Short-term reward experience biases inference despite dissociable neural correlates

[1]  Xiao-Jing Wang,et al.  Inhibitory Control in the Cortico-Basal Ganglia-Thalamocortical Loop: Complex Regulation and Interplay with Memory and Decision Processes , 2016, Neuron.

[2]  Camillo Padoa-Schioppa,et al.  Neuronal Remapping and Circuit Persistence in Economic Decisions , 2016, Nature Neuroscience.

[3]  Timothy Edward John Behrens,et al.  Two Anatomically and Computationally Distinct Learning Signals Predict Changes to Stimulus-Outcome Associations in Hippocampus , 2016, Neuron.

[4]  R. Cools,et al.  Human Choice Strategy Varies with Anatomical Projections from Ventromedial Prefrontal Cortex to Medial Striatum. , 2016, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[5]  Peter Dayan,et al.  Simple Plans or Sophisticated Habits? State, Transition and Learning Interactions in the Two-Step Task , 2015, bioRxiv.

[6]  T. Hare,et al.  Transcranial Stimulation over Frontopolar Cortex Elucidates the Choice Attributes and Neural Mechanisms Used to Resolve Exploration–Exploitation Trade-Offs , 2015, The Journal of Neuroscience.

[7]  Marco K. Wittmann,et al.  The Good, the Bad, and the Irrelevant: Neural Mechanisms of Learning Real and Hypothetical Rewards and Effort , 2015, The Journal of Neuroscience.

[8]  M. Sakagami,et al.  Dissociable functions of reward inference in the lateral prefrontal cortex and the striatum , 2015, Front. Psychol..

[9]  Dylan A. Simon,et al.  Model-based choices involve prospective neural activity , 2015, Nature Neuroscience.

[10]  R. Dolan,et al.  Ventral striatal dopamine reflects behavioral and neural signatures of model-based control during sequential decision making , 2015, Proceedings of the National Academy of Sciences.

[11]  J. Kable,et al.  Dorsal striatum is necessary for stimulus-value but not action-value learning in humans. , 2014, Brain : a journal of neurology.

[12]  Joseph T. McGuire,et al.  Functionally Dissociable Influences on Learning Rate in a Dynamic Environment , 2014, Neuron.

[13]  Adrian M. Owen,et al.  Striatum in stimulus–response learning via feedback and in decision making , 2014, NeuroImage.

[14]  Alan D. Lopez,et al.  Global, regional, and national prevalence of overweight and obesity in children and adults during 1980–2013: a systematic analysis for the Global Burden of Disease Study 2013 , 2014, The Lancet.

[15]  Etienne Koechlin,et al.  Foundations of human reasoning in the prefrontal cortex , 2014, Science.

[16]  M. Ullsperger,et al.  Neurophysiology of performance monitoring and adaptive behavior. , 2014, Physiological reviews.

[17]  D. Sharp,et al.  The role of the posterior cingulate cortex in cognition and disease. , 2014, Brain : a journal of neurology.

[18]  Markus Ullsperger,et al.  Real and Fictive Outcomes Are Processed Differently but Converge on a Common Adaptive Mechanism , 2013, Neuron.

[19]  Timothy E. J. Behrens,et al.  Brain Systems for Probabilistic and Dynamic Prediction: Computational Specificity and Integration , 2013, PLoS biology.

[20]  Ian W. Eisenberg,et al.  Frontal Theta Overrides Pavlovian Learning Biases , 2013, The Journal of Neuroscience.

[21]  Massimo Marinacci,et al.  Advances in Economics and Econometrics: Ambiguity and the Bayesian Paradigm , 2013 .

[22]  Timothy E. J. Behrens,et al.  Counterfactual Choice and Learning in a Neural Network Centered on Human Lateral Frontopolar Cortex , 2011, PLoS biology.

[23]  John M. Pearson,et al.  Posterior cingulate cortex: adapting behavior to a changing world , 2011, Trends in Cognitive Sciences.

[24]  C. N. Boehler,et al.  Task-Load-Dependent Activation of Dopaminergic Midbrain Areas in the Absence of Reward , 2011, The Journal of Neuroscience.

[25]  P. Dayan,et al.  Model-based influences on humans’ choices and striatal prediction errors , 2011, Neuron.

