• Anna C K van Duijvenvoorde, Hilde M Huizenga, Leah H Somerville, Mauricio R Delgado, Alisa Powers, Wouter D Weeda, B J Casey, Elke U Weber, and Bernd Figner.
• University of Amsterdam, Department of Psychology, 1018 XA Amsterdam, The Netherlands, Leiden University, Department of Psychology; Brain & Development Lab, 2333 AK Leiden, The Netherlands, Leiden Institute for Brain and Cognition, 2333 AK Leiden, The Netherlands, b.figner@psych.ru.nl a.c.k.van.duijvenvoorde@fsw.leidenuniv.nl.
• J. Neurosci. 2015 Jan 28; 35 (4): 1549-60.

AbstractAdolescence is often described as a period of increased risk taking relative to both childhood and adulthood. This inflection in risky choice behavior has been attributed to a neurobiological imbalance between earlier developing motivational systems and later developing top-down control regions. Yet few studies have decomposed risky choice to investigate the underlying mechanisms or tracked their differential developmental trajectory. The current study uses a risk-return decomposition to more precisely assess the development of processes underlying risky choice and to link them more directly to specific neural mechanisms. This decomposition specifies the influence of changing risks (outcome variability) and changing returns (expected value) on the choices of children, adolescents, and adults in a dynamic risky choice task, the Columbia Card Task. Behaviorally, risk aversion increased across age groups, with adults uniformly risk averse and adolescents showing substantial individual differences in risk sensitivity, ranging from risk seeking to risk averse. Neurally, we observed an adolescent peak in risk-related activation in the anterior insula and dorsal medial PFC. Return sensitivity, on the other hand, increased monotonically across age groups and was associated with increased activation in the ventral medial PFC and posterior cingulate cortex with age. Our results implicate adolescence as a developmental phase of increased neural risk sensitivity. Importantly, this work shows that using a behaviorally validated decision-making framework allows a precise operationalization of key constructs underlying risky choice that inform the interpretation of results.Copyright © 2015 the authors 0270-6474/15/351549-12$15.00/0.

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