From prediction error to incentive salience: mesolimbic computation of reward motivation

By Kent C. Berridge. European Journal of Neuroscience, 2012

691 citations recorded by the source corpus.

Reward contains separable psychological components of learning, incentive motivation and pleasure. Most computational models have focused only on the learning component of reward, but the motivational component is equally important in reward circuitry, and even more directly controls behavior. Modeling the motivational component requires recognition of additional control factors besides learning. Here I discuss how mesocorticolimbic mechanisms generate the motivation component of incentive salience. Incentive salience takes Pavlovian learning and memory as one input and as an equally important input takes neurobiological state factors (e.g. drug states, appetite states, satiety states) that can vary independently of learning. Neurobiological state changes can produce unlearned fluctuations or even reversals in the ability of a previously learned reward cue to trigger motivation. Such fluctuations in cue‐triggered motivation can dramatically depart from all previously learned values about the associated reward outcome. Thus, one consequence of the difference between incentive salience and learning can be to decouple cue‐triggered motivation of the moment from previously learned values of how good the associated reward has been in the past. Another consequence can be to produce irrationally strong motivation urges that are not justified by any memories of previous reward values (and without distorting associative predictions of future reward value). Such irrationally strong motivation may be especially problematic in addiction. To understand these phenomena, future models of mesocorticolimbic reward function should address the neurobiological state factors that participate to control generation of incentive salience.

Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/6457f5fb2af3d7fad62d62bebb7770effc49099e

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Citations in the corpus

Neurophysiology of performance monitoring and adaptive behavior. (2014, background): “In Berridge’s words, “ incentive salience is generated afresh by mesocorticolimbic circuits each time the stimulus is re-encountered ” (34).”
Interest Development and Its Relation to Curiosity: Needed Neuroscientific Research (2019, background): “Whereas the prediction error literature focuses on learning and anticipation of reward, Berridge and colleagues (e.g., Berridge 2012; Berridge and Robinson 1998) demonstrated that reward has three distinct psychological components, as well as three distinct neural substrates: liking, (affect),…”
Process Account of Curiosity and Interest: A Reward-Learning Perspective (2018, background): “Research in neuroscience has provided support of the distinction of liking and wanting in the reward learning process (Berridge 2012).”
Revisiting the Role of Rewards in Motivation and Learning: Implications of Neuroscientific Research (2016, background): “More specifically, regarding the liking/pleasure components, Berridge et al. (2009) con-”
Opponent actor learning (OpAL): modeling interactive effects of striatal dopamine on reinforcement learning and choice incentive. (2014, background): “Recent studies have debated the link between incentive or performance effects of dopamine on one hand, and reinforcement learning effects on the other, with some arguing that all reinforcement learning effects could be reinterpreted in terms of incentive salience (Berridge, 2012).”
Pleasure systems in the brain (2015, methodology): “(2013a), based on data from Reynolds and Berridge (2008) and Richard and Berridge (2011).”
Model-Based and Model-Free Pavlovian Reward Learning: Revaluation, Revision and Revelation (2014, background): “…or learned, as distinguished from the physiological manipulation by appetite states, drugs, or brain activations that might more directly change CS value in parallel with UCS value, similar to the CS result for Dead Sea saltiness (Berridge, 2012; Zhang, Berridge, Tindell, Smith, & Aldridge, 2009).”
Motivation and Personality: A Neuropsychological Perspective (2013, background): “Berridge (2007, 2012) has described the two major reward systems as incentive (‘wanting’) and hedonic (‘liking’) systems.”
Liking, Wanting and the Incentive-Sensitization Theory of Addiction (2016, background): “, & Berridge, K. C. (2003). Addiction. Annual Review of Psychology, 54, 25–53. http://dx.doi.org/10.1146/annurev.psych.54 .101601.145237 Robinson, T. E., & Berridge, K. C. (2008). The incentive sensitization theory of addiction: Some current issues. Philosophical Transactions of the Royal Society of”
The neuroscience of learning: beyond the Hebbian synapse. (2013, background): “There are several recent, theoretically oriented reviews of the relevant literature (Berridge 2012, Dayan & Daw 2008, Flagel et al. 2011, Schultz 2006, Zhang et al. 2009).”
Beyond simple reinforcement learning: the computational neurobiology of reward‐learning and valuation (2012, background): “Berridge (2012) summarizes experimental evidence to support his argument for a role of dopamine in regulating incentive salience.”