Predicting Mental Health in Adolescence: Frontoinsular Circuitry, Emotion in Daily Life, and Risk for Depression.

Abstract

Adolescence is a period of marked change in emotional behavior and related neural circuitry. During this unique stage of development, large-scale brain networks undergo dynamic changes, particularly in corticolimbic circuitry that has been implicated in both healthy and disrupted cognitive control of emotion (1). Coupled with novel psychosocial and physical challenges, these dynamic changes make adolescence a formative period that marks both a window of opportunity and also a window of increased vulnerability. The incidence of psychiatric disorders peaks during adolescence, with mood and anxiety disorders being especially common (2). The onset of these disorders early in life is associated with an increased risk for suicidality, substance abuse, poor academic and social functioning, and chronicity of illness into adulthood (3). Enhancing the prediction of risk to guide diagnosis and facilitate tailored treatment recommendations is therefore vital for optimizing mental health outcomes across the lifespan. Delineating brain-based alterations associated with risk represents a promising approach to improving clinical prediction early in life. Indeed, neural markers that predict clinical outcomes alone or in combination with traditional behavioral measures have increasingly been identified (4). Yet the majority of research on neuromarkers as predictors of clinical status or treatment response has been conducted in adults. Given the substantial reorganization of corticolimbic circuitry, the potential for developmentally specific interactions between neural and environmental factors, and the heightened salience of specific contextual factors during adolescence, such as social interactions or stressful life events, the strongest predictors of risk for mood and anxiety disorders in adolescents may be different from those factors that are most predictive in adults. Combining neural markers with investigations into the temporal dynamics of emotion may be an especially fruitful strategy for clinical prediction during adolescence. Parsing emotions into their simplest elements (e.g., magnitude, duration, and habituation) using ecological momentary assessment (EMA) has shed new light on risk for mood and anxiety disorders in adulthood and facilitated mapping these core aspects of emotion to neural processes (5). Adolescents experience intense and frequent emotions and heightened emotional variability relative to children and adults, highlighting the importance of considering how emotional experiences uniquely unfold over time during this period of development (6). In conjunction with rapid advances in mobile technology, the ubiquity of smart phones in adolescents’ lives makes EMA a particularly suitable methodology to assess interactions between developmental timing and emotion dynamics in daily life.