How do humans make choices between different types of rewards? Economists have long argued on theoretical grounds that humans typically make these choices as if the values of the options they consider have been mapped to a single common scale for comparison. Neuroimaging studies in humans have recently begun to suggest the existence of a small group of specific brain sites that appear to encode the subjective values of different types of rewards on a neural common scale, almost exactly as predicted by theory. We have conducted a meta analysis using data from thirteen different functional magnetic resonance imaging studies published in recent years and we show that the principle brain area associated with this common representation is a subregion of the ventromedial prefrontal cortex (vmPFC)/orbitofrontal cortex (OFC). The data available today suggest that this common valuation path is a core system that participates in day-to-day decision making suggesting both a neurobiological foundation for standard economic theory and a tool for measuring preferences neurobiologically. Perhaps even more exciting is the possibility that our emerging understanding of the neural mechanisms for valuation and choice may provide fundamental insights into pathological choice behaviors like addiction, obesity and gambling.

The ability of human subjects to choose between disparate kinds of rewards suggests that the neural circuits for valuing different reward types must converge. Economic theory suggests that these convergence points represent the subjective values (SVs) of different reward types on a common scale for comparison. To examine these hypotheses and to map the neural circuits for reward valuation we had food and water-deprived subjects make risky choices for money, food, and water both in and out of a brain scanner. We found that risk preferences across reward types were highly correlated; the level of risk aversion an individual showed when choosing among monetary lotteries predicted their risk aversion toward food and water. We also found that partially distinct neural networks represent the SVs of monetary and food rewards and that these distinct networks showed specific convergence points. The hypothalamic region mainly represented the SV for food, and the posterior cingulate cortex mainly represented the SV for money. In both the ventromedial prefrontal cortex (vmPFC) and striatum there was a common area representing the SV of both reward types, but only the vmPFC significantly represented the SVs of money and food on a common scale appropriate for choice in our data set. A correlation analysis demonstrated interactions across money and food valuation areas and the common areas in the vmPFC and striatum. This may suggest that partially distinct valuation networks for different reward types converge on a unified valuation network, which enables a direct comparison between different reward types and hence guides valuation and choice.

It is well established that neural imaging technology can predict preferences for consumer products. However, the applicability of this method to consumer marketing research remains uncertain, partly because of the expense required. In this article, the authors demonstrate that neural measurements made with a relatively low-cost and widely available measurement method—electroencephalography (EEG)—can predict future choices of consumer products. In the experiment, participants viewed individual consumer products in isolation, without making any actual choices, while their neural activity was measured with EEG. At the end of the experiment, participants were offered choices between pairs of the same products. The authors find that neural activity measured from a midfrontal electrode displays an increase in the N200 component and a weaker theta band power that correlates with a more preferred product. Using recent techniques for relating neural measurements to choice prediction, they demonstrate that these measures predict subsequent choices. Moreover, the accuracy of prediction depends on both the ordinal and cardinal distance of the EEG data; the larger the difference in EEG activity between two products, the better the predictive accuracy.

Multiple high-frequency rTMS of the DLPFC can attenuate nicotine craving.

Rationale and objective-Relapse to drug use in humans can be induced by exposure to drugassociated cues. The ability of drug cues to provoke 'relapse' has been studied in laboratory animals using a reinstatement model in which resumption of drug seeking is assessed after extinction of drug-reinforced responding. In this model, there are no adverse consequences of drug-seeking behavior. However, in humans abstinence is often self-imposed, and relapse episodes likely involve making a choice between the desire for the drug and the negative consequences of pursuing it (a conflict situation). Here, we describe a conflict model of cueinduced relapse in rats that approximate the human condition.Methods-Rats were trained to lever-press for cocaine; infusions were paired with a discrete light-cue. An 'electric barrier' was then introduced by electrifying the floor area near the levers. Responding decreased over days with increasing shock intensities, until the rats did not approach the levers for 3 days. Subsequently, the effect of intermittent non-contingent-light-cue presentations on resumption of lever responding (relapse) was assessed in extinction tests, with the electric barrier remaining activated; during testing lever-presses led to contingent light-cue presentations.Results-Non-contingent cue exposure led to resumption of lever presses during the relapse tests in 14 of the 24 rats. Surprisingly, 24 h later, 11 of the 24 rats resumed lever responding in a subsequent post non-contingent cue test under similar extinction conditions. Large individual differences in responding were observed during both tests.Conclusions-At its current stage of development, the conflict relapse model appears particularly suitable for studying individual differences in cue-induced relapse to cocaine seeking or factors that promote this relapse. KeywordsAnimal models; Drug cues; Cocaine self-administration; Reinstatement; Relapse Cocaine addiction is characterized by high rates of relapse to drug use during abstinence (Mendelson and Mello 1996). In humans, cocaine relapse and craving can be induced by acute exposure to cues previously associated with cocaine use (O'Brien 2005). The ability of cocaine cues to provoke 'relapse' to drug use has been studied in laboratory animals using different variations of a reinstatement model (Shaham et al. 2003). Typically, in these studies laboratory animals are trained to lever-press for drug infusions in the presence of distinct cues (e.g., tone, light, specific odors); then, following extinction of lever responding in the absence of the drug cues, non-reinforced resumption of pressing on the drug-