" target="_blank">Substack</a>. His next book is</em> "<em>Hero's Dose: The Case For Psychedelics in Ritual and Therapy."</em></p>
What would it be like to experience the 4th dimension?
Physicists have understood at least theoretically, that there may be higher dimensions, besides our normal three. The first clue came in 1905 when Einstein developed his theory of special relativity. Of course, by dimensions we’re talking about length, width, and height. Generally speaking, when we talk about a fourth dimension, it’s considered space-time. But here, physicists mean a spatial dimension beyond the normal three, not a parallel universe, as such dimensions are mistaken for in popular sci-fi shows.
An algorithm may allow doctors to assess PTSD candidates for early intervention after traumatic ER visits.
- 10-15% of people visiting emergency rooms eventually develop symptoms of long-lasting PTSD.
- Early treatment is available but there's been no way to tell who needs it.
- Using clinical data already being collected, machine learning can identify who's at risk.
The psychological scars a traumatic experience can leave behind may have a more profound effect on a person than the original traumatic experience. Long after an acute emergency is resolved, victims of post-traumatic stress disorder (PTSD) continue to suffer its consequences.
In the U.S. some 30 million patients are annually treated in emergency departments (EDs) for a range of traumatic injuries. Add to that urgent admissions to the ED with the onset of COVID-19 symptoms. Health experts predict that some 10 percent to 15 percent of these people will develop long-lasting PTSD within a year of the initial incident. While there are interventions that can help individuals avoid PTSD, there's been no reliable way to identify those most likely to need it.
That may now have changed. A multi-disciplinary team of researchers has developed a method for predicting who is most likely to develop PTSD after a traumatic emergency-room experience. Their study is published in the journal Nature Medicine.
70 data points and machine learning
Image source: Creators Collective/Unsplash
Study lead author Katharina Schultebraucks of Columbia University's Department Vagelos College of Physicians and Surgeons says:
"For many trauma patients, the ED visit is often their sole contact with the health care system. The time immediately after a traumatic injury is a critical window for identifying people at risk for PTSD and arranging appropriate follow-up treatment. The earlier we can treat those at risk, the better the likely outcomes."
The new PTSD test uses machine learning and 70 clinical data points plus a clinical stress-level assessment to develop a PTSD score for an individual that identifies their risk of acquiring the condition.
Among the 70 data points are stress hormone levels, inflammatory signals, high blood pressure, and an anxiety-level assessment. Says Schultebraucks, "We selected measures that are routinely collected in the ED and logged in the electronic medical record, plus answers to a few short questions about the psychological stress response. The idea was to create a tool that would be universally available and would add little burden to ED personnel."
Researchers used data from adult trauma survivors in Atlanta, Georgia (377 individuals) and New York City (221 individuals) to test their system.
Of this cohort, 90 percent of those predicted to be at high risk developed long-lasting PTSD symptoms within a year of the initial traumatic event — just 5 percent of people who never developed PTSD symptoms had been erroneously identified as being at risk.
On the other side of the coin, 29 percent of individuals were 'false negatives," tagged by the algorithm as not being at risk of PTSD, but then developing symptoms.
Image source: Külli Kittus/Unsplash
Schultebraucks looks forward to more testing as the researchers continue to refine their algorithm and to instill confidence in the approach among ED clinicians: "Because previous models for predicting PTSD risk have not been validated in independent samples like our model, they haven't been adopted in clinical practice." She expects that, "Testing and validation of our model in larger samples will be necessary for the algorithm to be ready-to-use in the general population."
"Currently only 7% of level-1 trauma centers routinely screen for PTSD," notes Schultebraucks. "We hope that the algorithm will provide ED clinicians with a rapid, automatic readout that they could use for discharge planning and the prevention of PTSD." She envisions the algorithm being implemented in the future as a feature of electronic medical records.
The researchers also plan to test their algorithm at predicting PTSD in people whose traumatic experiences come in the form of health events such as heart attacks and strokes, as opposed to visits to the emergency department.