Blocking D2/D3 dopamine receptors in male participants increases volatility of beliefs when learning to trust others

[1]  Rick A Adams,et al.  Increased Belief Instability in Psychotic Disorders Predicts Treatment Response to Metacognitive Training , 2022, Schizophrenia bulletin.

[2]  M. Rettenbacher,et al.  Sex differences in antipsychotic efficacy and side effects in schizophrenia spectrum disorder: results from the BeSt InTro study , 2021, npj Schizophrenia.

[3]  Rick A Adams,et al.  Everything is connected: Inference and attractors in delusions , 2021, Schizophrenia Research.

[4]  M. Mandelkern,et al.  Striatal dopamine D2-type receptor availability and peripheral 17β-estradiol , 2021, Molecular Psychiatry.

[5]  Klaas E. Stephan,et al.  Cholinergic and dopaminergic effects on prediction error and uncertainty responses during sensory associative learning , 2020, NeuroImage.

[6]  Katharina V. Wellstein,et al.  Hierarchical Bayesian models of social inference for probing persecutory delusional ideation. , 2020, Journal of abnormal psychology.

[7]  R. Mcelreath.  Statistical Rethinking , 2020 .

[8]  Karl J. Friston,et al.  Variability in Action Selection Relates to Striatal Dopamine 2/3 Receptor Availability in Humans: A PET Neuroimaging Study Using Reinforcement Learning and Active Inference Models , 2020, Cerebral cortex.

[9]  J. Gläscher,et al.  Using reinforcement learning models in social neuroscience: frameworks, pitfalls and suggestions of best practices , 2019, Social cognitive and affective neuroscience.

[10]  Dan J Stein,et al.  The Human Basolateral Amygdala Is Indispensable for Social Experiential Learning , 2019, Current Biology.

[11]  Samuel J. Gershman,et al.  Believing in dopamine , 2019, Nature Reviews Neuroscience.

[12]  Jessica I. Määttä,et al.  Dopamine promotes cognitive effort by biasing the benefits versus costs of cognitive work , 2019, Science.

[13]  Ladislas Nalborczyk,et al.  An Introduction to Bayesian Multilevel Models Using brms: A Case Study of Gender Effects on Vowel Variability in Standard Indonesian. , 2019, Journal of speech, language, and hearing research : JSLHR.

[14]  A. Shenhav,et al.  Resolving uncertainty in a social world , 2019, Nature Human Behaviour.

[15]  Eduardo A. Aponte,et al.  Inflexible social inference in individuals with subclinical persecutory delusional tendencies , 2019, Schizophrenia Research.

[16]  P. Bürkner,et al.  Ordinal Regression Models in Psychology: A Tutorial , 2019, Advances in Methods and Practices in Psychological Science.

[17]  Lars Muckli,et al.  The Predictive Coding Account of Psychosis , 2018, Biological Psychiatry.

[18]  V. Wyart,et al.  Computational noise in reward-guided learning drives behavioral variability in volatile environments , 2018, Nature Neuroscience.

[19]  Rick A Adams,et al.  Dopaminergic basis for signaling belief updates, but not surprise, and the link to paranoia , 2018, Proceedings of the National Academy of Sciences.

[20]  Jenifer Z. Siegel,et al.  Beliefs about bad people are volatile , 2018, Nature Human Behaviour.

[21]  Gary Napier,et al.  Attractor-like Dynamics in Belief Updating in Schizophrenia , 2018, The Journal of Neuroscience.

[22]  S. Gershman,et al.  Belief state representation in the dopamine system , 2018, Nature Communications.

[23]  F. Turkheimer,et al.  Determinants of treatment response in first-episode psychosis: an 18F-DOPA PET study , 2018, Molecular Psychiatry.

[24]  M. Mehta,et al.  The “highs and lows” of the human brain on dopaminergics: Evidence from neuropharmacology , 2017, Neuroscience & Biobehavioral Reviews.

[25]  Paul-Christian Bürkner,et al.  brms: An R Package for Bayesian Multilevel Models Using Stan , 2017 .

[26]  Samuel Gershman,et al.  Dopamine, Inference, and Uncertainty , 2017, bioRxiv.

[27]  David Badre,et al.  Working Memory Load Strengthens Reward Prediction Errors , 2017, The Journal of Neuroscience.

[28]  D. Zald,et al.  The impact of common dopamine D2 receptor gene polymorphisms on D2/3 receptor availability: C957T as a key determinant in putamen and ventral striatum , 2017, Translational Psychiatry.

[29]  T. Robbins,et al.  Effects of dopamine D2/D3 receptor antagonism on human planning and spatial working memory , 2017, Translational Psychiatry.

