The authors explore the division of labor between the basal ganglia-dopamine (BG-DA) system and the orbitofrontal cortex (OFC) in decision making. They show that a primitive neural network model of the BG-DA system slowly learns to make decisions on the basis of the relative probability of rewards but is not as sensitive to (a) recency or (b) the value of specific rewards. An augmented model that explores BG-OFC interactions is more successful at estimating the true expected value of decisions and is faster at switching behavior when reinforcement contingencies change. In the augmented model, OFC areas exert top-down control on the BG and premotor areas by representing reinforcement magnitudes in working memory. The model successfully captures patterns of behavior resulting from OFC damage in decision making, reversal learning, and devaluation paradigms and makes additional predictions for the underlying source of these deficits.Keywords: decision making, neural network, basal ganglia, orbitofrontal cortex, reinforcement learning What enables humans to make choices that lead to long-term gains, even when having to incur short-term losses? Such decisionmaking skills depend on the processes of action selection (choosing between one of several possible responses) and reinforcement learning (modifying the likelihood of selecting a given response on the basis of experienced consequences). Although all mammals can learn to associate their actions with consequences, humans are particularly advanced in their ability to flexibly modify the relative reinforcement values of alternative choices to select the most adaptive behavior in a particular behavioral, spatial, and temporal context.The behavioral and cognitive neurosciences have identified two neural systems that are involved in such adaptive behavior. On the one hand, the basal ganglia (BG) and the neuromodulator dopamine (DA) are thought to participate in both action selection and reinforcement learning

Contemporary perspectives on age differences in risk taking, informed by advances in developmental neuroscience, have emphasized the need to examine the ways in which emotional and cognitive factors interact to influence decision making. In the present study, a diverse sample of 901 individuals between the ages of 10 and 30 were administered a modified version of the Iowa Gambling Task, which is designed to measure affective decision making. Results indicate that approach behaviors (operationalized as the tendency to play increasingly from the advantageous decks over the course of the task) display an inverted U-shape relation to age, peaking in mid- to late adolescence. In contrast, avoidance behaviors (operationalized as the tendency to refrain from playing from the disadvantageous decks) increase linearly with age, with adults avoiding disadvantageous decks at higher rates than both preadolescents and adolescents. The finding that adolescents, compared to adults, are relatively more approach oriented in response to positive feedback and less avoidant in response to negative feedback is consistent with recent studies of brain development, as well as epidemiological data on various types of risky behavior, and may have important practical implications for the prevention of adolescent risk taking.

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A growing number of imaging studies suggest that alcohol cues, mainly visual, elicit activation in mesocorticolimbic structures. Such findings are consistent with the growing recognition that these structures play an important role in the attribution of incentive salience and the pathophysiology of addiction. The present study investigated whether the presentation of alcohol taste cues can activate brain regions putatively involved in the acquisition and expression of incentive salience. Using functional magnetic resonance imaging, we recorded BOLD activity while delivering alcoholic tastes to 37 heavy drinking but otherwise healthy volunteers. The results yielded a pattern of BOLD activity in mesocorticolimbic structures (ie prefrontal cortex, striatum, ventral tegmental area/substantia nigra) relative to an appetitive control. Further analyses suggested strong connectivity between these structures during cue-elicited urge and demonstrated significant positive correlations with a measure of alcohol use problems (ie the Alcohol Use Disorders Identification Test). Thus, repeated exposure to the taste alcohol in the scanner elicits activation in mesocorticolimbic structures, and this activation is related to measures of urge and severity of alcohol problems.

Although numerous studies provide general support for the importance of genetic factors in the risk for alcohol use disorders (AUDs), candidate gene and genome-wide studies have yet to identify a set of genetic variations that explain a significant portion of the variance in AUDs. One reason is that alcohol-related phenotypes used in genetic studies are typically based on highly heterogeneous diagnostic categories. Therefore, identifying neurobiological phenotypes related to neuroadaptations that drive the development of AUDs is critical for the future success of genetic and epigenetic studies. One such neurobiological phenotype is the degree to which exposure to alcohol taste cues recruits the basal ganglia, prefrontal cortex, and motor areas, all of which have been shown to have a critical role in addictive behaviors in animal studies. To that end, this study was designed to examine whether cue-elicited responses of these structures are associated with AUD severity in a large sample (n=326) using voxelwise and functional connectivity measures. Results suggested that alcohol cues significantly activated dorsal striatum, insula/orbitofrontal cortex, anterior cingulate cortex, and ventral tegmental area. AUD severity was moderately correlated with regions involved in incentive salience such as the nucleus accumbens and amygdala, and stronger relationships with precuneus, insula, and dorsal striatum. The findings indicate that AUDs are related to neuroadaptations in these regions and that these measures may represent important neurobiological phenotypes for subsequent genetic studies.