Reward Systems: Human

Transcription

1 Reward Systems: Human 345 Reward Systems: Human M R Delgado, Rutgers University, Newark, NJ, USA ã 2009 Elsevier Ltd. All rights reserved. Introduction Rewards can be broadly defined as stimuli of positive valence that can influence behavior. They can be manifested through a variety of ways, ranging from appetitive goods to a mere congratulatory pat on the back, and can shape both short-term (e.g., receiving candy after homework) and long-term (e.g., receiving a degree after years of school) goal-directed behavior. Rewards can be observed impacting basic everyday behaviors, such as searching for nutrients, but also more complex social interactions, such as developing trust. The evolutionary function of rewards, therefore, is thought to consist of three primary purposes. First, rewards can induce an overall positive emotional state. Second, the appetitive and hedonic nature of rewards can elicit exploratory or approach behavior. Third, through associative learning, rewards can also serve to reinforce a behavior, or assign a positive value to a previously neutral stimulus or action. In order to exert an influence on behavior, however, rewards must first be detected by the brain. Information about the various properties of a stimulus, such as its valence, magnitude, probability, and time of consumption, must be integrated to form a representation of the reward value or the value of the action necessary to obtain it. Through experience and a highly adaptive neural network, the brain is then able to show preference toward specific rewards, predict when such rewards will become available, and guide behaviors toward a positive outcome. Although such learning about rewards mostly has a positive influence on life, the neural systems responsible for reward-related processing can go awry, in turn leading to abuse of behaviors that lead to rewarding feelings and contributing to many social maladies. Thus, it is imperative to understand the neurobiology underlying the human reward system, specifically how rewards come to be represented in the brain and how humans learn about them. Neuroanatomy of Reward Processing Much of the knowledge about reward systems of the brain come from early theories and a rich animal literature, which highlight some basic ideas about the neural basis of rewards. For example, while information about the physical and chemical attributes of a potential reward is processed by the sensory system (i.e., first through visual, gustatory, olfactory, auditory, or tactile receptors, followed by distributed sensory cortical areas), such information does not initially carry any value to the organism without knowledge of its purpose or effect on behavior. Thus, the coding of a reward representation in the brain is an integrative process that takes into account the physical, but also the subjective, value of a reward with respect to an overall goal. Animal research has been fundamental in delineating a potential neural circuit involved in reward processing and goal-directed behavior, to form the basis of understanding the human reward system. While these elegant animal models and data that derived them are not fully described herein, the neural circuit concept provides an opportunity to highlight the underlying neuroanatomy. A simple version of the neural circuitry that mediates reward processing involves different regions that have multiple inputs and outputs, with the primary components being areas in the prefrontal cortex, basal ganglia, amygdala, and midbrain nuclei that carry the modulatory neurotransmitter dopamine (Figure 1). In the prefrontal cortex, some reward-related responses have been reported in dorsolateral areas. However, a fair amount of research implicates orbitofrontal cortex as the key prefrontal region where sensory and affective information about rewards is integrated. The orbitofrontal cortex (encompassing predominantly Brodmann s areas 10, 11, and 47) receives sensory and visceral motor information and is hypothesized to mediate many functions that involve linking stimuli classified as reward with hedonic experience or affective value. The orbitofrontal cortex can be further subdivided into a medial and lateral portion, both with distinct functionality, as will be discussed later. The orbitofrontal cortex also has strong connections with mesolimbic structures such as the amygdala, located in the medial temporal lobe, and the striatum, the primary input unit of the basal ganglia. The amygdala, a structure classically considered to be involved in aversive learning, has also been shown to participate in other aspects of emotion processing, namely appetitive or reward learning. The striatum, in turn, due to its connectivity with motor structures, has mostly been associated with motor behavior, although more recent research also links the basal ganglia with cognitive and affective processing. The striatum can be subdivided into both anatomically and functionally distinct components: dorsal (consisting of the caudate nucleus and putamen) and ventral (including nucleus accumbens and ventral putamen) striatum. All three regions, orbitofrontal cortex, amygdala, and striatum, are innervated with dopaminergic input from

