A Predictive Reinforcement Model of Dopamine Neurons for Learning Approach Behavior

A neural network model of how dopamine and prefrontal cortex activity guides short- and long-term information processing within the cortico-striatal circuits during reward-related learning of approach behavior is proposed. The model predicts two types of reward-related neuronal responses generated during learning: (1) cell activity signaling errors in the prediction of the expected time of reward delivery and (2) neural activations coding for errors in the prediction of the amount and type of reward or stimulus expectancies. The former type of signal is consistent with the responses of dopaminergic neurons, while the latter signal is consistent with reward expectancy responses reported in the prefrontal cortex. It is shown that a neural network architecture that satisfies the design principles of the adaptive resonance theory of Carpenter and Grossberg (1987) can account for the dopamine responses to novelty, generalization, and discrimination of appetitive and aversive stimuli. These hypotheses are scrutinized via simulations of the model in relation to the delivery of free food outside a task, the timed contingent delivery of appetitive and aversive stimuli, and an asymmetric, instructed delay response task.     

Influence of Dopaminergically Mediated Reward on Somatosensory Decision-Making

Reward-related dopaminergic influences on learning and overt behaviour are well established, but any influence on sensory decision-making is largely unknown. We used functional magnetic resonance imaging (fMRI) while participants judged electric somatosensory stimuli on one hand or other, before being rewarded for correct performance at trial end via a visual signal, at one of four anticipated financial levels. Prior to the procedure, participants received either placebo (saline), a dopamine agonist (levodopa), or an antagonist (haloperidol). Principal findings: higher anticipated reward improved tactile decisions. Visually signalled reward reactivated primary somatosensory cortex for the judged hand, more strongly for higher reward. After receiving a higher reward on one trial, somatosensory activations and decisions were enhanced on the next trial. These behavioural and neural effects were all enhanced by levodopa and attenuated by haloperidol, indicating dopaminergic dependency. Dopaminergic reward-related influences extend even to early somatosensory cortex and sensory decision-making.     

Pavlovian reward prediction and receipt in schizophrenia: relationship to anhedonia

Reward processing abnormalities have been implicated in the pathophysiology of negative symptoms such as anhedonia and avolition in schizophrenia. However, studies examining neural responses to reward anticipation and receipt have largely relied on instrumental tasks, which may confound reward processing abnormalities with deficits in response selection and execution. 25 chronic, medicated outpatients with schizophrenia and 20 healthy controls underwent functional magnetic resonance imaging using a pavlovian reward prediction paradigm with no response requirements. Subjects passively viewed cues that predicted subsequent receipt of monetary reward or non-reward, and blood-oxygen-level-dependent signal was measured at the time of cue presentation and receipt. At the group level, neural responses to both reward anticipation and receipt were largely similar between groups. At the time of cue presentation, striatal anticipatory responses did not differ between patients and controls. Right anterior insula demonstrated greater activation for nonreward than reward cues in controls, and for reward than nonreward cues in patients. At the time of receipt, robust responses to receipt of reward vs. nonreward were seen in striatum, midbrain, and frontal cortex in both groups. Furthermore, both groups demonstrated responses to unexpected versus expected outcomes in cortical areas including bilateral dorsolateral prefrontal cortex. Individual difference analyses in patients revealed an association between physical anhedonia and activity in ventral striatum and ventromedial prefrontal cortex during anticipation of reward, in which greater anhedonia severity was associated with reduced activation to money versus no-money cues. In ventromedial prefrontal cortex, this relationship held among both controls and patients, suggesting a relationship between anticipatory activity and anhedonia irrespective of diagnosis. These findings suggest that in the absence of response requirements, brain responses to reward receipt are largely intact in medicated individuals with chronic schizophrenia, while reward anticipation responses in left ventral striatum are reduced in those patients with greater anhedonia severity.     

