Publications

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Peer Reviewed Journal Articles

2022 and In Press

• Blanco, N., Turner, B. M., and Sloutsky, V. M. (2022). The benefits of immature cognitive control: How distributed attention guards against learning traps. Journal of Experimental Child Psychology, 226, 105548.
• Galdo, M., Weichart, E. R., Sloutsky, V. M., and Turner, B. M. (2022). The Quest for Simplicity in Human Learning: Identifying the Constraints on Attention. Cognitive Psychology, 138, 101508.
  • Supplementary Materials
• Kang, I., Galdo, M., and Turner, B. M. (2022). Constraining Functional Coactivation with a Cluster-based Structural Connectivity Network. Network Neuroscience, 6(4), 1032-1065.
• Kang, I., Yi, W., and Turner, B. M. (2022). A Regularization Method for Linking Brain and Behavior. Psychological Methods, 27(3):400-425.
• Weichart, E. R., Galdo, M. Sloutsky, V. M., and Turner, B. M. (in press). As Within, so Without; As Above, so Below: Common Mechanisms Can Support Between- and Within-Trial Learning Dynamics. In press at Psychological Review.
• Weichart, E. R.*, Evans, D. G.*, Galdo, M., Bahg, G., and Turner, B. M. (2022). Distributed Neural Systems Support Flexible Attention Updating during Category Learning. Journal of Cognitive Neuroscience, 34 (10): 1761–1779. *Joint first authorship.

2021

• Kirkpatrick, R. P., Turner, B. M., and Sederberg, P. B. (2021). Equal Evidence Perceptual Tasks Suggest a Key Role for Interactive Competition in Decision-Making. Psychological Review, 128(6), 1051–1087.
• Kvam, P. D., Romeu, R. J., Turner, B. M., Vassileva, J., and Busemeyer, J. R. (2021). Testing the factor structure underlying behavior using joint cognitive models: Impulsivity in delay discounting and Cambridge gambling tasks. Psychological Methods, 26(1), 18–37.
• Kvam, P. D., and Turner, B. M. (2021). Reconciling similarity across models of continuous selections. Psychological Review, 128(4), 766–786.
• Wang, T., Merkle, E. C., Anguera, J. A., and Turner, B. M. (2021). Score-based Tests for Detecting Heterogeneity in Linear Mixed Models. Behavioral Research Methods. 53, 216-231.
• Weichart, E. R., Darby, K. P., Fenton, A. W., Jacques, B. G., Kirkpatrick, R. P., Turner, B. M., Sederberg, P. B. (2021). Quantifying Mechanisms of Cognition with an Experiment and Modeling Ecosystem. Behavioral Research Methods. 53, 1833–1856.

2020

• Bahg, G., Evans, D., Galdo, M., and Turner, B. M. (2020). Gaussian process linking functions for mind, brain, and behavior. Proceedings of the National Academy of Sciences. 117, 29398-29406
  • First Version (PsyArXiv)
• Bahg, G., Sederberg, P. B., Myung, J. I., Li, X., Pitt, M. A., Lu, Z.-L., and Turner, B. M. (2020). Real-time Adaptive Design Optimization within Functional MRI Experiments. Computational Brain and Behavior, 3(4), 400-429.
• Galdo, M., Bahg, G., and Turner, B. M. (2020). Variational Bayesian methods for cognitive science. Psychological Methods, 25, 535-559.
  • Journal Version
• Haines, N., Beauchaine, T. P., Galdo, M., Rogers, A. H., Hahn, H., Pitt, M. A., Myung, J. I., Turner, B. M., Ahn, W.-Y. (2020). Anxiety modulates preference for immediate rewards among trait-impulsive individuals: A hierarchical Bayesian analysis. Clinical Psychological Science, 8, 1017-1036.
• Liu, Q., Petrov, A. A., Lu, Z.-L., and Turner, B. M. (2020). Extensions of Multivariate Dynamical Systems to simultaneously explain neural and behavioral data. Computational Brain and Behavior, 3(4), 430-457.
• Molloy, M. F., Romeu, R. J., Kvam, P. D., Finn, P. R., Busemeyer, J. R., and Turner, B. M. (2020). Hierarchies improve individual assessment of temporal discounting behavior. Decision, 7, 212-224.
  • Supplementary Materials
• Weichart, E. R., Turner, B. M., and Sederberg, P. B. (2020). A model of dynamic, within-trial conflict resolution for decision making. Psychological Review, 127, 749-777.

