PROJECT SUMMARY
Our global population is aging faster than ever, promising challenges for healthcare and community wellness.
Affective processes are known to support health and wellbeing across the lifespan. Consequently, a better
understanding of these processes has profound implications for the prevention and treatment of health disorders
(e.g., geriatric depression, cardiovascular disease, dementia) and for policies supporting adults into later life.
Older adults reliably report greater positive emotions, less aroused negative emotions, and greater emotion
regulation efficacy compared to younger adults. These changes have primarily been attributed to age-related
shifts in cognitive processes like attention, memory, motivation, control, and self-regulation. However, older
adults also demonstrate less robust autonomic responding during emotion, lesser sensitivity to bodily sensations
(interoception), and maladaptive gut-based decision-making. Collectively, these findings point to a novel
hypothesis: the Physiological Hypothesis of Emotional Aging (PHEA). PHEA hypothesizes that age-related shifts
in functional activation and connectivity within the allostatic interoceptive brain network (AIN) produce changes
in emotional experience via concurrent changes in interoception and peripheral reactivity. The proposed project
evaluates this hypothesis across three scientific aims leveraging data from sponsor Lindquist’s on-going cohort
study of adults (n = 120, 18-80 years old). Participants in this study complete an in-lab session, one week of
experience sampling, and a functional brain scan yielding measures of physiological reactivity, interoceptive
ability, and emotional reactivity both in-lab and in-daily life. The proposed project is accompanied by 6 specific
training objectives that will help the applicant to build new expertise in the neurobiology of affective aging, cutting-
edge experimental methodologies (e.g., in-scanner acquisition of autonomic physiology, ultrahigh resolution
functional brain scanning), and data analytic techniques (e.g., graph theory). The scientific aims and training
objectives outlined in this proposal will better our understanding of basic mechanisms underlying
healthy and disordered emotional aging; will help scientists, practitioners and policymakers address the
health needs of our aging population; and will support the applicant’s transition into a productive and
independent research scientist.