Pain and emotional distress are realities that affect us all. Preventing, resolving, and sometimes accepting pain and distress motivates many human endeavors, ranging from spiritual practices to medical interventions. Understanding the brain basis of pain and emotion could transform how we understand these fundamental facets of human life, but currently, there are no human brain measures adequate for determining whether one is angry or sad, whether pain is physical or emotional, or whether one is feeling pain that is intense or mild. In this talk, I describe a series of studies aimed at beginning to address these questions. Combining functional neuroimaging with machine learning techniques, we have developed brain markers capable of indicating the intensity of pain and negative emotion in individual participants with > 90% accuracy, with no prior knowledge of an individual's experience. In addition to their use as markers, such maps can provide insight into the structure of the neurophysiological representations underlying pain and distress. Our findings to date suggest that specific types of aversive experiences are encoded in separate, population-based patterns that are co-localized in similar gross anatomical circuits. These studies are part of a transformational shift in how neuroimaging data is being used, from early 'blob-based' brain-mapping studies to the development of predictive maps with tangible translational potential. They show that as the field progresses, we may be able to map specific types of subjective experience to specific brain circuits. This endeavor enables cross-species mapping of mechanisms, translational work on treatment development, and new ways of understanding and relieving human suffering.