Trial-by-trial data analysis using computational models
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[1] Peter Bossaerts,et al. Neural correlates of mentalizing-related computations during strategic interactions in humans , 2008, Proceedings of the National Academy of Sciences.
[2] Ben J. A. Kröse,et al. Learning from delayed rewards , 1995, Robotics Auton. Syst..
[3] N. Daw,et al. Reinforcement Learning Signals in the Human Striatum Distinguish Learners from Nonlearners during Reward-Based Decision Making , 2007, The Journal of Neuroscience.
[4] P. Dayan,et al. Cortical substrates for exploratory decisions in humans , 2006, Nature.
[5] H. Akaike. A new look at the statistical model identification , 1974 .
[6] P. Dayan,et al. Differential Encoding of Losses and Gains in the Human Striatum , 2007, The Journal of Neuroscience.
[7] K. Doya,et al. The computational neurobiology of learning and reward , 2006, Current Opinion in Neurobiology.
[8] P. Glimcher,et al. JOURNAL OF THE EXPERIMENTAL ANALYSIS OF BEHAVIOR 2005, 84, 555–579 NUMBER 3(NOVEMBER) DYNAMIC RESPONSE-BY-RESPONSE MODELS OF MATCHING BEHAVIOR IN RHESUS MONKEYS , 2022 .
[9] Joseph Hilbe,et al. Data Analysis Using Regression and Multilevel/Hierarchical Models , 2009 .
[10] Colin Camerer,et al. Dissociating the Role of the Orbitofrontal Cortex and the Striatum in the Computation of Goal Values and Prediction Errors , 2008, The Journal of Neuroscience.
[11] R. Dolan,et al. Subliminal Instrumental Conditioning Demonstrated in the Human Brain , 2008, Neuron.
[12] G. Schwarz. Estimating the Dimension of a Model , 1978 .
[13] Brian Knutson,et al. FMRI Visualization of Brain Activity during a Monetary Incentive Delay Task , 2000, NeuroImage.
[14] P. Glimcher,et al. Midbrain Dopamine Neurons Encode a Quantitative Reward Prediction Error Signal , 2005, Neuron.
[15] Karl J. Friston,et al. Temporal Difference Models and Reward-Related Learning in the Human Brain , 2003, Neuron.
[16] A. Barto. Adaptive Critics and the Basal Ganglia , 1995 .
[17] P. Glimcher,et al. The neural correlates of subjective value during intertemporal choice , 2007, Nature Neuroscience.
[18] Karl J. Friston,et al. Bayesian model selection for group studies , 2009, NeuroImage.
[19] S. Kakade,et al. Acquisition and extinction in autoshaping. , 2002, Psychological review.
[20] Kenji Doya,et al. Estimating Internal Variables and Paramters of a Learning Agent by a Particle Filter , 2003, NIPS.
[21] R. Hertwig,et al. The priority heuristic: making choices without trade-offs. , 2006, Psychological review.
[22] J. O'Doherty,et al. Model‐Based fMRI and Its Application to Reward Learning and Decision Making , 2007, Annals of the New York Academy of Sciences.
[23] Samuel M. McClure,et al. Temporal Prediction Errors in a Passive Learning Task Activate Human Striatum , 2003, Neuron.
[24] Karl J. Friston,et al. Mixed-effects and fMRI studies , 2005, NeuroImage.
[25] P. Dayan,et al. Reinforcement learning: The Good, The Bad and The Ugly , 2008, Current Opinion in Neurobiology.
[26] Radford M. Neal. Pattern Recognition and Machine Learning , 2007, Technometrics.
[27] D. McFadden. Conditional logit analysis of qualitative choice behavior , 1972 .
[28] Karl J. Friston,et al. Generalisability, Random Effects & Population Inference , 1998, NeuroImage.
[29] Sabrina M. Tom,et al. The Neural Basis of Loss Aversion in Decision-Making Under Risk , 2007, Science.
