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      Mesolimbic Dopamine Signals the Value of Work

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          Abstract

          Dopamine cell firing can encode errors in reward prediction, providing a learning signal to guide future behavior. Yet dopamine is also a key modulator of motivation, invigorating current behavior. Existing theories propose that fast (“phasic”) dopamine fluctuations support learning, while much slower (“tonic”) dopamine changes are involved in motivation. We examined dopamine release in the nucleus accumbens across multiple time scales, using complementary microdialysis and voltammetric methods during adaptive decision-making. We first show that minute-by-minute dopamine levels covary with reward rate and motivational vigor. We then show that second-by-second dopamine release encodes an estimate of temporally-discounted future reward (a value function). We demonstrate that changing dopamine immediately alters willingness to work, and reinforces preceding action choices by encoding temporal-difference reward prediction errors. Our results indicate that dopamine conveys a single, rapidly-evolving decision variable, the available reward for investment of effort, that is employed for both learning and motivational functions.

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          Most cited references59

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          The debate over dopamine's role in reward: the case for incentive salience.

          Debate continues over the precise causal contribution made by mesolimbic dopamine systems to reward. There are three competing explanatory categories: 'liking', learning, and 'wanting'. Does dopamine mostly mediate the hedonic impact of reward ('liking')? Does it instead mediate learned predictions of future reward, prediction error teaching signals and stamp in associative links (learning)? Or does dopamine motivate the pursuit of rewards by attributing incentive salience to reward-related stimuli ('wanting')? Each hypothesis is evaluated here, and it is suggested that the incentive salience or 'wanting' hypothesis of dopamine function may be consistent with more evidence than either learning or 'liking'. In brief, recent evidence indicates that dopamine is neither necessary nor sufficient to mediate changes in hedonic 'liking' for sensory pleasures. Other recent evidence indicates that dopamine is not needed for new learning, and not sufficient to directly mediate learning by causing teaching or prediction signals. By contrast, growing evidence indicates that dopamine does contribute causally to incentive salience. Dopamine appears necessary for normal 'wanting', and dopamine activation can be sufficient to enhance cue-triggered incentive salience. Drugs of abuse that promote dopamine signals short circuit and sensitize dynamic mesolimbic mechanisms that evolved to attribute incentive salience to rewards. Such drugs interact with incentive salience integrations of Pavlovian associative information with physiological state signals. That interaction sets the stage to cause compulsive 'wanting' in addiction, but also provides opportunities for experiments to disentangle 'wanting', 'liking', and learning hypotheses. Results from studies that exploited those opportunities are described here. In short, dopamine's contribution appears to be chiefly to cause 'wanting' for hedonic rewards, more than 'liking' or learning for those rewards.
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            A Causal Link Between Prediction Errors, Dopamine Neurons and Learning

            Situations where rewards are unexpectedly obtained or withheld represent opportunities for new learning. Often, this learning includes identifying cues that predict reward availability. Unexpected rewards strongly activate midbrain dopamine neurons. This phasic signal is proposed to support learning about antecedent cues by signaling discrepancies between actual and expected outcomes, termed a reward prediction error. However, it is unknown whether dopamine neuron prediction error signaling and cue-reward learning are causally linked. To test this hypothesis, we manipulated dopamine neuron activity in rats in two behavioral procedures, associative blocking and extinction, that illustrate the essential function of prediction errors in learning. We observed that optogenetic activation of dopamine neurons concurrent with reward delivery, mimicking a prediction error, was sufficient to cause long-lasting increases in cue-elicited reward-seeking behavior. Our findings establish a causal role for temporally-precise dopamine neuron signaling in cue-reward learning, bridging a critical gap between experimental evidence and influential theoretical frameworks.
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              Matching behavior and the representation of value in the parietal cortex.

              Psychologists and economists have long appreciated the contribution of reward history and expectation to decision-making. Yet we know little about how specific histories of choice and reward lead to an internal representation of the "value" of possible actions. We approached this problem through an integrated application of behavioral, computational, and physiological techniques. Monkeys were placed in a dynamic foraging environment in which they had to track the changing values of alternative choices through time. In this context, the monkeys' foraging behavior provided a window into their subjective valuation. We found that a simple model based on reward history can duplicate this behavior and that neurons in the parietal cortex represent the relative value of competing actions predicted by this model.
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                Author and article information

                Journal
                9809671
                21092
                Nat Neurosci
                Nat. Neurosci.
                Nature neuroscience
                1097-6256
                1546-1726
                28 October 2015
                23 November 2015
                January 2016
                01 July 2016
                : 19
                : 1
                : 117-126
                Affiliations
                [1 ]) Department of Psychology, University of Michigan, Ann Arbor, USA
                [2 ]) Department of Chemistry, University of Michigan, Ann Arbor, USA
                [3 ]) Department of Pharmacology, University of Michigan, Ann Arbor, USA
                [4 ]) Department of Biomedical Engineering, University of Michigan, Ann Arbor, USA
                [5 ]) Department of the Neuroscience Graduate Program, University of Michigan, Ann Arbor, USA
                [6 ]) BrainLinks-BrainTools Cluster of Excellence and Bernstein Center, University of Freiburg, Germany
                [7 ]) Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
                Author notes
                [9 ]) Corresponding author ( jdberke@ 123456umich.edu )
                [8]

                ) Contributed equally to this work.

                Article
                NIHMS733226
                10.1038/nn.4173
                4696912
                26595651
                bf6ce2b4-cd7d-474a-a816-8bf6ab1ad909

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                Neurosciences
                Neurosciences

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