2019

• Busemeyer, J., Gluth, S., Rieskamp, J., and Turner, B. M. (2019). Cognitive and neural bases of multi-attribute, multi-alternative, value-based decisions. Trends in Cognitive Science. 23, 251-263.
  • Journal Version
• Gaut, G., Li, X., Turner, B. M., Cunningham, W. A., Lu, Z. L., and Steyvers, M. (2019). Predicting Task and Subject Differences with Functional Connectivity and BOLD Variability. Brain Connectivity, 9 (6).
  • Journal Version
• Molloy, M. F., Bahg, G., Lu, Z.-L., and Turner, B. M. (2019) Individual differences in the neural dynamics of response inhibition. Journal of Cognitive Neuroscience, 31 (12), 1976-1996.
• *Molloy, M. F., *Galdo, M., Bahg, G., Liu, Q., and Turner, B. M. (2019). What’s in a response time?: On the importance of response time measures in constraining models of context effects. Decision, 6, 171-200
  • * indicates equal contribution.
  • Journal Version 
  • Supplementary Materials
• Poldrack, R. A., Feingold, F., Frank, M. J., Gleeson, P., de Hollander, G., Huys, Q. J. M., Love, B. C., Markiewicz, C. J., Moran, R., Ritter, P., Rogers, T. T., Turner, B. M., Yarkoni, T., Zhan, M., Cohen, J. D. (2019). The importance of standards for sharing of computational models and data. Computational Brain and Behavior, 2, 229-232.
  • Journal Version 
  • Link to Special Issue
• Turner, B. M. (2019). Toward a common representational framework for adaptation. Psychological Review. 126, 660-692.
  • Supplementary Material
  • Journal Version
• Turner, B. M., Palestro, J. J., Miletic, S., and Forstmann, B. U. (2019). Advances in techniques for imposing reciprocity in brain-behavior relations. Neuroscience and Biobehavioral Reviews, 102, 327-336.
  • Journal Version

2018

• Molloy, M. F., Bahg, G., Li, X., Steyvers, M., Lu, Z.-L., and Turner, B. M. (2018). Hierarchical Bayesian analyses for modeling BOLD time series data. Computational Brain and Behavior. 2, 184-213.
  • Journal Version
• Palestro, J. J., Bahg, G., Sederberg, P. B., Lu, Z.-L., Steyvers, M., and Turner, B. M. (2018). A tutorial on joint models of neural and behavioral measures of cognition. Journal of Mathematical Psychology. 84, 20-48.
  • Journal Version 
  • Code for tutorial
• Palestro, J. J., Weichart, E., Sederberg, P. B., and Turner, B. M. (2018). Some task demands induce collapsing bounds: Evidence from a behavioral analysis. Psychological Bulletin and Review. 25, 1225-1248.
  • Journal Version 
  • Supplementary Materials
• Turner, B. M., McClelland, J. L., and Busemeyer, J. (2018). Bayesian statistics to assess Bayesian optimality. Behavioral and Brain Sciences. e246.
• Turner, B. M., Miletic, S., and Forstmann, B. U. (2018). Outlook on deep neural networks in computational cognitive modeling. NeuroImage. 180, 117-118.
• Turner, B. M., Rodriguez, C. A., Liu, Q., Molloy, M. F., Hoogendijk, M., and McClure, S. M. (2018). On the neural and mechanistic bases of self-control. Cerebral Cortex. 1-19.
  • Journal Version
• Turner, B. M., Schley, D. R., Muller, C., and Tsetsos, K. (2018). Competing models of multi-attribute, multi-alternative preferential choice. Psychological Review, 125, 329-362.
  • Supplementary Materials
  • Journal Version
• Turner, B. M. and Van Zandt, T. (2018). Approximating Bayesian inference through model simulation. Trends in Cognitive Science. 22, 826-840.
  • Journal Version