[26]  Carsten Nicolas Boehler,et al.  Substantia Nigra Activity Level Predicts Trial-to-Trial Adjustments in Cognitive Control , 2011, Journal of Cognitive Neuroscience.

[27]  I. Gilboa,et al.  Advances in Economics and Econometrics: Ambiguity and the Bayesian Paradigm , 2011 .

[28]  Thomas H. B. FitzGerald,et al.  Differentiable Neural Substrates for Learned and Described Value and Risk , 2010, Current Biology.

[29]  Robert C. Wilson,et al.  An Approximately Bayesian Delta-Rule Model Explains the Dynamics of Belief Updating in a Changing Environment , 2010, The Journal of Neuroscience.

[30]  Pierre Baldi,et al.  Of bits and wows: A Bayesian theory of surprise with applications to attention , 2010, Neural Networks.

[31]  P. Dayan,et al.  States versus Rewards: Dissociable Neural Prediction Error Signals Underlying Model-Based and Model-Free Reinforcement Learning , 2010, Neuron.

[32]  Arnaud D'Argembeau,et al.  The Iowa Gambling Task in fMRI images , 2009, Human brain mapping.

[33]  C. Padoa-Schioppa Range-Adapting Representation of Economic Value in the Orbitofrontal Cortex , 2009, The Journal of Neuroscience.

[34]  M. Frank,et al.  Instructional control of reinforcement learning: A behavioral and neurocomputational investigation , 2009, Brain Research.

[35]  J. W. Aldridge,et al.  Dissecting components of reward: 'liking', 'wanting', and learning. , 2009, Current opinion in pharmacology.

[36]  Matthew Hickman,et al.  Global epidemiology of injecting drug use and HIV among people who inject drugs: a systematic review , 2008, The Lancet.

[37]  Mark W Woolrich,et al.  Associative learning of social value , 2008, Nature.

[38]  Andrew Caplin,et al.  Axiomatic Methods, Dopamine and Reward Prediction Error This Review Comes from a Themed Issue on Cognitive Neuroscience Edited Advantages of the Axiomatic Approach , 2022 .

[39]  R. Kessler,et al.  The prevalence and correlates of adult ADHD in the United States: results from the National Comorbidity Survey Replication. , 2006, The American journal of psychiatry.

[40]  T. Robbins,et al.  Neural systems of reinforcement for drug addiction: from actions to habits to compulsion , 2005, Nature Neuroscience.

[41]  Richard S. Sutton,et al.  Reinforcement Learning: An Introduction , 2005, IEEE Transactions on Neural Networks.

[42]  Mark W. Woolrich,et al.  Advances in functional and structural MR image analysis and implementation as FSL , 2004, NeuroImage.

[43]  K. R. Ridderinkhof,et al.  The Role of the Medial Frontal Cortex in Cognitive Control , 2004, Science.

[44]  Karl J. Friston,et al.  Dissociable Roles of Ventral and Dorsal Striatum in Instrumental Conditioning , 2004, Science.

[45]  Jonathan D. Cohen,et al.  Anterior Cingulate Conflict Monitoring and Adjustments in Control , 2004, Science.

[46]  S. Killcross,et al.  Coordination of actions and habits in the medial prefrontal cortex of rats. , 2003, Cerebral cortex.

[47]  Michael Brady,et al.  Improved Optimization for the Robust and Accurate Linear Registration and Motion Correction of Brain Images , 2002, NeuroImage.

[48]  Stephen M. Smith,et al.  A global optimisation method for robust affine registration of brain images , 2001, Medical Image Anal..

[49]  Don H. Johnson,et al.  Symmetrizing the Kullback-Leibler Distance , 2001 .

[50]  Nikolaus R. McFarland,et al.  Striatonigrostriatal Pathways in Primates Form an Ascending Spiral from the Shell to the Dorsolateral Striatum , 2000, The Journal of Neuroscience.

[51]  A. Damasio,et al.  Insensitivity to future consequences following damage to human prefrontal cortex , 1994, Cognition.

[52]  Richard S. Sutton,et al.  Neuronlike adaptive elements that can solve difficult learning control problems , 1983, IEEE Transactions on Systems, Man, and Cybernetics.

[53]  J. Stevens,et al.  Animal Intelligence , 1883, Nature.