Memory and Decision Making Lab

Publications

2017

Danileiko, I. & Lee, M.D. (in press). A model-based approach to the wisdom of the crowd in category learning. Cognitive Science. Accepted 13-Sep-2017. [pdf] [osf]

Bennett, S. T., Benjamin, A. S., & Steyvers, M. (2017). A Bayesian model of knowledge and metacognitive control: Applications to opt-in tasks. Submitted to Cognitive Science Society 2017. [pdf]

Guan, H., & Lee, M.D. (in press). The effect of goals and environments on human performance in optimal stopping problems. Decision. [pdf]

Mistry, P.K., Skewes, J., & Lee, M.D. (2017). An Adaptive Signal Detection Model Applied to Understanding Autism Spectrum Disorder. Submitted to Cognitive Science Society 2017. [pdf]

Mistry, P. K., & Trueblood, J. S. (2017). An Investigation of Factors that Influence Resource Allocation Decisions. Submitted to Cognitive Science Society 2017. [pdf]

Sumner, S.E., Stokes, R.C., Mistry, P.K., Jaeggi, S.M., & Sarnecka, B.W. (2017). A freshly baked perspective on how we measure risk propensity in children. Submitted to Cognitive Science Society 2017. [pdf]

2016

Cassey, P. J., Gaut, G., Steyvers, M., & Brown, S. D. (2016). A generative joint model for spike trains and saccades during perceptual decision-making. Psychonomic bulletin & review, 1 -22. DOI:10.3758/s13423-016-1056-z

Gaut, G., Steyvers, M., Imel, Z., Atkins, D., & Smyth, P. (2016). Content coding of psychotherapy transcripts using labeled topic models. IEEE Journal of Biomedical and Health Informatics. PP(99), pp.1. DOI: 10.1109/JBHI.2015.2503985

Danileiko, I., & Lee, M.D. (2016). Inferring individual differences between and within exemplar and decision-bound models of categorization. In J. Trueswell, A. Papafragou, D. Grodner, & D. Mirman (Eds.), Proceedings of the 38th Annual Conference of the Cognitive Science Society. Austin, TX: Cognitive Science Society. [pdf] [osf]

Mistry, P.K., Lee, M.D., & Newell, B.R. (2016). An empirical evaluation of models for how people learn cue search orders. In J. Trueswell, A. Papafragou, D. Grodner, & D. Mirman (Eds.), Proceedings of the 38th Annual Conference of the Cognitive Science Society. Austin, TX: Cognitive Science Society. [pdf] [osf]

Nunez, M. D., Vandekerckhove, J., & Srinivasan, R. (2016). How attention influences perceptual decision making: Single-trial EEG correlates of drift-diffusion model parameters. Journal of Mathematical Psychology. [preprint pdf]

Trueblood, J. S., Mistry, P. K., & Pothos, E. M. (2016). A Quantum Bayes Net Approach to Causal Reasoning. In, E. Dzhafarov, R. Zhang, S. Joardan, and V. Cervantes (Eds.) Contextuality from Quantum Physics to Psychology. (pp. 449-463). World Scientific. [pdf]

Trueblood, J. S. & Mistry, P. K. (in press). Quantum models of human causal reasoning. In, A. Khrennikov and E. Haven (Eds.) The Palgrave Handbook of Quantum Models in Social Science: Applications and Grand Challenges. Palgrave Macmillian. [pdf]

Mistry, P. K., Trueblood, J. S., Vandekerckhove, J. & Pothos, E. M. (submitted). Quantum or Classical causal reasoning? A Bayesian comparison.

2015

Nunez, M.D., Srinivasan, R., & Vandekerckhove, J. (2015). Individual differences in attention influence perceptual decision making. Frontiers in psychology, 8. [pdf]

Danileiko, I., Lee, M.D., & Kalish, M.L. (2015). A Bayesian latent mixture approach to modeling individual differences in categorization using General Recognition Theory. In D.C. Noelle & R. Dale (Eds.), Proceedings of the 37th Annual Conference of the Cognitive Science Society, pp. 501-506. Austin, TX: Cognitive Science Society. [pdf] [supplement]

Mistry, P. K. & Trueblood, J. S. (2015). Reconstructing the Bayesian Adaptive Toolbox: Challenges of a dynamic environment and partial information acquisition. In D. C. Noelle, R. Dale, A. S. Warlaumont, J. Yoshimi, T. Matlock, C. D. Jennings, & P. P. Maglio (Eds.) Proceedings of the 37th Annual Conference of the Cognitive Science Society (pp. 1595-1600). Austin, TX: Cognitive Science Society. [pdf]

Mistry, P. K., Trueblood, J. S., Vandekerckhove, J. & Pothos, E. M. (2015). A latent-mixture quantum probability model of causal reasoning within a Bayesian inference framework. In D. C. Noelle, R. Dale, A. S. Warlaumont, J. Yoshimi, T. Matlock, C. D. Jennings, & P. P. Maglio (Eds.) Proceedings of the 37th Annual Conference of the Cognitive Science Society (pp. 1589-1594). Austin, TX: Cognitive Science Society. [pdf]

2014

Lee, M.D., & Danileiko, I. (2014). Using cognitive models to combine probability estimates. Judgment and Decision Making, 9, 259-273.[pdf] [data1] [data2] [code] [link]