How personal experience as a racial minority led to a career studying compassion meditation in diverse populations
Mind & Life Institute Interview with Helen Weng (UCSF Osher Center)
An Interview with Mind & Life Fellow, Helen Weng, PhD.
Helen is interested in how contemplative practices can improve communication within and between individuals, and how this in turn improves psychological and physical health. Her work is focused on developing a novel fMRI task to measure mindful breath awareness, using community-engaged approaches to adapt fMRI study procedures to underrepresented populations from diverse contemplative communities, and understanding how mindfulness-based interventions impact body awareness and psychophysiological variables.
[Could you tell us about your current study?] In the EMBODY study, I’m using a new fMRI methodology to study meditation. It uses machine learning or pattern recognition technology, which has been around for 15 years in the field, to identify mental states during meditation. This is in contrast to standard fMRI methods, which averages brain activity together within a person as well as across people. Because mental states during meditation are fluctuating and changing, and different people may have different patterns of brain activity, using pattern recognition approaches that are individualized to each person make more sense. The way my brain works during meditation doesn’t have to look the same as somebody else’s when they meditate. So we’re developing these methods to first study focused attention to the breath in order to see when people are paying attention to their breath or not, based on individualized brain data.
Since this methodology is more individualized to each person, it’s more conducive to including a greater diversity of people in these studies. There are a lot of biases and assumptions in neuroscience. These assumptions carry out when we analyze data.
We assume that brains act similarly, to the extent that we actually average the activity, which means we exclude certain people’s brain activity who might be considered “abnormal.” For instance, we typically exclude left-handers, people with neurological disorders, people who have had head injuries, or mental health issues. We end up with a pool of people who don’t represent the greater population. Once we have methods that accounts for each person’s unique activity, we no longer need to have all those stringent study criteria.
I’m working with the East Bay Meditation Center to reexamine these assumptions. It comes down to who can lie still in the scanner for two hours comfortably and who can pay attention to their breath.