A Neural Computational Model of Incentive Salience

By Citation Zhang, Jun Zhang, Kent C. Berridge, Amy J. Tindell, Kyle S. Smith, J. Aldridge, Karl J. Friston. PLoS Comput. Biol., 2009

318 citations recorded by the source corpus.

Incentive salience is a motivational property with ‘magnet-like’ qualities. When attributed to reward-predicting stimuli (cues), incentive salience triggers a pulse of ‘wanting’ and an individual is pulled toward the cues and reward. A key computational question is how incentive salience is generated during a cue re-encounter, which combines both learning and the state of limbic brain mechanisms. Learning processes, such as temporal-difference models, provide one way for stimuli to acquire cached predictive values of rewards. However, empirical data show that subsequent incentive values are also modulated on the fly by dynamic fluctuation in physiological states, altering cached values in ways requiring additional motivation mechanisms. Dynamic modulation of incentive salience for a Pavlovian conditioned stimulus (CS or cue) occurs during certain states, without necessarily requiring (re)learning about the cue. In some cases, dynamic modulation of cue value occurs during states that are quite novel, never having been experienced before, and even prior to experience of the associated unconditioned reward in the new state. Such cases can include novel drug-induced mesolimbic activation and addictive incentive-sensitization, as well as natural appetite states such as salt appetite. Dynamic enhancement specifically raises the incentive salience of an appropriate CS, without necessarily changing that of other CSs. Here we suggest a new computational model that modulates incentive salience by integrating changing physiological states with prior learning. We support the model with behavioral and neurobiological data from empirical tests that demonstrate dynamic elevations in cue-triggered motivation (involving natural salt appetite, and drug-induced intoxication and sensitization). Our data call for a dynamic model of incentive salience, such as presented here. Computational models can adequately capture fluctuations in cue-triggered ‘wanting’ only by incorporating modulation of previously learned values by natural appetite and addiction-related states.

Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience

View Paper: https://www.semanticscholar.org/paper/45291637057c4efe558de38c81ed562569119351

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Citations in the corpus

A connectome of a learning and memory center in the adult Drosophila brain (2017, background): “A second possibility, suggested from the framework of reinforcement learning established in vertebrates (Zhang et al., 2009), is related to motivation and the comparison of expected versus actual reward.”
Model-Based and Model-Free Pavlovian Reward Learning: Revaluation, Revision and Revelation (2014, methodology): “According to the Zhang et al. (2009) account, the cached value of previous UCS encounters is changed by a physiological–neurobiological factor called kappa that reflects the current brain/body state of the individual (whether the state is novel or familiar).”
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).”
Opponent actor learning (OpAL): modeling interactive effects of striatal dopamine on reinforcement learning and choice incentive. (2014, result): “These findings support the observations that motivational state at the time of choice can impact an animal's behavior to approach an action which had been preferentially associated with negative outcomes during learning (Zhang et al., 2009).”
From prediction error to incentive salience: mesolimbic computation of reward motivation (2012, background): “The first form, which is usually applicable, is multiplicative (A; equation 3a in Zhang et al., 2009): A : ~rðrt; jÞ ¼ j rt: This form applies to the amplification of ‘wanting’ for a reward by addictive drug administration or by permanent drug-induced neural sensitization.”
The tempted brain eats: pleasure and desire circuits in obesity and eating disorders. (2010, unknown): “But together in the right combinations they are motivationally compelling in a synergy that is greater than the sum of the parts (Zhang et al., 2009).”