2 346 Reward Systems: Human Striatum Caudate Putamen a Nucleus accumbens Amygdala Orbitofrontal cortex b Figure 1 Brain regions involved in reward processing in the human brain. (a) Coronal view of the striatum and its components: caudate, putamen, and nucleus accumbens; (b) coronal view of the amygdala; and (c) sagittal view of the orbitofrontal cortex (approximately Brodmann s areas 10, 11, and 46) resting near the orbit of the eyes. c midbrain nuclei, such as the ventral tegmentum area and the substantia nigra. Dopamine, a neurotransmitter previously thought to be involved in representing a reward response, has more recently been linked not with the response to a reward, but instead with providing a teaching signal that helps the brain adjust expectations about the representation of reward value. There are other neural structures that have been implicated in specific aspects of reward processing. Some of these other regions, which are not discussed at length herein, include the ventral pallidum, part of the basal ganglia complex, the thalamus, a relay station from the basal ganglia to diverse areas of the prefrontal cortex, the cingulate gyrus, and the hypothalamus. The basic circuit involved in human reward processing, therefore, involves the orbitofrontal cortex, amygdala, and the striatum, along with modulation by dopamine neurons. Reward Representations in the Human Brain Recent advances in technology have allowed researchers to confirm and extend basic findings from animal studies by looking at the human reward system using neuroimaging and neuropsychological methodologies. By means of similar types of rewards, such as food and liquids, this research has found a tremendous amount of overlap between species in terms of the neurocircuitry involved in reward processing. A reward such as food is known as a primary reinforcer it is innate to an organism, and therefore is processed through similar neural pathways across species. However, due to social and cultural evolution, other types of reinforcers available for humans, chiefly money, are also thought to affect behavior through a similar circuitry. This class of reward, consisting of secondary reinforcers, has developed its reinforcing properties through associations with primary rewards (e.g., money, a secondary reinforcer, allows one to purchase food, a primary reinforcer). Irrespective of the type of reinforcer, human neuroimaging and neuropsychological studies have suggested that regions of the brain such as the orbitofrontal cortex, amygdala, and striatum represent and integrate information about the value of rewards (Figure 2). Such representations are formed at time of reward delivery, when an unknown stimulus (i.e., the rewarding stimulus) is assigned value due to hedonic pleasure or satisfaction it provides. After learning an association between a reinforcer and a particular stimulus or behavior, the reward representation is then transferred to the earliest predictor of

3 Reward Systems: Human 347 Primary reinforcer Secondary reinforcer y = 12 y = 8 cg ins vst Figure 2 Example of primary and secondary reinforcers and similarities in neural systems. Primary reinforcers (e.g., food and liquids) are innate to an organism while secondary reinforcers (e.g., money) gain their reinforcing properties through learning and associations with primary rewards. Despite the differences between primary and secondary reinforcers, there is some overlap in how information about the reward is processed in the brain. For example, activation in the striatum is observed in experimental paradigms where the incentive is either a primary or secondary reinforcer. vst, ventral striatum; cg, cingulate gyrus; ins, insula; y ¼ Talairach coordinate reflecting coronal positioning. Adapted from Gottfried JA, O Doherty J, and Dolan RJ (2003) Encoding predictive reward value in human amygdala and orbitofrontal cortex. Science 301(5636): and from Delgado MR, Frank RH, and Phelps EA (2005) Perceptions of moral character modulate the neural systems of reward during the trust game. Nature Neuroscience 8(11): , with permission. such reward. These new representations of expected reward value are constantly updated and, consequently, behavior is modified to maximize the availability of rewards. Coding Reward Value Once sensory information about a potential reward comes into the