Adaptive Coding of Reward Value by Dopamine Neurons

By Philippe N. Tobler, Christopher D. Fiorillo, Wolfram Schultz. 2005

1,285 citations recorded by the source corpus.

Subfields: Cellular and Molecular Neuroscience, Molecular Biology

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cellular and Molecular Neuroscience

In Molecular Biology

Citations in the corpus

Theory of Mind: A Neural Prediction Problem (2013, neutral): “…example of a neural “error” code: the rate of firing corresponds to any currently “new” (i.e., previously unpredictable) information about the value of coming reward, not to the actual value of any currently perceived stimulus (Bayer and Glimcher, 2005; Nakahara et al., 2004; Tobler et al., 2005).”
Ventral tegmental area neurons in learned appetitive behavior and positive reinforcement. (2007, background): “This increase in firing scales with the magnitude of reward received (e.g., vol- ume of juice; Tobler et al. 2005).”
Tonic dopamine: opportunity costs and the control of response vigor (2007, positive): “Larger phasic prediction-error signals for stimuli previously associated with higher rewards (Fiorillo et al. 2003; Tobler et al. 2005) would then result in faster responding to these cues.”
Counterfactual Choice and Learning in a Neural Network Centered on Human Lateral Frontopolar Cortex (2011, background): “The discrepancy between the two, called the prediction error, is thought to be fundamental for learning because it partly determines the degree to which future reward expectations for the choice should be revised [6,7].”
Leptin regulation of the mesoaccumbens dopamine pathway. (2006, positive): “…incentive motivation (Berridge and Robinson, 1998; Kelley et al., 2005; Robinson et al., 2005; Salamone et al., 2005) and reward-related learning (Tobler et al., 2005), and is a major substrate underlying the locomotor-activating, rewarding and addictive effects of drugs of abuse (Wise, 2002;…”
Neural systems implicated in delayed and probabilistic reinforcement (2006, background): “DA neurons that innervate the Acb may fire in a manner related to reward probability (Fiorillo et al., 2003, 2005; Niv et al., 2005; Tobler et al., 2005) and the midbrain, the site of the cell bodies of these neurons, responds to stimulus uncertainty in humans (Aron et al.”
The debate over dopamine’s role in reward: the case for incentive salience (2007, background): “…models of reinforcement learning, which incorporates time more explicitly into expectations of reward as a series of future events ðV s t ð Þ ¼ h P i¼0 g i r tþ1 iÞ, (Bayer and Glimcher 2005; Daw et al. 2005; Dayan and Balleine 2002; Montague et al. 2004; Schultz 2002, 2006; Tobler et al. 2005a,b).”
Corticostriatal-hypothalamic circuitry and food motivation: integration of energy, action and reward. (2005, background): “An influential line of research on the electrophysiological responses of ventral tegmental area neurons has indicated that these cells may convey to the Acb a type of training signal related to the relevance of stimuli in predicting reward [176–178], although there is debate as to whether dopamine t”
Neuronal Reward and Decision Signals: From Theories to Data. (2015, background): “Their activations disappear gradually with extinction (598), possibly due to inhibition from neighboring pars reticulata neurons activated during extinction (408).”
Neural differentiation of expected reward and risk in human subcortical structures. (2006, methodology): “In the nonhuman primate brain, delayed firing of dopaminergic neurons was positively correlated with risk when risk was modulated by changing reward probabilities (Fiorillo et al., 2003; Tobler et al., 2005).”
Unique properties of mesoprefrontal neurons within a dual mesocorticolimbic dopamine system. (2008, positive): “Schultz and colleagues have successfully defined the computational roles of tonic and phasic discharge patterns of conventional DA midbrain neurons in reward-prediction error and uncertainty signaling (Fiorillo et al., 2003; Schultz, 2007; Tobler et al., 2005).”
Multiphasic Temporal Dynamics in Responses of Midbrain Dopamine Neurons to Appetitive and Aversive Stimuli (2013, methodology): “Previous work suggests that the system is optimized so that the activity of dopamine neurons robustly discriminates among the most likely reward values at each moment, consistent with principles of efficient (optimal) coding (Tobler et al., 2005).”
A framework for studying the neurobiology of value-based decision making (2008, background): “Similar risk and expected-value signals have been found in the midbrain dopamine system in electrophysiology studies in non-human primate”
Income and happiness: Evidence, explanations and economic implications (2006, background): “Some neurological evidence is presented in Tobler et al. (2005), using animal studies.”
Reinforcement learning in the brain (2009, result): “Impressively, even in sophisticated conditioning tasks such as blocking and appetitive conditioned inhibition, dopaminergic responses are in line with the predictions of TD learning (Tobler et al., 2003, 2005; Waelti, Dickinson, & Schultz, 2001).”