A functional difference in information processing between orbitofrontal cortex and ventral striatum during decision-making behaviour

Both orbitofrontal cortex (OFC) and ventral striatum (vStr) have been identified as key structures that represent information about value in decision-making tasks. However, the dynamics of how this information is processed are not yet understood. We recorded ensembles of cells from OFC and vStr in rats engaged in the spatial adjusting delay-discounting task, a decision-making task that involves a trade-off between delay to and magnitude of reward. Ventral striatal neural activity signalled information about reward before the rat''s decision, whereas such reward-related signals were absent in OFC until after the animal had committed to its decision. These data support models in which vStr is directly involved in action selection, but OFC processes decision-related information afterwards that can be used to compare the predicted and actual consequences of behaviour.     

Dissociable reward and timing signals in human midbrain and ventral striatum

Reward prediction error (RPE) signals are central to current models of reward-learning. Temporal difference (TD) learning models posit that these signals should be modulated by predictions, not only of magnitude but also timing of reward. Here we show that BOLD activity in the VTA conforms to such TD predictions: responses to unexpected rewards are modulated by a temporal hazard function and activity between a predictive stimulus and reward is depressed in proportion to predicted reward. By contrast, BOLD activity in ventral striatum (VS) does not reflect a TD RPE, but instead encodes a signal on the variable relevant for behavior, here timing but not magnitude of reward. The results have important implications for dopaminergic models of cortico-striatal learning and suggest a modification of the conventional view that VS BOLD necessarily reflects inputs from dopaminergic VTA neurons signaling an RPE.     

Early Effects of Reward Anticipation Are Modulated by Dopaminergic Stimulation

The abilities to predict future rewards and assess the value of reward delivery are crucial aspects of adaptive behavior. While the mesolimbic system, including dopaminergic midbrain, ventral striatum and prefrontal cortex have long been associated with reward processing, recent studies also indicate a prominent role of early visual brain regions. However, the precise underlying neural mechanisms still remain unclear. To address this issue, we presented participants with visual cues predicting rewards of high and low magnitudes and probability (2×2 factorial design), while neural activity was scanned using magnetoencephalography. Importantly, one group of participants received 150 mg of the dopamine precursor levodopa prior to the experiment, while another group received a placebo. For the placebo group, neural signals of reward probability (but not magnitude) emerged at ∼100 ms after cue presentation at occipital sensors in the event-related magnetic fields. Importantly, these probability signals were absent in the levodopa group indicating a close link. Moreover, levodopa administration reduced oscillatory power in the high (20–30 Hz) and low (13–20 Hz) beta band during both reward anticipation and delivery. Taken together, our findings indicate that visual brain regions are involved in coding prospective reward probability but not magnitude and that these effects are modulated by dopamine.     

Reward representations and reward-related learning in the human brain: insights from neuroimaging

This review outlines recent findings from human neuroimaging concerning the role of a highly interconnected network of brain areas including orbital and medial prefrontal cortex, amygdala, striatum and dopaminergic mid-brain in reward processing. Distinct reward-related functions can be attributed to different components of this network. Orbitofrontal cortex is involved in coding stimulus reward value and in concert with the amygdala and ventral striatum is implicated in representing predicted future reward. Such representations can be used to guide action selection for reward, a process that depends, at least in part, on orbital and medial prefrontal cortex as well as dorsal striatum.     

Expectations and outcomes: decision-making in the primate brain

Success in a constantly changing environment requires that decision-making strategies be updated as reward contingencies change. How this is accomplished by the nervous system has, until recently, remained a profound mystery. New studies coupling economic theory with neurophysiological techniques have revealed the explicit representation of behavioral value. Specifically, when fluid reinforcement is paired with visually-guided eye movements, neurons in parietal cortex, prefrontal cortex, the basal ganglia, and superior colliculus—all nodes in a network linking visual stimulation with the generation of oculomotor behavior—encode the expected value of targets lying within their response fields. Other brain areas have been implicated in the processing of reward-related information in the abstract: midbrain dopaminergic neurons, for instance, signal an error in reward prediction. Still other brain areas link information about reward to the selection and performance of specific actions in order for behavior to adapt to changing environmental exigencies. Neurons in posterior cingulate cortex have been shown to carry signals related to both reward outcomes and oculomotor behavior, suggesting that they participate in updating estimates of orienting value.     

