The 20th century produced a plethora of discoveries in science and technology. Too often, though, society has used these triumphs to reinforce the conventional view of intelligence. By equating intelligence with hyper-rationality, this narrow conception neglects the vital role of affect: feeling capacities that were selected in evolution because they helped to solve fundamental problems of survival and life regulation in an intelligent manner. Through theoretical and empirical neuroscientific investigation, our project will illuminate the importance of affect in intelligence.

Scholarship in a variety of philosophical and scientific disciplines will inform our project’s conclusions, and will prepare the ground for a larger project of more extensive theoretical and empirical explorations. Additionally, we will collect empirical neuroscientific data to develop a widened definition of intelligence that includes affect as a critical component.

Using a machine-learning classifier, we are analyzing patterns of activity in the insular cortex (a region important for representing feelings and connecting to other regions involved in intelligent behavior), as measured by fMRI, in research participants who are experiencing a range of feelings. We have hypothesized that differences in classifier performance of distinct feelings across individuals relate to differences in diverse measures of intelligence, thus providing empirical, neurobiological support for the idea that feelings contribute to intelligence.

This work will extend our understanding of intelligence, enrich our conception of humanity, and encourage a fuller flourishing of our social and spiritual dimensions.