2017

• Miletic, S., Turner, B. M., Forstmann, B. U., and Van Maanen, L. (2017). Parameter recovery for the Leaky Competing Accumulator model. Journal of Mathematical Psychology. 76, 25-50.
  • Journal Version
• Palmeri, T. J., Love, B. C., and Turner, B. M. (2017). Model-based cognitive neuroscience. Journal of Mathematical Psychology. 76, 56-64.
  • Journal Version 
  • Special Issues at Journal of Mathematical Psychology
• Turner, B. M., Forstmann, B. U., Love, B. C., Palmeri, T. J., and Van Maanen, L. (2017). Approaches to analysis in model-based cognitive neuroscience. Journal of Mathematical Psychology. 76, 65-79.
  • Journal Version
• Turner, B. M., Gao, J., Koenig, S., Palfy, D., and McClelland, J. L. (2017). The dynamics of multimodal integration: The averaging diffusion model. Psychonomic Bulletin and Review. 24, 1819-1843.
  • Journal Version
• Turner, B. M., Wang, T., and Merkle, E. (2017). Factor analysis linking functions for simultaneously modeling neural and behavioral data. NeuroImage. 153, 28-48.

2016

• Turner, B. M., Rodriguez, C. A., Norcia, T. M., McClure, S. M., and Steyvers, M. (2016). Why more is better: Simultaneous modeling of EEG, fMRI, and behavioral data. NeuroImage, 128, 96-115.
  • Brad Love’s (2016) commentary
• Turner, B. M., and Schley, D. R. (2016). The anchor integration model: A descriptive model of anchoring effects. Cognitive Psychology. 90. 1-47.
  • Journal Version
• Turner, B. M., Sederberg, P. B., and McClelland, J. L. (2016). Bayesian analysis of simulation-based models. Journal of Mathematical Psychology. 72, 191-199.
  • Journal Version

2015

• Rodriguez, C. A., Turner, B. M., Van Zandt, T., and McClure, S. M. (2015). The neural basis of value accumulation in intertemporal choice. European Journal of Neuroscience. 1-11.
  • Journal Version
• Turner, B. M., Van Maanen, L., Forstmann, B. U. (2015). Informing cognitive abstractions through neuroimaging: The Neural Drift Diffusion Model. Psychological Review. 122, 312-336.
  • Journal Version 
  • Supplementary Materials
• Van Maanen, L., Turner, B. M., and Forstmann, B. U. (2015). From model-based perceptual decision-making to spatial interference control. Current Opinion in Behavioral Sciences. 1, 72-77.
  • Journal Version

2014

• Djulbegovic, B. H., Beckstead, J., Reljic, T., Hozo, I., Kumar, A., Cannon-Bowers, J., Taylor, S., Tsalatsanis, A., Turner, B. M., and Paidas, C. (2014). Evaluation of physicians’ cognitive styles. Medical Decision Making. 34, 627-637.
  • Journal Version
• Mittner, M., Boekel, W., Tucker, A. M., Turner, B. M., Heathcote, A., Forstmann, B. U. (2014). When the brain takes a break: A model-based analysis of mind wandering. Journal of Neuroscience. 34, 16286-16295.
• Rodriguez, C. A., Turner, B. M., and McClure, S. M. (2014). Intertemporal choice as discounted value accumulation. PLoS ONE. 9, e90138.
• Steyvers, M., Wallsten, T. S., Merkle, E. C., and Turner, B. M. (2014). Evaluating probabilistic forecasts with Bayesian signal detection models. Risk Analysis. 34, 435-452.
  • Journal Version
• Turner, B. M., and Sederberg, P. B. (2014). A generalized, likelihood-free method for posterior estimation. Psychonomic Bulletin and Review. 21, 227-250.
  • Journal Version 
  • Code
• Turner, B. M., Steyvers, M., Merkle, E. C., Budescu, D. V., and Wallsten, T. S. (2014). Forecast aggregation via re-calibration. Machine Learning. 95, 261-289.
  • Journal Version
• Turner, B. M., and Van Zandt, T. (2014). Hierarchical approximate Bayesian computation. Psychometrika. 79, 185-209.
  • Journal Version

2013

• Turner, B. M., Dennis, S., and Van Zandt, T. (2013). Likelihood-free Bayesian analysis of memory models. Psychological Review. 120, 667-678.
  • Journal Version 
  • Supplementary Materials
• Turner, B. M., Forstmann, B. U., Wagenmakers, E. J., Brown, S. D., Sederberg, P. B., and Steyvers, M. (2013). A Bayesian framework for simultaneously modeling neural and behavioral data. NeuroImage. 72, 193-206.
• Turner, B. M., Sederberg, P. B., Brown, S. D., and Steyvers, M. (2013). A method for efficiently sampling from distributions with correlated dimensions. Psychological Methods. 18, 368-384.
  • Journal Version

