Adolescence represents a neurodevelopmental period characterised by heightened reward drive and weaker inhibitory control that may increase vulnerability to compulsive overconsumption of highly-palatable foods and food addiction. This narrative review aimed to summarise research investigating the presence of food addiction in adolescents and establish the role that impulsivity traits (i.e., reward sensitivity and rash impulsivity), previously linked to substance and behavioural addictions, play in contributing to food addiction in this cohort. It was found that the prevalence of food addiction was typically higher in studies that recruited adolescents who were overweight/obese or from clinical populations. Overall, impulsivity was found to be more consistently associated with food addiction, while the relationships between measures of reward sensitivity and food addiction were mixed. Findings of this review suggest trait impulsivity may contribute to food addiction in adolescents, however, further longitudinal and prospective research is recommended to confirm these findings and to investigate the potential interactive effects of reward sensitivity and rash impulsivity.

The aim of the current research was to identify the extent to which reward sensitivity and impulsivity were related to food addiction.
Forty-five studies, published from 2009 to June 2019, investigating reward sensitivity and/or impulsivity with food addiction as measured by the Yale Food Addiction Scale were reviewed.
Reward sensitivity, as measured by the Sensitivity to Reward (SR) scale, was positively associated with food addiction in two studies, but failed to yield consistent results in other studies when measured with the Behavioral Inhibition/Behavioral Activation Scales. Self-report impulsivity, as measured by the Barratt Impulsiveness Scale (BIS-11), was consistently associated with food addiction, with attentional impulsivity and motor impulsivity the most consistent subscales. Similarly, food addiction was also consistently associated with Negative Urgency, Positive Urgency, and Lack of Perseverance as measured by the UPPS-P Impulsive Behavior Scale. Food addiction was inconsistently associated with disinhibition, as measured by behavioral tasks, indicating food addiction appears more aligned with self-report measures of impulsivity.
Research in this field is dominated by university student, overweight and obese samples. Additional research is required to further tease out these relationships.

According to the dual systems perspective, risk taking peaks during adolescence because activation of an early-maturing socioemotional-incentive processing system amplifies adolescents\' affinity for exciting, pleasurable, and novel activities at a time when a still immature cognitive control system is not yet strong enough to consistently restrain potentially hazardous impulses. We review evidence from both the psychological and neuroimaging literatures that has emerged since 2008, when this perspective was originally articulated. Although there are occasional exceptions to the general trends, studies show that, as predicted, psychological and neural manifestations of reward sensitivity increase between childhood and adolescence, peak sometime during the late teen years, and decline thereafter, whereas psychological and neural reflections of better cognitive control increase gradually and linearly throughout adolescence and into the early 20s. While some forms of real-world risky behavior peak at a later age than predicted, this likely reflects differential opportunities for risk-taking in late adolescence and young adulthood, rather than neurobiological differences that make this age group more reckless. Although it is admittedly an oversimplification, as a heuristic device, the dual systems model provides a far more accurate account of adolescent risk taking than prior models that have attributed adolescent recklessness to cognitive deficiencies.

Eating disorders (EDs) and overweight/obesity (OW/OB) are serious public health concerns that share common neuropsychological features and patterns of disturbed eating. Reward-related decision making as a basic neurocognitive function may trans-diagnostically underlie both pathological overeating and restricted eating. The present meta-analysis synthesizes the evidence from N=82 neuropsychological studies for altered reward-related decision making in all ED subtypes, OW and OB. The overall effect sizes for the differences between currently-ill ED patients and OW/OB people and controls were Hedge\'s g=-0.49 [CI: -0.63; -0.35], and Hedge\'s g=-0.39 [CI: -0.53; -0.25], respectively. Decision making was found to be altered to similar degrees in all ED subtypes and OB. Effect sizes, however, diverged for the different measures of decision making. Adolescents appear to be less affected than adults. When foods were used as rewarding stimuli, decision making was found to be intact in OB. The findings support that altered general reward-related decision making is a salient neuropsychological factor across eating and weight disorders in adulthood.

Despite being considered primarily a mood disorder, major depressive disorder (MDD) is characterized by cognitive and decision making deficits. Recent research has employed computational models of reinforcement learning (RL) to address these deficits. The computational approach has the advantage in making explicit predictions about learning and behavior, specifying the process parameters of RL, differentiating between model-free and model-based RL, and the computational model-based functional magnetic resonance imaging and electroencephalography. With these merits there has been an emerging field of computational psychiatry and here we review specific studies that focused on MDD. Considerable evidence suggests that MDD is associated with impaired brain signals of reward prediction error and expected value (\'wanting\'), decreased reward sensitivity (\'liking\') and/or learning (be it model-free or model-based), etc., although the causality remains unclear. These parameters may serve as valuable intermediate phenotypes of MDD, linking general clinical symptoms to underlying molecular dysfunctions. We believe future computational research at clinical, systems, and cellular/molecular/genetic levels will propel us toward a better understanding of the disease.