Wilson, R. C., Takahashi, Y. K., Schoenbaum, G., & Niv, Y. (accepted). Orbitofrontal cortex as a cognitive map of task space. Neuron

Wilson, R. C., Nassar, M. R., & Gold, J. I. (2013). A Delta-rule approximation to Bayesian inference in change-point problems. PLOS Computational Biology, 9(7), e1003150 [pdf] [supplement]

Wilson, R. C., & Niv, Y. (2012). Inferring relevance in a changing world. Frontiers in Human Neuroscience, 5:189. doi: 10.3389/fnhum.2011.00189 [pdf]

Nassar, M. R., Rumsey, K. M., Wilson, R. C., Parikh, K., Heasly, B., & Gold, J. I. (2012). Rational regulation of learning dynamics by pupil-linked arousal systems. Nature Neuroscience, 15, 1040-1046. doi:10.1038/nn.3130 [pdf]

Takahashi, Y. K., Roesch, M. R., Wilson, R. C., Toreson, K., P. O'Donnell, Niv, Y., & Schoenbaum, G. (2011). Expectancy-related firing of midbrain dopamine neurons depends on orbitofrontal cortex. Nature Neuroscience, 14, 1590-1597 [pdf]

Wilson, R. C., Nassar, M. R., & Gold, J. I. (2010). Bayesian online learning of the hazard rate in change-point problems. Neural Computation, 22(9), 2452-2476 [pdf] [code]

Nassar, M. R., Wilson, R. C., Heasly, B., & Gold, J. I. (2010). An approximately Bayesian Delta-rule model explains the dynamics of belief updating in a changing environment. Journal of Neuroscience, 30(37), 12366-12378 [pdf]

Wilson, R. C. (2009). Parallel Hopfield networks. Neural Computation, 21(3), 831-850 [pdf] [code]

Das, S. R., Lazarewicz, M. T., Wilson, R. C., & Finkel, L. H. (2009). Sensitivity to motion features in point light displays of biological motion. Spatial Vision, 22(2), 105-125

Das, S. R., Wilson, R. C., Lazarewicz, M. T., & Finkel, L. H. (2006). Two-stage PCA extracts spatiotemporal features for gait recognition. Journal of Multimedia, 1(5), 9-17.

Wilson, R. C., & Hürlimann, M. D. (2006). Relationships between internal field gradients, diffusion & relaxation in porous media. Journal of Magnetic Resonance, 183(1), 1-12 [pdf]

Wilson, R. C., Geana, A., White, J. M., Ludvig, E. A. & Cohen, J. D. (2013). Exploration strategies in human decision making. Reinforcement Learning & Decision Making [pdf] [poster]

Wilson, R. C., & Niv, Y. (2013). Is model fitting necessary for model-based fMRI? Reinforcement Learning & Decision Making [pdf] [poster]

Geana, A., Wilson, R. C., & Cohen, J. D. (2013). Reward, Risk & Ambiguity in Human Exploration: A Wheel of Fortune Task. Reinforcement Learning & Decision Making [pdf] [poster]

Reverdy, P., Wilson, R. C., Holmes, P., & Leonard, N. E. (2012). Towards optimization of a human-inspired heuristic for solving explore-exploit problems. 51st IEEE Conference on Decision & Control (pp. 2820-2825) [pdf]

Gershman, S. J., & Wilson, R. C. (2010). The neural costs of optimal control. Advances in Neural Information Processing Systems, 23, 712-720 [pdf]

Wilson, R. C., & Finkel, L. H. (2009). A neural implementation of the Kalman filter. Advances in Neural Information Processing Systems 22, 2062-2070 [pdf] [supplement] [poster]

Das, S. R., Wilson, R. C., Lazarewicz, M. T., & Finkel, L. H. (2006). Two-stage principal component analysis for gait recognition. 7th IEEE International Conference on Automatic Face & Gesture Recognition (pp. 579-584) [pdf]

Wilson, R. C., Das, S. R., & Finkel, L. H. (2006). Motion as shape: a novel method for recognition & prediction of biological motion. British Machine Vision Conference 69.1-69.10, BMVA Press [pdf]