brain, a representation of the subjective value must be assigned to aid the dissociation between rewards and nonrewards. This type of representation regarding the affective value of a stimulus is thought to be coded in the orbitofrontal cortex. Activity in orbitofrontal cortex, for example, has been found during functional magnetic resonance imaging (fmri) studies when comparing a stimulus of positive valence (e.g., a pleasant liquid) with a neutral stimulus (e.g., a tasteless solution). Similar results have been reported irrespective of sensory modality, using gustatory, olfactory (i.e., pleasant odors), and tactile (i.e., pleasant touch) stimuli. These findings also extend into more subjective, yet still sensory, reward representations, as coded by the auditory (e.g., pleasant music) and visual (e.g., beautiful faces) domains. A further dissociation within the orbitofrontal cortex has been suggested between the lateral and more medial portions. While lateral orbitofrontal has been linked with representations of negative stimuli (such as unpleasant touch, or loss of money), the medial orbitofrontal cortex has been implicated with processing stimuli with positive valence. Neuroimaging studies have also shown that orbitofrontal cortex codes for representations of monetary rewards, concurrent with studies involving primary reinforcers. Some of these studies involve extensive activation in medial aspects of the prefrontal cortex. Further, patients with lesions in the orbitofrontal cortex demonstrate impairments in forming reward representations and updating the contingencies required to obtain such rewards, as evidenced by poor performance in probabilistic learning experiments that involve contingency reversals. The comparison between an affective and a nonaffective stimulus, however, could also suggest that orbitofrontal activation may be due to the differences in sensory intensity between the stimuli, rather than coding for reward value. Yet, when human study

4 348 Reward Systems: Human participants are presented with olfactory stimuli that differ in terms of valence (positive and negative) and intensity (high and low), activity in the orbitofrontal cortex is found to code for the valence of a stimulus, but not intensity (which is associated with amygdala activation). More support for the idea that the orbitofrontal cortex codes for representations of reward value, rather than just sensory properties of a stimulus, is observed during satiation. A hungry human, for instance, will show activation in orbitofrontal cortex when presented with two different food stimuli. After repeatedly feeding on one of the two stimuli, the activation will decrease for such food item due to satiation, but activation will persist for the other stimulus which still has rewarding value. Hence, the myriad of human data supports the existing animal models and suggests that the orbitofrontal cortex is an important structure involved in representing the value of a stimulus during reward delivery. Expected Reward Value There is more than one way that a reward representation can be coded by the brain. As discussed, a reward such as a food item can be processed in the orbitofrontal cortex. Yet, if an affective neutral stimulus is associated with delivery of the food item, then such stimulus comes to predict the reward. In this case, the neutral stimulus (which is no longer neutral) serves as a conditioned stimulus and provides an expected or predictive representation of reward value. This expectation of reward is created through learning (either via experience or verbal communication) and is observed in day-to-day life (e.g., pizza box predicts food reward for a hungry individual). The assignment of value to the conditioned stimulus that comes to predict reward occurs through an interaction of neural structures previously described, along with dopaminergic modulation. Recordings from nonhuman primate dopamine neurons demonstrate that this class of neurons is sensitive to unexpected rewards, such as a drop of juice. Further, if a neutral stimulus, such as a neutral tone, is paired with the delivery of the juice reward (e.g., a pleasant liquid), dopamine neuron cell firing will cease to occur at the time of reward delivery. Instead, dopamine neurons will fire at the earliest predictor of a reward, in this example the neutral tone. This transfer of activity due to Pavlovian learning mechanisms highlights how reward representations can be transferred to any stimulus that has strong associative connections with a positive outcome or reward. In humans, predictive reward representations can be observed in dopaminergic targets such as the orbitofrontal cortex, ventral striatum, and amygdala. Recent fmri studies have suggested that the human orbitofrontal cortex codes not only for