Adolescence is a developmental period which is often characterized as a time of impulsive and risky choices leading to increased incidence of unintentional injuries and violence, alcohol and drug abuse, unintended pregnancy, and sexually transmitted diseases. Traditional neurobiological and cognitive explanations for such suboptimal decisions have failed to account for nonlinear changes in behaviour observed during adolescence, relative to childhood and adulthood. This chapter provides a biologically plausible conceptualization of the neural mechanisms underlying these nonlinear changes in behaviour, of a heightened sensitivity to incentives while impulse control is still relatively immature during this period. Recent human imaging and animal studies provide a biological basis for this view, suggesting differential development of limbic reward systems relative to top-down control systems during adolescence, relative to childhood and adulthood. Finally, a mathematical model is provided to further distinguish these constructs of impulsivity and risky choices to further characterize developmental and individual differences in suboptimal decisions during this period.
When making decisions between different options, we often consider two basic properties of these options, how risky they are and when they will occur. For example, we may choose to gamble or to wait for a larger reward. Decisions under risk refer to decisions among known probabilistic options, inter-temporal decisions refer to choices between options that will be realized at known future timepoints.
Risky and inter-temporal decisions have been captured theoretically primarily by Ecology and Microeconomics but findings from Behavioral Economics, Psychology and Neuroscience often contradicted theoretical predictions. As a consequence, a wealth of more descriptive models has emerged to explain the findings. A subset of these models has stressed the similarities between risky and inter-temporal decisions. In this chapter we review both core theoretical approaches and empirical findings. We discuss possible explanations for discrepancies and identify key behavioral experiments.
This chapter reviews the extracellular studies of dopamine neurons in behaving animals. Topics covered include motor functions of dopamine neurons, reward functions of dopamine neurons, reward learning functions of dopamine neurons, economic value functions of dopamine neurons, and attention and novelty functions of dopamine neurons.
Emerging evidence suggests that the long-established distinction between habit-based and goal-directed decision-making mechanisms can also be sustained in humans. Although the habit-based system has been extensively studied in humans, the goal-directed system is less well characterized. This review brings to that task the distinction between conceptual and nonconceptual representational mechanisms. Conceptual representations are structured out of semantic constituents (concepts)--the use of which requires an ability to perform some language-like syntactic processing. Decision making--as investigated by neuroscience and psychology--is normally studied in isolation from questions about concepts as studied in philosophy and cognitive psychology. We ask what role concepts play in the "goal-directed" decision-making system. We argue that one fruitful way of studying this system in humans is to investigate the extent to which it deploys conceptual representations.
Reward and punishment have opposite affective value but are both processed by the cingulate cortex. However, it is unclear whether the positive and negative affective values of monetary reward and punishment are processed by separate or common subregions of the cingulate cortex. We performed a functional magnetic resonance imaging study using a free-choice task and compared cingulate activations for different levels of monetary gain and loss. Gain-specific activation (increasing activation for increasing gain, but no activation change in relation to loss) occurred mainly in the anterior part of the anterior cingulate and in the posterior cingulate cortex. Conversely, loss-specific activation (increasing activation for increasing loss, but no activation change in relation to gain) occurred between these areas, in the middle and posterior part of the anterior cingulate. Integrated coding of gain and loss (increasing activation throughout the full range, from biggest loss to biggest gain) occurred in the dorsal part of the anterior cingulate, at the border with the medial prefrontal cortex. Finally, unspecific activation increases to both gains and losses (increasing activation to increasing gains and increasing losses, possibly reflecting attention) occurred in dorsal and middle regions of the cingulate cortex. Together, these results suggest separate and common coding of monetary reward and punishment in distinct subregions of the cingulate cortex. Further meta-analysis suggested that the presently found reward- and punishment-specific areas overlapped with those processing positive and negative emotions, respectively.