2012

• Turner, B. M., Rim, H., Betz, N. and Nygren, T. (2012). The maximization inventory. Judgment and Decision Making. 7, 48-60.
• Turner, B. M., and Sederberg, P. B. (2012). Approximate Bayesian computation with differential evolution. Journal of Mathematical Psychology. 56, 375-385.
  • Journal Version
• Turner, B. M., and Van Zandt, T. (2012). A tutorial on approximate Bayesian computation. Journal of Mathematical Psychology. 56, 69-85.
  • Journal Version

2011

• Betz, N. E., and Turner, B. M. (2011). Using item response theory and adaptive testing in online career assessment. Journal of Career Assessment. 19, 274-286.
  • Journal Version
• Rim, H. B., Turner, B. M., Betz, N. and Nygren, T. (2011). Studies of the dimensionality, correlates, and meaning of measures of the maximizing tendency. Judgment and Decision Making. 6, 565-579.
• Turner, B. M., Van Zandt, T., and Brown, S. (2011). A dynamic, stimulus-driven model of signal detection. Psychological Review. 118, 583-613.
  • Journal Version 
  • Code

2010

• Turner, B. M., Betz, N. E., Edwards, M. C., and Borgen, F. H. (2010). Psychometric examination of an inventory of self-efficacy for the Holland vocational themes using item response theory. Measurement and Evaluation in Counseling and Development. 43, 188-198.
  • Journal Version

2009

• Turner, B. M. (2009). The mathematical process of classification. The Pentagon. 68, 5-16.

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Books

• Forstmann, B. U. and Turner, B. M. (forthcoming). Introduction to model-based cognitive neuroscience. Second Edition.
• Turner, B. M., Forstmann, B. U., and Steyvers, M. (2019). Joint models of neural and behavioral data. Springer: New York.
• Palestro, J. J., Sederberg, P. B., Osth, A. F., Van Zandt, T., and Turner, B. M. (2018). Likelihood-free Bayesian inference in cognitive science. Springer: New York.

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Book Chapters

• Turner, B. M., Bahg, G., Galdo, M., and Liu, Q. (in press). Advancements in joint modeling of neural and behavioral data. In Forstmann, B. U. and Turner, B. M. (Eds.), An introduction to model-based cognitive neuroscience: Second Edition. Springer: New York.
• Ly, A., Boehm, U., Heathcote, A., Turner, B. M., Forstmann, B., Marsman, M., and Matzke, D. (2017). A flexible and efficient hierarchical Bayesian approach to the exploration of individual differences in cognitive-model-based neuroscience. In A. A. Moustafa (Ed.), Computational Models of Brain and Behavior. (pp. 467-480). Wiley Blackwell.
• Turner, B. M. (2015). Constraining cognitive abstractions through Bayesian modeling. In Forstmann, B. U. and Wagenmakers, E.-J. (Eds.), An Introduction to Model-based Cognitive Neuroscience. (pp. 199-220). Springer: New York.

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Theses

• Bahg, G. (2021). The Effects of Personalization on Category Learning. (Unpublished Doctoral Dissertation).
• Liu, Q. (2021). Dynamics of Multi-attribute Decision Making Revealed by Eye-tracking. (Unpublished Doctoral Dissertation).
• Yi, W. (2020). Confidence as a Continuous State of Evidence with Dynamic Competition. (Unpublished Masters Thesis).
• Galdo, M. (2020). Towards a Quantitative Framework for Detecting Transfer of Learning. (Unpublished Masters Thesis).
• Bahg, G. (2018). Adaptive Design Optimization in Functional MRI experiments. (Unpublished Masters Thesis).
• Liu, Q. (2018). Extensions of Multivariate Dynamical Systems for simultaneous explanations of neural and behavioral data. (Unpublished Masters Thesis)
• Molloy, M. F. (2018). Hierarchical Bayesian analysis reveals complex neural dynamics of inhibitory control. (Unpublished Thesis for Research Distinction in Neuroscience).
• Palestro, J. J. (2018). Some tasks demands require collapsing bounds: Evidence from a behavioral analysis. (Unpublished Masters Thesis).
• Turner, B. M. (2011). Likelihood-Free Bayesian Modeling. (Unpublished Doctoral Dissertation).
• Turner, B. M. (2009). Signal detection theory: A proposal for a nonparametric model. (Unpublished Masters Thesis).