reward-specific representations, but also for conditioned stimuli that predict reward. Representations of expected reward value in the orbitofrontal cortex may be formed in conjunction with the ventral striatum and the amygdala (Figure 3). Activity in both of these structures, for example, has also been found during appetitive conditioning paradigms involving primary reinforcers such as pleasant liquids and odors. Further, patients with unilateral medial temporal lobe lesions (which include amygdala) are impaired in conditioned preference learning, where patterns are associated with food rewards. Unlike the orbitofrontal cortex, however, the ventral striatum and amygdala have been associated with coding the representation of reward value during the expectation or predictive phase of reward processing, rather than during actual reward delivery. This suggests an important role for these structures in learning about rewards and making predictions about potential rewards. Representations of predicted reward can be observed in the human orbitofrontal cortex and ventral striatum with both primary (e.g., food) and secondary (e.g., money) reinforcers. Anticipation of monetary rewards, for example, leads to activation in the ventral striatum, since the stimulus inducing the anticipation carries a predictive representation of reward. Interestingly, the overlap between types of reinforcers is not observed in the amygdala, as conditioned stimuli that predict a monetary reward (i.e., a secondary reinforcer) do not usually yield amygdala activation. This potential discrepancy might be because of intensity differences between primary and secondary reinforcers, though limitations in neuroimaging methodology cannot be discounted. It is useful to examine neuropsychological investigations in conjunction with neuroimaging data, which do not imply causality. For example, one experiment found that patients with amygdala lesions did not show anticipatory responses to potential monetary wins and losses in a gambling game (i.e., the Iowa Gambling Task), although the complexities of such a task make it difficult to interpret the deficit as a failure to show predictive representations of value. Adjusting Expected Values and Actions That Lead to Reward The brain has a representation of reward value that, through learning, shifts to the earliest predictor of the reward. The conditioned stimulus then provides an expectation of reward. However, the brain must adjust the representation of the expected reward signal if a reward fails to occur (e.g., opening a pizza box but finding it empty). This is especially the case when a reward is contingent on a behavior, as an organism

5 Reward Systems: Human 349 y = 42 OFC 1 BOLD response CS 1 CS 2 a y = 6 4 Amygdala BOLD response 0 4 CS 1 CS 2 b Figure 3 Representations of expected reward value in the orbitofrontal cortex and amygdala during appetitive conditioning experiment. Two predictive stimuli are presented and one stimulus (conditioned stimulus 1, CS 1; orange color) is satiated midway through experiment, while the other stimulus (CS 2; light blue color) is not. Graphs represent differential blood oxygenation level-dependent (BOLD) responses (postsatiation break minus presatiation). (a) Activation of orbitofrontal cortex (OFC) to the devalued conditioned stimulus (CS 1) was decreased compared to the nondevalued conditioned stimulus (CS 2), suggesting that representations of expected reward value are constantly changing with motivational state. (b) The same pattern of results is observed in the amygdala. BOD, blood-oxygen level dependent. Adapted from Gottfried JA, O Doherty J, and Dolan RJ (2003) Encoding predictive reward value in human amygdala and orbitofrontal cortex. Science 301(5636): , with permission. has to quickly adapt and update action representations that will lead to rewards. Dopamine neurons provide an illustration of how the nonhuman primate brain might signal a potential error in prediction. The role of dopamine in rewardrelated learning is thought to be a teaching signal that relays information about the representation of rewards. As previously discussed, these cells typically show learning-related activity demonstrated by a transfer in neural firing from the unexpected reward to the predictive cue. Notably, dopamine cells will also show a depression in neuronal firing when an expected reward is omitted. By signaling the presence of an unexpected reward and the omission of a predicted reward, dopamine is able to provide a reward prediction error signal that aids in goal-directed behavior. In humans, the prediction error signal is observed in dopaminergic targets, but primarily in the striatum. Different portions of the striatum have shown evidence of coding for errors in prediction in neuroimaging studies. Using primary reinforcers, activation in the ventral putamen has been correlated with a prediction error signal. Using secondary reinforcers, the majority of studies suggest that the nucleus accumbens may be more involved. Although this separation within the striatum between primary and secondary reinforcers has been observed in some studies, it is not uniform and it may merely reflect a difference in type of paradigms or even particular properties of the reinforcer. A more clear dissociation within the striatum is observed between dorsal and ventral striatum. As