[30] M. Hallett. Human Brain Function , 1998, Trends in Neurosciences.
[31] D. Barraclough,et al. Prefrontal cortex and decision making in a mixed-strategy game , 2004, Nature Neuroscience.
[32] David J. C. MacKay,et al. Information Theory, Inference, and Learning Algorithms , 2004, IEEE Transactions on Information Theory.
[33] Peter Dayan,et al. A Neural Substrate of Prediction and Reward , 1997, Science.
[34] K. Doya,et al. Representation of Action-Specific Reward Values in the Striatum , 2005, Science.
[35] Samuel M. McClure,et al. Policy Adjustment in a Dynamic Economic Game , 2006, PloS one.
[36] N. Daw,et al. Striatal Activity Underlies Novelty-Based Choice in Humans , 2008, Neuron.
[37] John N. Tsitsiklis,et al. Neuro-Dynamic Programming , 1996, Encyclopedia of Machine Learning.
[38] D. Freedman,et al. On The So-Called “Huber Sandwich Estimator” and “Robust Standard Errors” , 2006 .
[39] L. Nystrom,et al. Tracking the hemodynamic responses to reward and punishment in the striatum. , 2000, Journal of neurophysiology.
[40] Teck-Hua Ho,et al. Experience-Weighted Attraction Learning in Coordination Games: Probability Rules, Heterogeneity, and Time-Variation. , 1998, Journal of mathematical psychology.
[41] Michael L. Platt,et al. Neural correlates of decision variables in parietal cortex , 1999, Nature.
[42] R. Turner,et al. Event-Related fMRI: Characterizing Differential Responses , 1998, NeuroImage.
[43] J. O'Doherty,et al. Marketing actions can modulate neural representations of experienced pleasantness , 2008, Proceedings of the National Academy of Sciences.
[44] Sean M. Polyn,et al. Beyond mind-reading: multi-voxel pattern analysis of fMRI data , 2006, Trends in Cognitive Sciences.
[45] Michael J. Frank,et al. Genetic triple dissociation reveals multiple roles for dopamine in reinforcement learning , 2007, Proceedings of the National Academy of Sciences.
[46] Teck-Hua Ho,et al. Experience-Weighted Attraction Learning in Games: A Unifying Approach , 1997 .
[47] Peter Dayan,et al. Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems , 2001 .
[48] Karl J. Friston,et al. Posterior probability maps and SPMs , 2003, NeuroImage.
[49] W. Newsome,et al. Matching Behavior and the Representation of Value in the Parietal Cortex , 2004, Science.
[50] P. Dayan,et al. Uncertainty-based competition between prefrontal and dorsolateral striatal systems for behavioral control , 2005, Nature Neuroscience.
[51] L. Wasserman,et al. Computing Bayes Factors by Combining Simulation and Asymptotic Approximations , 1997 .
[52] Michael I. Jordan,et al. PEGASUS: A policy search method for large MDPs and POMDPs , 2000, UAI.
[53] Richard S. Sutton,et al. Reinforcement Learning: An Introduction , 1998, IEEE Trans. Neural Networks.
[54] Kevin McCabe,et al. Neural signature of fictive learning signals in a sequential investment task , 2007, Proceedings of the National Academy of Sciences.
[55] Timothy E. J. Behrens,et al. Learning the value of information in an uncertain world , 2007, Nature Neuroscience.
[56] John K Kruschke,et al. Bayesian data analysis. , 2010, Wiley interdisciplinary reviews. Cognitive science.
[57] C. Bhat. Quasi-random maximum simulated likelihood estimation of the mixed multinomial logit model , 2001 .
[58] P. J. Huber. The behavior of maximum likelihood estimates under nonstandard conditions , 1967 .
[59] Michael J. Frank,et al. By Carrot or by Stick: Cognitive Reinforcement Learning in Parkinsonism , 2004, Science.