Single units in the pigeon brain integrate reward amount and time-to-reward in an impulsive choice task

BACKGROUND: Animals prefer small over large rewards when the delays preceding large rewards exceed an individual tolerance limit. Such impulsive choice behavior occurs even in situations in which alternative strategies would yield more optimal outcomes. Behavioral research has shown that an animal's choice is guided by the alternative rewards' subjective values, which are a function of reward amount and time-to-reward. Despite increasing knowledge about the pharmacology and anatomy underlying impulsivity, it is still unknown how the brain combines reward amount and time-to-reward information to represent subjective reward value. RESULTS: We trained pigeons to choose between small, immediate rewards and large rewards delivered after gradually increasing delays. Single-cell recordings in the avian Nidopallium caudolaterale, the presumed functional analog of the mammalian prefrontal cortex, revealed that neural delay activation decreased with increasing delay length but also covaried with the expected reward amount. This integrated neural response was modulated by reward amount and delay, as predicted by a hyperbolical equation, of subjective reward value derived from behavioral studies. Furthermore, the neural activation pattern reflected the current reward preference and the time point of the shift from large to small rewards. CONCLUSIONS: The reported activity was modulated by the temporal devaluation of the anticipated reward in addition to reward amount. Our findings contribute to the understanding of neuropathologies such as drug addiction, pathological gambling, frontal lobe syndrome, and attention-deficit disorders, which are characterized by inappropriate temporal discounting and increased impulsiveness.     

Timing in reward and decision processes

Sensitivity to time, including the time of reward, guides the behaviour of all organisms. Recent research suggests that all major reward structures of the brain process the time of reward occurrence, including midbrain dopamine neurons, striatum, frontal cortex and amygdala. Neuronal reward responses in dopamine neurons, striatum and frontal cortex show temporal discounting of reward value. The prediction error signal of dopamine neurons includes the predicted time of rewards. Neurons in the striatum, frontal cortex and amygdala show responses to reward delivery and activities anticipating rewards that are sensitive to the predicted time of reward and the instantaneous reward probability. Together these data suggest that internal timing processes have several well characterized effects on neuronal reward processing.     

Asymmetric and adaptive reward coding via normalized reinforcement learning

Learning is widely modeled in psychology, neuroscience, and computer science by prediction error-guided reinforcement learning (RL) algorithms. While standard RL assumes linear reward functions, reward-related neural activity is a saturating, nonlinear function of reward; however, the computational and behavioral implications of nonlinear RL are unknown. Here, we show that nonlinear RL incorporating the canonical divisive normalization computation introduces an intrinsic and tunable asymmetry in prediction error coding. At the behavioral level, this asymmetry explains empirical variability in risk preferences typically attributed to asymmetric learning rates. At the neural level, diversity in asymmetries provides a computational mechanism for recently proposed theories of distributional RL, allowing the brain to learn the full probability distribution of future rewards. This behavioral and computational flexibility argues for an incorporation of biologically valid value functions in computational models of learning and decision-making.     

Activation of VTA GABA neurons disrupts reward consumption

The activity of ventral tegmental area (VTA) dopamine (DA) neurons promotes behavioral responses to rewards and environmental stimuli that predict them. VTA GABA inputs synapse directly onto DA neurons and may regulate DA neuronal activity to alter reward-related behaviors; however, the functional consequences of selective activation of VTA GABA neurons remains unknown. Here, we show that in?vivo optogenetic activation of VTA GABA neurons disrupts reward consummatory behavior but not conditioned anticipatory behavior in response to reward-predictive cues. In addition, direct activation of VTA GABA projections to the nucleus accumbens (NAc) resulted in detectable GABA release but did not alter reward consumption. Furthermore, optogenetic stimulation of VTA GABA neurons directly suppressed the activity and excitability of neighboring DA neurons as well as the release of DA in the NAc, suggesting that the dynamic interplay between VTA DA and GABA neurons can control the initiation and termination of reward-related behaviors.     