6 350 Reward Systems: Human previously described, the ventral striatum is involved in representations of expected reward, highlighted by activation to a predictive conditioned stimulus during appetitive learning paradigms. The dorsal striatum, in contrast, is important for specifically coding the representation of a reward which is contingent on behavior. This is illustrated in conditioning paradigms, where visual cues predict the delivery of rewards either noncontingently (Pavlovian conditioning) or contingently (instrumental conditioning) on choice behavior. Activation of the caudate nucleus, part of the dorsal striatum, is observed only during instrumental conditioning. Thus, the dorsal striatum, particularly the caudate nucleus, appears to be involved in the coding of action specific representations of reward value. Modulation by Properties of Reward Once reward-related information is detected by the brain and a representation is formed, such representation is constantly updated to reflect changes in the current value of the reward. This updating depends on the current state of the organism and the properties of the rewarding stimulus. For example, as previously discussed, a food reward will have a representation of value for a hungry individual. This representation of reward value, however, changes as the individual becomes satiated, suggesting that the motivational state of an organism can temporarily affect representations of reward and the neural circuitry involved in reward processing. Additionally, reward representations in the brain also take into consideration the properties of a reward, such as valence, magnitude, probability, and time of consumption. Valence Valence refers to the positive or negative quality attributed to a stimulus. For example, glucose water is a pleasant liquid solution considered to have positive qualities, while salty water is an unpleasant solution with negative qualities. Similarly, winning money and receiving positive feedback (e.g., pat on the back) are pleasant stimuli, while losing money and receiving negative feedback (e.g., reprimand) are unpleasant stimuli. Interestingly, the interaction between the valence of a stimulus and its reward value is not as clear-cut as the preceding examples suggest, leaving open questions for future investigations. For instance, although avoidance of a negative outcome such as losing money is generally a positive outcome, can it be considered a reward? What about receiving a small reward, a positive outcome, when a preferred larger one was available (i.e., regret)? As previously mentioned, the representation of the value of a reward during delivery of such reward is coded in the orbitofrontal cortex. However, human neuroimaging studies also suggest that the human dorsal striatum is active during reward delivery when it is contingent on a behavior. Unlike more medial portions of the orbitofrontal cortex, the dorsal striatum does not create a representation of the reward value per se. Instead, it codes the differential activity between stimuli of positive and negative valence during trial-and-error learning, maintaining a representation of the outcome of goal-directed actions to help guide future behavior. Magnitude and Probability of Reward An affective stimulus can vary in terms of valence, but also magnitude. Although magnitude could also refer to the intensity of a stimulus, the primary definition refers to the amount or quantity of a reward. Changes in reward magnitude (e.g., increases in the expectation of reward or reward delivery) evoke predictive reward representations in orbitofrontal cortex and ventral striatum that grade parametrically according to increases in value (i.e., higher magnitudes, Figure 4). Besides magnitude, an important component of the expected reward value representation is the probability of a potential reward delivery. A stimulus that is paired with a reward elicits a prediction of reward delivery. At times, however, the probability of receiving a reward is probabilistic. That is, there is a chance a reward will not be delivered. This is observed in everyday behavior, from extremes such as playing the lottery to hoping there is one more slice of pizza in the box. The