Wolfram Schultz

Getting formal with dopamine and reward.

Recent neurophysiological studies reveal that neurons in certain brain structures carry specific signals about past and future rewards. Dopamine neurons display a short-latency, phasic reward signal indicating the difference between actual and predicted rewards. The signal is useful for enhancing neuronal processing and learning behavioral reactions. It is distinctly different from dopamines tonic enabling of numerous behavioral processes. Neurons in the striatum, frontal cortex, and amygdala also process reward information but provide more differentiated information for identifying and anticipating rewards and organizing goal-directed behavior. The different reward signals have complementary functions, and the optimal use of rewards in voluntary behavior would benefit from interactions between the signals. Addictive psychostimulant drugs may exert their action by amplifying the dopamine reward signal.

Multiple reward signals in the brain

The fundamental biological importance of rewards has created an increasing interest in the neuronal processing of reward information. The suggestion that the mechanisms underlying drug addiction might involve natural reward systems has also stimulated interest. This article focuses on recent neurophysiological studies in primates that have revealed that neurons in a limited number of brain structures carry specific signals about past and future rewards. This research provides the first step towards an understanding of how rewards influence behaviour before they are received and how the brain might use reward information to control learning and goal-directed behaviour.

Dopamine responses comply with basic assumptions of formal learning theory

According to contemporary learning theories, the discrepancy, or error, between the actual and predicted reward determines whether learning occurs when a stimulus is paired with a reward. The role of prediction errors is directly demonstrated by the observation that learning is blocked when the stimulus is paired with a fully predicted reward. By using this blocking procedure, we show that the responses of dopamine neurons to conditioned stimuli was governed differentially by the occurrence of reward prediction errors rather than stimulus–reward associations alone, as was the learning of behavioural reactions. Both behavioural and neuronal learning occurred predominantly when dopamine neurons registered a reward prediction error at the time of the reward. Our data indicate that the use of analytical tests derived from formal behavioural learning theory provides a powerful approach for studying the role of single neurons in learning.

Behavioral dopamine signals

Lesioning and psychopharmacological studies suggest a wide range of behavioral functions for ascending midbrain dopaminergic systems. However, electrophysiological and neurochemical studies during specific behavioral tasks demonstrate a more restricted spectrum of dopamine-mediated changes. Substantial increases in dopamine-mediated activity, as measured by electrophysiology or voltammetry, are related to rewards and reward-predicting stimuli. A somewhat slower, distinct electrophysiological response encodes the uncertainty associated with rewards. Aversive events produce different, mostly slower, electrophysiological dopamine responses that consist predominantly of depressions. Additionally, more modest dopamine concentration fluctuations, related to punishment and movement, are seen at 200-18,000 times longer time courses using voltammetry and microdialysis in vivo. Using these responses, dopamine neurotransmission provides differential and heterogeneous information to subcortical and cortical brain structures about essential outcome components for approach behavior, learning and economic decision-making.

Dopamine neurons and their role in reward mechanisms.

Information related to rewards is processed by a limited number of brain structures. Recent studies have demonstrated that dopamine neurons respond to appetitive events, such as primary rewards and reward-predicting stimuli. Rather than responding unconditionally, these neurons signal deviations from the prediction of future appetitive events. These reward-related responses correspond formally to concepts of behavioral and computational learning theories and may thus constitute teaching signals for appetitive learning.