[30]  W. Schultz,et al.  Dopamine Modulates Adaptive Prediction Error Coding in the Human Midbrain and Striatum , 2017, The Journal of Neuroscience.

[31]  Jiqiang Guo,et al.  Stan: A Probabilistic Programming Language. , 2017, Journal of statistical software.

[32]  P. Dayan,et al.  Pharmacological Fingerprints of Contextual Uncertainty , 2016, PLoS biology.

[33]  Nikolaus Weiskopf,et al.  A17 HD brain-train: neuroplasticity as a target to improve function in huntington’s disease , 2016 .

[34]  Rafal Bogacz,et al.  Learning Reward Uncertainty in the Basal Ganglia , 2016, PLoS Comput. Biol..

[35]  Lei Zhang,et al.  Revealing Neurocomputational Mechanisms of Reinforcement Learning and Decision-Making With the hBayesDM Package , 2016, bioRxiv.

[36]  D. Freeman.  Persecutory delusions: a cognitive perspective on understanding and treatment. , 2016, The lancet. Psychiatry.

[37]  C. Soares-Cunha,et al.  Activation of D2 dopamine receptor-expressing neurons in the nucleus accumbens increases motivation , 2016, Nature Communications.

[38]  W. Schultz,et al.  Adaptive Prediction Error Coding in the Human Midbrain and Striatum Facilitates Behavioral Adaptation and Learning Efficiency , 2016, Neuron.

[39]  P. Sterzer,et al.  Mesolimbic confidence signals guide perceptual learning in the absence of external feedback , 2016, eLife.

[40]  B. Mickey,et al.  Genetic variation and dopamine D2 receptor availability: a systematic review and meta-analysis of human in vivo molecular imaging studies , 2016, Translational Psychiatry.

[41]  Richard McElreath,et al.  Statistical Rethinking: A Bayesian Course with Examples in R and Stan , 2015 .

[42]  E. Phelps,et al.  The Effects of Social Context and Acute Stress on Decision Making Under Uncertainty , 2015, Psychological science.

[43]  Samuel Gershman,et al.  A Unifying Probabilistic View of Associative Learning , 2015, PLoS Comput. Biol..

[44]  Aki Vehtari,et al.  Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC , 2015, Statistics and Computing.

[45]  Rick A Adams,et al.  Computational Psychiatry: towards a mathematically informed understanding of mental illness , 2015, Journal of Neurology, Neurosurgery & Psychiatry.

[46]  T. Fuchs.  The intersubjectivity of delusions , 2015, World psychiatry : official journal of the World Psychiatric Association.

[47]  B. Averbeck,et al.  Injection of a Dopamine Type 2 Receptor Antagonist into the Dorsal Striatum Disrupts Choices Driven by Previous Outcomes, But Not Perceptual Inference , 2015, The Journal of Neuroscience.

[48]  Karl J. Friston,et al.  Active inference and epistemic value , 2015, Cognitive neuroscience.

[49]  Karl J. Friston,et al.  Uncertainty in perception and the Hierarchical Gaussian Filter , 2014, Front. Hum. Neurosci..

[50]  John K. Kruschke,et al.  Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan , 2014 .

[51]  Namjung Huh,et al.  Role of dopamine D2 receptors in optimizing choice strategy in a dynamic and uncertain environment , 2014, Front. Behav. Neurosci..

[52]  Anne G E Collins,et al.  Working Memory Contributions to Reinforcement Learning Impairments in Schizophrenia , 2014, The Journal of Neuroscience.

[53]  M. Ullsperger,et al.  Differential Modulation of Reinforcement Learning by D2 Dopamine and NMDA Glutamate Receptor Antagonism , 2014, The Journal of Neuroscience.

[54]  Karl J. Friston,et al.  The Dopaminergic Midbrain Encodes the Expected Certainty about Desired Outcomes , 2014, Cerebral cortex.

[55]  Karl J. Friston,et al.  Computational psychiatry: the brain as a phantastic organ. , 2014, The lancet. Psychiatry.

[56]  D. Bates,et al.  Fitting Linear Mixed-Effects Models Using lme4 , 2014, 1406.5823.

[57]  T. Robbins,et al.  Role of Dopamine D2 Receptors in Human Reinforcement Learning , 2014, Neuropsychopharmacology.

[58]  ปิยดา สมบัติวัฒนา.  Behavioral Game Theory: Experiments in Strategic Interaction , 2013 .

[59]  Raymond J. Dolan,et al.  The anatomy of choice: active inference and agency , 2013, Front. Hum. Neurosci..