Face perception is modulated by sexual preference

Face perception is mediated by a distributed neural system in the human brain . The response to faces is modulated by cognitive factors such as attention, visual imagery, and emotion ; however, the effects of gender and sexual orientation are currently unknown. We used fMRI to test whether subjects would respond more to their sexually preferred faces and predicted such modulation in the reward circuitry. Forty heterosexual and homosexual men and women viewed photographs of male and female faces and assessed facial attractiveness. Regardless of their gender and sexual orientation, all subjects similarly rated the attractiveness of both male and female faces. Within multiple, bilateral face-selective regions in the visual cortex, limbic system, and prefrontal cortex, similar patterns of activation were found in all subjects in response to both male and female faces. Consistent with our hypothesis, we found a significant interaction between stimulus gender and the sexual preference of the subject in the thalamus and medial orbitofrontal cortex, where heterosexual men and homosexual women responded more to female faces and heterosexual women and homosexual men responded more to male faces. Our findings suggest that sexual preference modulates face-evoked activation in the reward circuitry.     

Stimulus-dependent adjustment of reward prediction error in the midbrain

Previous reports have described that neural activities in midbrain dopamine areas are sensitive to unexpected reward delivery and omission. These activities are correlated with reward prediction error in reinforcement learning models, the difference between predicted reward values and the obtained reward outcome. These findings suggest that the reward prediction error signal in the brain updates reward prediction through stimulus-reward experiences. It remains unknown, however, how sensory processing of reward-predicting stimuli contributes to the computation of reward prediction error. To elucidate this issue, we examined the relation between stimulus discriminability of the reward-predicting stimuli and the reward prediction error signal in the brain using functional magnetic resonance imaging (fMRI). Before main experiments, subjects learned an association between the orientation of a perceptually salient (high-contrast) Gabor patch and a juice reward. The subjects were then presented with lower-contrast Gabor patch stimuli to predict a reward. We calculated the correlation between fMRI signals and reward prediction error in two reinforcement learning models: a model including the modulation of reward prediction by stimulus discriminability and a model excluding this modulation. Results showed that fMRI signals in the midbrain are more highly correlated with reward prediction error in the model that includes stimulus discriminability than in the model that excludes stimulus discriminability. No regions showed higher correlation with the model that excludes stimulus discriminability. Moreover, results show that the difference in correlation between the two models was significant from the first session of the experiment, suggesting that the reward computation in the midbrain was modulated based on stimulus discriminability before learning a new contingency between perceptually ambiguous stimuli and a reward. These results suggest that the human reward system can incorporate the level of the stimulus discriminability flexibly into reward computations by modulating previously acquired reward values for a typical stimulus.     

Predicting the stream of consciousness from activity in human visual cortex

Can the rapid stream of conscious experience be predicted from brain activity alone? Recently, spatial patterns of activity in visual cortex have been successfully used to predict feature-specific stimulus representations for both visible and invisible stimuli. However, because these studies examined only the prediction of static and unchanging perceptual states during extended periods of stimulation, it remains unclear whether activity in early visual cortex can also predict the rapidly and spontaneously changing stream of consciousness. Here, we used binocular rivalry to induce frequent spontaneous and stochastic changes in conscious experience without any corresponding changes in sensory stimulation, while measuring brain activity with fMRI. Using information that was present in the multivariate pattern of responses to stimulus features, we could accurately predict, and therefore track, participants' conscious experience from the fMRI signal alone while it underwent many spontaneous changes. Prediction in primary visual cortex primarily reflected eye-based signals, whereas prediction in higher areas reflected the color of the percept. Furthermore, accurate prediction during binocular rivalry could be established with signals recorded during stable monocular viewing, showing that prediction generalized across viewing conditions and did not require or rely on motor responses. It is therefore possible to predict the dynamically changing time course of subjective experience with only brain activity.     