Dopamine signals for reward value and risk: basic and recent data

BackgroundPrevious lesion, electrical self-stimulation and drug addiction studies suggest that the midbrain dopamine systems are parts of the reward system of the brain. This review provides an updated overview about the basic signals of dopamine neurons to environmental stimuli.MethodsThe described experiments used standard behavioral and neurophysiological methods to record the activity of single dopamine neurons in awake monkeys during specific behavioral tasks.ResultsDopamine neurons show phasic activations to external stimuli. The signal reflects reward, physical salience, risk and punishment, in descending order of fractions of responding neurons. Expected reward value is a key decision variable for economic choices. The reward response codes reward value, probability and their summed product, expected value. The neurons code reward value as it differs from prediction, thus fulfilling the basic requirement for a bidirectional prediction error teaching signal postulated by learning theory. This response is scaled in units of standard deviation. By contrast, relatively few dopamine neurons show the phasic activation following punishers and conditioned aversive stimuli, suggesting a lack of relationship of the reward response to general attention and arousal. Large proportions of dopamine neurons are also activated by intense, physically salient stimuli. This response is enhanced when the stimuli are novel; it appears to be distinct from the reward value signal. Dopamine neurons show also unspecific activations to non-rewarding stimuli that are possibly due to generalization by similar stimuli and pseudoconditioning by primary rewards. These activations are shorter than reward responses and are often followed by depression of activity. A separate, slower dopamine signal informs about risk, another important decision variable. The prediction error response occurs only with reward; it is scaled by the risk of predicted reward.ConclusionsNeurophysiological studies reveal phasic dopamine signals that transmit information related predominantly but not exclusively to reward. Although not being entirely homogeneous, the dopamine signal is more restricted and stereotyped than neuronal activity in most other brain structures involved in goal directed behavior.

Neural coding of basic reward terms of animal learning theory, game theory, microeconomics and behavioural ecology

Neurons in a small number of brain structures detect rewards and reward-predicting stimuli and are active during the expectation of predictable food and liquid rewards. These neurons code the reward information according to basic terms of various behavioural theories that seek to explain reward-directed learning, approach behaviour and decision-making. The involved brain structures include groups of dopamine neurons, the striatum including the nucleus accumbens, the orbitofrontal cortex and the amygdala. The reward information is fed to brain structures involved in decision-making and organisation of behaviour, such as the dorsolateral prefrontal cortex and possibly the parietal cortex. The neural coding of basic reward terms derived from formal theories puts the neurophysiological investigation of reward mechanisms on firm conceptual grounds and provides neural correlates for the function of rewards in learning, approach behaviour and decision-making.

Updating dopamine reward signals.

Highlights ► Dopamine prediction errors are influenced by model-based information. ► Dopamine neurons show limited activations to punishers when proper controls are made. ► Dopamine neurons do not code salience to a substantial extent. ► Intact dopamine mechanisms are required for learning and posysynaptic plasticity.

Responses to reward in monkey dorsal and ventral striatum.

SummaryThe sources of input and the behavioral effects of lesions and drug administration suggest that the striatum participates in motivational processes. We investigated the activity of single striatal neurons of monkeys in response to reward delivered for performing in a go-nogo task. A drop of liquid was given each time the animal correctly executed or withheld an arm movement in reaction to a visual stimulus. Of 1593 neurons, 115 showed increased activity in response to delivery of liquid reward in both go and nogo trials. Responding neurons were predominantly located in dorsal and ventromedial parts of anterior putamen, in dorsal and ventral caudate, and in nucleus accumbens. They were twice as frequent in ventral as compared to dorsal striatal areas. Responses occurred at a median latency of 337 ms and lasted for 525 ms, with insignificant differences between dorsal and ventral striatum. Reward responses differed from activity recorded in the face area of posterior putamen which varied synchronously with individual mouth movements. Responses were directly related to delivery of primary liquid reward and not to auditory stimuli associated with it. Most of them also occurred when reward was delivered outside of the task. These results demonstrate that neurons of dorsal and particularly ventral striatum are involved in processing information concerning the attribution of primary reward.

Neural Correlates of Value, Risk, and Risk Aversion Contributing to Decision Making under Risk

Decision making under risk is central to human behavior. Economic decision theory suggests that value, risk, and risk aversion influence choice behavior. Although previous studies identified neural correlates of decision parameters, the contribution of these correlates to actual choices is unknown. In two different experiments, participants chose between risky and safe options. We identified discrete blood oxygen level-dependent (BOLD) correlates of value and risk in the ventral striatum and anterior cingulate, respectively. Notably, increasing inferior frontal gyrus activity to low risk and safe options correlated with higher risk aversion. Importantly, the combination of these BOLD responses effectively decoded the behavioral choice. Striatal value and cingulate risk responses increased the probability of a risky choice, whereas inferior frontal gyrus responses showed the inverse relationship. These findings suggest that the BOLD correlates of decision factors are appropriate for an ideal observer to detect behavioral choices. More generally, these biological data contribute to the validity of the theoretical decision parameters for actual decisions under risk.