[60]  J. Rieskamp,et al.  DAT1 Polymorphism Determines L-DOPA Effects on Learning about Others’ Prosociality , 2013, PloS one.

[61]  Lydia Krabbendam,et al.  Trust versus paranoia: abnormal response to social reward in psychotic illness. , 2013, Brain : a journal of neurology.

[62]  Karl J. Friston,et al.  The Computational Anatomy of Psychosis , 2013, Front. Psychiatry.

[63]  Mark Slifstein,et al.  The nature of dopamine dysfunction in schizophrenia and what this means for treatment. , 2012, Archives of general psychiatry.

[64]  Andreas Meyer-Lindenberg,et al.  Neural mechanisms of social risk for psychiatric disorders , 2012, Nature Neuroscience.

[65]  Anne G E Collins,et al.  How much of reinforcement learning is working memory, not reinforcement learning? A behavioral, computational, and neurogenetic analysis , 2012, The European journal of neuroscience.

[66]  Martin Strobel,et al.  To trust or not to trust: the dynamics of social interaction in psychosis. , 2012, Brain : a journal of neurology.

[67]  Raymond J. Dolan,et al.  Dopamine, Affordance and Active Inference , 2012, PLoS Comput. Biol..

[68]  R. Romo,et al.  Dopamine neurons code subjective sensory experience and uncertainty of perceptual decisions , 2011, Proceedings of the National Academy of Sciences.

[69]  Anthony A Grace,et al.  Antipsychotic Drugs Rapidly Induce Dopamine Neuron Depolarization Block in a Developmental Rat Model of Schizophrenia , 2011, The Journal of Neuroscience.

[70]  M. D’Esposito,et al.  Inverted-U–Shaped Dopamine Actions on Human Working Memory and Cognitive Control , 2011, Biological Psychiatry.

[71]  M. Batzer,et al.  Reading TE leaves: new approaches to the identification of transposable element insertions. , 2011, Genome research.

[72]  Karl J. Friston,et al.  A Bayesian Foundation for Individual Learning Under Uncertainty , 2011, Front. Hum. Neurosci..

[73]  M. Ullsperger,et al.  Dopamine-Mediated Reinforcement Learning Signals in the Striatum and Ventromedial Prefrontal Cortex Underlie Value-Based Choices , 2011, The Journal of Neuroscience.

[74]  A. Malhotra,et al.  D2 receptor genetic variation and clinical response to antipsychotic drug treatment: a meta-analysis. , 2010, The American journal of psychiatry.

[75]  Lorena R. R. Gianotti,et al.  Dopamine Receptor D4 Polymorphism Predicts the Effect of L-DOPA on Gambling Behavior , 2010, Biological Psychiatry.

[76]  O. Hikosaka,et al.  Two types of dopamine neuron distinctly convey positive and negative motivational signals , 2009, Nature.

[77]  E. Fehr.  On the Economics and Biology of Trust , 2009, SSRN Electronic Journal.

[78]  Karl J. Friston.  Hierarchical Models in the Brain , 2008, PLoS Comput. Biol..

[79]  Colin Camerer,et al.  Explicit neural signals reflecting reward uncertainty , 2008, Philosophical Transactions of the Royal Society B: Biological Sciences.

[80]  W. Newsome,et al.  The temporal precision of reward prediction in dopamine neurons , 2008, Nature Neuroscience.

[81]  W. Yao,et al.  Dopaminergic signaling in dendritic spines. , 2008, Biochemical pharmacology.

[82]  R. Zeckhauser,et al.  Betrayal Aversion: Evidence from Brazil, China, Oman, Switzerland, Turkey, and the United States , 2008 .

[83]  Michael X. Cohen,et al.  Dopamine gene predicts the brain's response to dopaminergic drug , 2007, The European journal of neuroscience.

[84]  F. Yasuno,et al.  The antipsychotic sultopride is overdosed--a PET study of drug-induced receptor occupancy in comparison with sulpiride. , 2006, The international journal of neuropsychopharmacology.

[85]  R. Dolan,et al.  Dopamine-dependent prediction errors underpin reward-seeking behaviour in humans , 2006, Nature.

[86]  Michael J. Frank,et al.  A mechanistic account of striatal dopamine function in human cognition: psychopharmacological studies with cabergoline and haloperidol. , 2006, Behavioral neuroscience.

[87]  V. S. Chakravarthy,et al.  The Role of the Basal Ganglia in Exploration in a Neural Model Based on Reinforcement Learning , 2006, Int. J. Neural Syst..