probabilistic nature of reward is an important component of behavior, since if every attainable reward was predictable there would be no evolutionary need to explore or show approach behavior. Thus, all regions of the basic reward circuit are influenced by reward probability, as evidenced by expected reward representations parametrically varying in terms of how uncertain they are in regions such as the orbitofrontal cortex and striatum. For example, the striatum is found to be more activated during unpredictable, compared to predictable, delivery of primary rewards. More recently, the medial prefrontal cortex has been implicated in integrating information about the potential magnitude and probability of a reward, forming a representation of the expected value of a reward. Time Finally, a representation of reward value can be influenced by the time the reward is expected to be delivered. A reward that is available immediately is thought

7 Reward Systems: Human 351 a b $0.00 +$0.20 +$1.00 +$5.00 Figure 4 Reward representations in the striatum are sensitive to magnitude differences. (a) Ventral striatum activation during anticipation of different magnitudes of monetary rewards. (b) Levels of blood oxygenation level-dependent response (represented by percent signal change) in ventral striatum varied based on different cues that represented monetary rewards of different magnitudes (ranging from $0 to $5.00). Adapted from Knutson B, Adams CM, Fong G W, et al. (2001) Anticipation of increasing monetary reward selectively recruits nucleus accumbens. Journal of Neuroscience 21(16): RC159, with permission. Copyright 2001 by the Society for Neuroscience. % Signal change ( SEM) ** to be more valuable than a reward available only in the future (e.g., a slice of pizza now vs. a week later). Recent investigations have suggested that the ventral striatum is more involved with processing immediate rewards, while prefrontal cortex regions are linked to evaluation of long-term rewards. This is supported by neuropsychological work with frontal-lesioned patients, who discount future consequences of their actions in a gambling game (i.e., larger losses) in deference to immediate rewards. Yet, more research is needed to fully understand the influence of time on the neural mechanisms of human reward processing. Modulation of Reward System by Cultural and Social Factors Together with findings from animal studies, recent research with humans has helped delineate a basic circuit involved in processing simple rewards such as food. Yet, human beings are much more complex and form reward representations through experience with social and cultural rewards which affect behavior. New fields of study are currently being developed to probe these more complex behaviors, which necessitate the merging of disciplines, as illustrated by social neuroscience and neuroeconomics. For instance, in humans, representations of reward value are also subjective; some like Coke and others like Pepsi, while some don t like soda at all. Studies have suggested that subjective preference for cultural rewards such as sugar-based liquids and even types of cars is represented in medial orbitofrontal areas. Interestingly, the expected representation of social rewards seems to involve primarily the striatum. It is possible that the striatum, particularly the dorsal striatum, is more involved in processing social rewards because of the link between human interaction and action. Social rewards such as love, humor, and cooperation all yield positive feelings, and presentation of a stimulus that predicts such hedonic feelings (e.g., a picture of a loved one) leads to activation in the striatum. These findings are strengthened by studies involving social and economic interactions, where an individual can either benefit or suffer from an interaction with another person. For example, in a trust game whereby reputations are built through experience, activation of the dorsal striatum is observed coding for a representation of expected reward value when a positive, trustworthy interaction occurs. To demonstrate how complex human nature is, however, such a signal can be influenced by previous information or biases that individuals have, rather than be driven by the presence or absence of rewards. Finally, the complexities of the human reward system are also observed during abuse of rewards, as displayed by drug addicts, for example. The lure of drugs leads to exaggerated representations of expected reward values (e.g., craving) that can hijack the brain s reward system. The influence of drugs on behavior will lead an addict to bypass natural rewards in favor of drugs, eventually deteriorating quality of life for the addict and those around him. Summary Rewards are incentives that influence behavior. The potential rewarding properties of a stimulus and its

