For the John Templeton Foundation, I wrote about groundbreaking research into how human brains map their beliefs about the divine.
Are the ways that people think about God different from the ways they think about siblings, celebrities, or superheroes? A three-year study launched in 2019, led by neuroscientists Adam Green of Georgetown University, Jordan Grafman of Northwestern University, and David Kraemer of Dartmouth College, with funding from the John Templeton Foundation, aims to increase our understanding of the ways believers and unbelievers conceptualize God in their everyday thinking using a sophisticated new approach to analyzing neuroimaging data.
The study will make use of a new data technique for analyzing brain scans. In past studies using functional magnetic resonance imaging (fMRI), researchers have looked for areas of a research participant’s brain that “light up” in association with a certain mental activity. The newer technique, called representational similarity analysis (RSA), takes fMRI data showing where mental activity is happening and applies machine learning techniques to compare the results of different kinds of mental activity — offering insight into how a particular concept or entity is represented in the brain. RSA has already been successfully applied to distinguish subjects’ mental representations of science concepts and characters in movies, but it has not previously been applied to how people think about religious concepts.