The ability to regulate one?s emotional responses is critical for maintaining emotional health in the face of adverse events that cumulate over the lifespan. Although some emotion regulation abilities are thought to be maintained or even improve in healthy older adults, such beneficial maturation effects are moderated by individual differences in depression and neurocognition that contribute to disability, morbidity, and loss of quality of life into old age. Frontolimbic circuit dysfunction is a hallmark of both younger and older adults with major depressive disorder (MDD), while both activation in and connectivity among components of these circuits predicts treatment response. Such disruptions impact core cognitive processes, including cognitive control and attentional biasing, that influence emotion regulation ability, although it is unknown how their susceptibility to depressive influences varies across the adult lifespan. Moreover, MDD patients are less able to utilize compensatory resources that help older adults cope with adversity, such as social support, in the face of age- associated neurocognitive decline. Given the projected growth of the elderly population in the U.S. and the associated burden on the public health system, it is imperative to develop effective interventions to target regulatory deficits associated with depression in late life and to begin to identify neurocognitive predictors of increasing depressive symptoms. Preliminary evidence from the study team demonstrates that the effectiveness of regulatory strategies such as reappraisal and distraction vary with age and depressive status. However, there is a pressing need for a comprehensive, integrative approach to study emotion regulation strategy use that links brain circuitry integrity, cognitive function, social support, and clinical symptoms, and investigates how these relationships change with age. The central hypothesis of the proposed study is that age, diagnostic status, neurocognitive functioning, and social support will differentially impact reappraisal and distraction efficacy, and that their combined effect on strategy use will predict depressive symptoms at 1 year post-scan. The proposed study is expected to yield new insights in how maturational changes contribute to the conscious ability to reduce negative affect in depressed adults. A total of 200 adults in stratified age groups from 35 to 75 years with and without MDD will undergo structural and task-based functional neuroimaging. We will test age- and diagnosis-specific differences in the success of two different emotion regulation strategies in reducing experimentally induced negative affect, identify brain regions associated with successful use of reappraisal and distraction using structural and functional magnetic resonance imaging, and test emotion regulation as a predictor of future depression symptom severity. Results will be used to better target emotion regulation interventions based on a patient?s age and diagnostic status.

Public Health Relevance

The overall goal of this project is characterize how age-related differences in brain circuitry, neurocognitive performance and social support predict emotion regulation ability in individuals with and without Major Depressive Disorder (MDD). MDD is a costly and burdensome condition that affects a significant proportion of the population across the lifespan, and as the population ages, there is a critical need for a greater understanding of the impact of adult maturation on effective emotion regulation. The findings of these studies are intended to be used in refinement of psychotherapeutic and brain stimulation interventions targeting mood symptoms in MDD that allow greater personalization based on the patient's age.

National Institute of Health (NIH)
National Institute of Mental Health (NIMH)
Research Project (R01)
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Special Emphasis Panel (ZMH1)
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Rowland, Laura Marie
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Duke University
Schools of Medicine
United States
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Powers, John P; LaBar, Kevin S (2018) Regulating emotion through distancing: A taxonomy, neurocognitive model, and supporting meta-analysis. Neurosci Biobehav Rev 96:155-173