8 352 Reward Systems: Human effect on goal-directed behavior are coded in the human brain by an intrinsic reward circuit consisting of orbitofrontal cortex, striatum, amygdala, and dopaminergic modulation. Attributes such as a stimulus valence (positive or negative) are represented in these structures. The orbitofrontal cortex is chieflyinvolved in assigning value to a stimulus during reward delivery. The striatum and the amygdala are involved in forming representations of the expected reward value of a stimulus, and constantly update such representations to reflect the current motivational state or changes in reward properties (e.g., probability and time of occurrence). The striatum, particularly the dorsal components, is also involved in forming action-specific representations of reward, monitoring the outcome of actions to maximize available rewards. The human reward circuit processes both simple primary (e.g., food) and secondary (e.g., money) rewards. Current research aims to understand how the basic reward circuitry processes more complex cultural and social rewards, as displayed by subjective preference (e.g., different types of beverages) and human interactions (e.g., trust). Explorations of the simple and complex intricacies of the neural basis underlying human reward processing afford an opportunity to further our knowledge regarding goal-directed behavior, leading to appreciation and treatment of many of societal maladies associated with abuse of the reward system. See also: Appetitive Systems: Amygdala and Striatum; Connectivity of Primate Reward Centers; Neuropsychology of Primate Reward Processes; Orbitofrontal Cortex: Visual Functions; Prefrontal Contributions to Reward Encoding; Reinforcement Models; Reward and Learning; Reward Processing: Human Imaging; Social Emotion: Neuroimaging. Further Reading Anderson AK, Christoff K, Stappen I, et al. (2003) Dissociated neural representations of intensity and valence in human olfaction. Nature Neuroscience 6(2): Bechara A, Damasio H, Damasio AR, et al. (1999) Different contributions of the human amygdala and ventromedial prefrontal cortex to decision-making. Journal of Neuroscience 19(13): Berns GS, McClure SM, Pagnoni G, et al. (2001) Predictability modulates human brain response to reward. Journal of Neuroscience 21(8): Breiter HC, Aharon I, Kahneman D, et al. (2001) Functional imaging of neural responses to expectancy and experience of monetary gains and losses. Neuron 30(2): Cox SM, Andrade A, and Johnsrude IS (2005) Learning to like: A role for human orbitofrontal cortex in conditioned reward. Journal of Neuroscience 25(10): Delgado MR, Frank RH, and Phelps EA (2005) Perceptions of moral character modulate the neural systems of reward during the trust game. Nature Neuroscience 8(11): Gottfried JA, O Doherty J, and Dolan RJ (2003) Encoding predictive reward value in human amygdala and orbitofrontal cortex. Science 301(5636): Johnsrude IS, Owen AM, White NM, et al. (2000) Impaired preference conditioning after anterior temporal lobe resection in humans. Journal of Neuroscience 20(7): King-Casas B, Tomlin D, Anen C, et al. (2005) Getting to know you: Reputation and trust in a two-person economic exchange. Science 308(5718): Knutson B and Cooper JC (2005) Functional magnetic resonance imaging of reward prediction. Current Opinion in Neurology 18(4): Knutson B, Adams CM, Fong GW, et al. (2001) Anticipation of increasing monetary reward selectively recruits nucleus accumbens. Journal of Neuroscience 21(16): RC159. Kringelbach ML (2005) The human orbitofrontal cortex: Linking reward to hedonic experience. Nature Reviews Neuroscience 6 (9): McClure SM, Laibson DI, Loewenstein G, et al. (2004) Separate neural systems value immediate & delayed monetary rewards. Science 306(5695): McClure SM, Li J, Tomlin D, et al. (2004) Neural correlates of behavioral preference for culturally familiar drinks. Neuron 44(2): Montague PR, King-Casas B, and Cohen JD (2006) Imaging valuation models in human choice. Annual Review of Neuroscience 29: O Doherty JP (2004) Reward representations and reward-related learning in the human brain: Insights from neuroimaging. Current Opinion in Neurobiology 14(6): O Doherty J, Dayan P, Schultz J, et al. (2004) Dissociable roles of ventral and dorsal striatum in instrumental conditioning. Science 304(5669): Rolls ET (1999) The Brain and Emotion. New York: Oxford University Press. Schultz W (2000) Multiple reward signals in the brain. Nature Reviews Neuroscience 1(3): Small DM, Gregory MD, Mak YE, et al. (2003) Dissociation of neural representation of intensity and affective valuation in human gustation. Neuron 39(4): Tricomi EM, Delgado MR, and Fiez JA (2004) Modulation of caudate activity by action contingency. Neuron 41(2):