Wilson, R. C., Geana, A., White, J. M., Ludvig, E. A., & Cohen, J. D. (2013). Exploration strategies in human decision making. Society for Judgement & Decision Making [abstract] [poster]

Wilson, R. C., White, J. M., & Cohen, J. D. (2013). The role of adaptive decision noise in exploration. Society for Neuroscience Abstracts [abstract] [poster]

Lositsky, O., Wilson, R. C., White, J. M., & Cohen, J. D. (2013). Bayesian model of proactive and reactive control in the AX-CPT. Computational Psychiatry [abstract] [poster]

Wilson, R. C., Takahashi, Y. K., Schoenbaum, G., & Niv, Y. (2013). Orbitofrontal cortex as a cognitive map of task space. Neuroeconomics [abstract]

Wilson, R. C., Takahashi, Y. K., Schoenbaum, G., & Niv, Y. (2012). Orbitofrontal cortex as a cognitive map of task space: implications for reversal learning & extinction. Society for Neuroscience Abstracts [abstract] [poster]

Wilson, R. C., Geana, A., White, J. M., Ludvig, E. A., & Cohen, J. D. (2011). Why the grass is greener on the other side: Behavioral evidence for an ambiguity bonus in human exploratory decision-making. Society for Neuroscience Abstracts [abstract] [poster]

Geana, A., Wilson, R. C., White, J. M., Ludvig, E. A., & Cohen, J. D. (2011). Separate roles for reward magnitude & uncertainty in the explore-exploit Dilemma. Society for Neuroscience Abstracts [abstract]

Tomlin, D., Nedic, A., Todd, M. T., Wilson, R. C., Prentice, D. A., Holmes, P., Cohen, J. D. (2011). Group foraging task reveals separable influences of individual experience & social information. Society for Neuroscience Abstracts

Wilson, R. C., Takahashi, Y. K., Schoenbaum, G., & Niv, Y. (2011). What is the role of orbitofrontal cortex in dopamine-dependent reinforcement learning? Computational & Systems Neuroscience [abstract]

Wilson, R. C., Takahashi, Y. K., Roesch, M. R., Stalnaker, T., Schoenbaum, G., & Niv, Y. (2010). A computational model of the role of orbitofrontal cortex & ventral striatum in signaling reward expectancy in reinforcement learning. Society for Neuroscience Abstracts [abstract] [poster]

Wilson, R. C., Cohen, J. D., & Niv, Y. (2010). Inferring relevance in a changing world. Society for Neuroscience Abstracts [abstract] [poster]

Wilson, R. C., Nassar, M. R., & Gold, J. I. (2010). A delta-rule approximation to Bayesian inference in change-point problems. Computational & Systems Neuroscience [abstract] [poster]

Nassar, M. R., Wilson, R. C., Kalwani, R., Heasly, B., & Gold, J. I. (2010). Pupillometric evidence for a role of locus coeruleus in dynamic belief updating. Computational & Systems Neuroscience

Wilson, R. C., Nassar, M. R., & Gold, J. I. (2009). An ideal observer model for optimal inference in the presence of different types of uncertainty. Computational & Systems Neuroscience [abstract]

Wilson, R. C., Das, S. R., & Finkel, L. H. (2008). A neural implementation of predictive coding. Computational & Systems Neuroscience [abstract]

Wilson, R. C. (2007). Parallel Hopfield networks. Computational & Systems Neuroscience [abstract] [poster]

Wilson, R. C., & Hürlimann, M. D. (2006). Relationships between internal field gradients, diffusion & relaxation in porous media. 8th International Bologna Conference on Magnetic Resonance in Porous Media

Wilson, R. C., & Finkel, L. H. (2006). Maximum likelihood decoding of moving stimuli using divisive normalization line attractor neural networks. Computational & Systems Neuroscience [abstract]

Wilson, R. C., Fernandez-Seara, M. A., & Wehrli, F. W. (2004). NMR study of the dynamic properties of bone water. 12th Annual Meeting of the ISMRM [abstract] [poster]