Relationship between Personality Traits and Brain Reward Responses when Playing on a Team

Cooperation is an integral part of human social life and we often build teams to achieve certain goals. However, very little is currently understood about emotions with regard to cooperation. Here, we investigated the impact of social context (playing alone versus playing on a team) on emotions while winning or losing a game. We hypothesized that activity in the reward network is modulated by the social context and that personality characteristics might impact team play. We conducted an event-related functional magnetic resonance imaging experiment that involved a simple game of dice. In the team condition, the participant played with a partner against another two-person team. In the single-player condition, the participant played alone against another player. Our results revealed that reward processing in the right amygdala was modulated by the social context. The main effect of outcome (gains versus losses) was associated with increased responses in the reward network. We also found that differences in the reward-related neural response due to social context were associated with specific personality traits. When playing on a team, increased activity in the amygdala during winning was a unique function of openness, while decreased activity in the ventromedial prefrontal cortex and ventral striatum during losing was associated with extraversion and conscientiousness, respectively. In conclusion, we provide evidence that working on a team influences the affective value of a negative outcome by attenuating the negative response associated with it in the amygdala. Our results also show that brain reward responses in a social context are affected by personality traits related to teamwork.     

Relief as a reward: hedonic and neural responses to safety from pain

Relief fits the definition of a reward. Unlike other reward types the pleasantness of relief depends on the violation of a negative expectation, yet this has not been investigated using neuroimaging approaches. We hypothesized that the degree of negative expectation depends on state (dread) and trait (pessimism) sensitivity. Of the brain regions that are involved in mediating pleasure, the nucleus accumbens also signals unexpected reward and positive prediction error. We hypothesized that accumbens activity reflects the level of negative expectation and subsequent pleasant relief. Using fMRI and two purpose-made tasks, we compared hedonic and BOLD responses to relief with responses during an appetitive reward task in 18 healthy volunteers. We expected some similarities in task responses, reflecting common neural substrates implicated across reward types. However, we also hypothesized that relief responses would differ from appetitive rewards in the nucleus accumbens, since only relief pleasantness depends on negative expectations. The results confirmed these hypotheses. Relief and appetitive reward task activity converged in the ventromedial prefrontal cortex, which also correlated with appetitive reward pleasantness ratings. In contrast, dread and pessimism scores correlated with relief but not with appetitive reward hedonics. Moreover, only relief pleasantness covaried with accumbens activation. Importantly, the accumbens signal appeared to specifically reflect individual differences in anticipation of the adverse event (dread, pessimism) but was uncorrelated to appetitive reward hedonics. In conclusion, relief differs from appetitive rewards due to its reliance on negative expectations, the violation of which is reflected in relief-related accumbens activation.     

Contributions of the amygdala to reward expectancy and choice signals in human prefrontal cortex

The prefrontal cortex (PFC) receives substantial anatomical input from the amygdala, and these two structures have long been implicated in reward-related learning and decision making. Yet little is known about how these regions interact, especially in humans. We investigated the contribution of the amygdala to reward-related signals in PFC by scanning two rare subjects with focal bilateral amygdala lesions using fMRI. The subjects performed a reversal learning task in which they first had to learn which of two choices was the more rewarding, and then flexibly switch their choices when contingencies changed. Compared with healthy controls, both amygdala lesion subjects showed a profound change in ventromedial prefrontal cortex (vmPFC) activity associated with reward expectation and behavioral choice. These findings support a critical role for the human amygdala in establishing expected reward representations in PFC, which in turn may be used to guide behavioral choice.     

Orbitofrontal cortex and memory formation

Which one of the many regions of the anatomically heterogeneous prefrontal cortex is part of the critical core of the neural circuit for encoding? This positron emission tomography (PET) experiment measured changes in cerebral blood flow (CBF) in normal human participants during the presentation of abstract visual information in four conditions that varied in their encoding demands. As encoding increased across the different conditions, there was an increase in activity in the right orbitofrontal cortex and the right parahippocampal region. No significant activation peaks were present in any other region of the frontal or temporal lobe. These findings indicate that the orbitofrontal cortex, which is massively connected to the medial temporal cortex, is a critical frontal region for memory formation.