[88]  W. Schultz,et al.  Behavioral and Brain Functions , 2005 .

[89]  Merja Haaparanta,et al.  The A1 allele of the human D2 dopamine receptor gene is associated with increased activity of striatal L-amino acid decarboxylase in healthy subjects , 2005, Pharmacogenetics and genomics.

[90]  S. Quartz,et al.  Getting to Know You: Reputation and Trust in a Two-Person Economic Exchange , 2005, Science.

[91]  W. Schultz,et al.  Adaptive Coding of Reward Value by Dopamine Neurons , 2005, Science.

[92]  Michael J. Frank,et al.  By Carrot or by Stick: Cognitive Reinforcement Learning in Parkinsonism , 2004, Science.

[93]  K. Erlandsson,et al.  Is regionally selective D2/D3 dopamine occupancy sufficient for atypical antipsychotic effect? an in vivo quantitative [123I]epidepride SPET study of amisulpride-treated patients. , 2003, The American journal of psychiatry.

[94]  L. Hays,et al.  Risperidone Attenuates the Discriminative-Stimulus Effects of d-Amphetamine in Humans , 2003, Journal of Pharmacology and Experimental Therapeutics.

[95]  Colin Camerer.  Behavioral Game Theory: Experiments in Strategic Interaction , 2003 .

[96]  J. Horvitz,et al.  Opposing Roles of D1 and D2 Receptors in Appetitive Conditioning , 2003, The Journal of Neuroscience.

[97]  U. Fischbacher,et al.  Strong reciprocity, human cooperation, and the enforcement of social norms , 2002, Human nature.

[98]  T. Robbins,et al.  Systemic sulpiride in young adult volunteers simulates the profile of cognitive deficits in Parkinson’s disease , 1999, Psychopharmacology.

[99]  W. Schultz.  Predictive reward signal of dopamine neurons. , 1998, Journal of neurophysiology.

[100]  Douglas M. Bates,et al.  LINEAR AND NONLINEAR MIXED-EFFECTS MODELS , 1998 .

[101]  Anthony A. Grace,et al.  Dopamine-cell depolarization block as a model for the therapeutic actions of antipsychotic drugs , 1997, Trends in Neurosciences.

[102]  Joyce E. Berg,et al.  Trust, Reciprocity, and Social History , 1995 .

[103]  D. Rubin,et al.  Inference from Iterative Simulation Using Multiple Sequences , 1992 .

[104]  E. Richfield,et al.  Anatomical and affinity state comparisons between dopamine D1 and D2 receptors in the rat central nervous system , 1989, Neuroscience.

[105]  William D. Penny,et al.  The Role of Dopamine in Temporal Uncertainty , 2016, Journal of Cognitive Neuroscience.

[106]  P. Read Montague,et al.  King-Casas Economic Exchange Getting to Know You : Reputation and Trust in a Two-Person , 2014 .

[107]  A. Meyer-Lindenberg,et al.  Striatal presynaptic dopamine in schizophrenia, part II: meta-analysis of [(18)F/(11)C]-DOPA PET studies. , 2013, Schizophrenia bulletin.

[108]  S. Kapur,et al.  How antipsychotics work—From receptors to reality , 2011, NeuroRX.

[109]  A. Cooper,et al.  Predictive Reward Signal of Dopamine Neurons , 2011 .

[110]  P. Grasby,et al.  Dopamine D2 receptor occupancy levels of acute sulpiride challenges that produce working memory and learning impairments in healthy volunteers , 2007, Psychopharmacology.

[111]  Michael J. Frank,et al.  Dynamic Dopamine Modulation in the Basal Ganglia: A Neurocomputational Account of Cognitive Deficits in Medicated and Nonmedicated Parkinsonism , 2005, Journal of Cognitive Neuroscience.

[112]  Richard S. Sutton,et al.  Reinforcement Learning: An Introduction , 1998, IEEE Trans. Neural Networks.

[113]  G. Sedvall,et al.  Prolactin response following intravenous and oral sulpiride in healthy human subjects in relation to sulpiride concentrations , 2004, Psychopharmacology.

[114]  S. Kakade,et al.  Acquisition and extinction in autoshaping. , 2002, Psychological review.

[115]  F. Bressolle,et al.  Absolute bioavailability, rate of absorption, and dose proportionality of sulpiride in humans. , 1992, Journal of pharmaceutical sciences.

[116]  R. Rescorla,et al.  A theory of Pavlovian conditioning : Variations in the effectiveness of reinforcement and nonreinforcement , 1972 .

[117]  W. Brown.  Animal Intelligence: Experimental Studies , 1912, Nature.