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  1. Helen Steingroever & Eric-Jan Wagenmakers (2014). Performance and Awareness in the Iowa Gambling Task. Behavioral and Brain Sciences 37 (1):41-42.
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  2. Dora Matzke, Jonathon Love, Thomas V. Wiecki, Scott D. Brown, Gordon D. Logan & Eric-Jan Wagenmakers (2013). Release the BEESTS: Bayesian Estimation of Ex-Gaussian STop-Signal Reaction Time Distributions. Frontiers in Psychology 4.
    The stop-signal paradigm is frequently used to study response inhibition. In this paradigm, participants perform a two-choice response time task where the primary task is occasionally interrupted by a stop-signal that prompts participants to withhold their response. The primary goal is to estimate the latency of the unobservable stop response (stop signal reaction time or SSRT). Recently, Matzke, Dolan, Logan, Brown, and Wagenmakers (in press) have developed a Bayesian parametric approach that allows for the estimation of the entire distribution of (...)
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  3. Helen Steingroever, Ruud Wetzels & Eric-Jan Wagenmakers (2013). Validating the PVL-Delta Model for the Iowa Gambling Task. Frontiers in Psychology 4:898.
    Decision-making deficits in clinical populations are often assessed with the Iowa gambling task (IGT). Performance on this task is driven by latent psychological processes, the assessment of which requires an analysis using cognitive models. Two popular examples of such models are the Expectancy Valence (EV) and Prospect Valence Learning (PVL) models. These models have recently been subjected to sophisticated procedures of model checking, spawning a hybrid version of the EV and PVL models—the PVL-Delta model. In order to test the validity (...)
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  4. Guy Hawkins, Scott D. Brown, Mark Steyvers & Eric-Jan Wagenmakers (2012). Context Effects in Multi-Alternative Decision Making: Empirical Data and a Bayesian Model. Cognitive Science 36 (3):498-516.
    For decisions between many alternatives, the benchmark result is Hick's Law: that response time increases log-linearly with the number of choice alternatives. Even when Hick's Law is observed for response times, divergent results have been observed for error rates—sometimes error rates increase with the number of choice alternatives, and sometimes they are constant. We provide evidence from two experiments that error rates are mostly independent of the number of choice alternatives, unless context effects induce participants to trade speed for accuracy (...)
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  5. Marieke Jepma, Eric-Jan Wagenmakers & Sander Nieuwenhuis (2012). Temporal Expectation and Information Processing: A Model-Based Analysis. Cognition 122 (3):426-441.
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  6. Eric-Jan Wagenmakers, Han L. J. van der Maas & Simon Farrell (2012). Abstract Concepts Require Concrete Models: Why Cognitive Scientists Have Not Yet Embraced Nonlinearly Coupled, Dynamical, Self-Organized Critical, Synergistic, Scale-Free, Exquisitely Context-Sensitive, Interaction-Dominant, Multifractal, Interdependent Brain-Body-Niche Systems. Topics in Cognitive Science 4 (1):87-93.
    After more than 15 years of study, the 1/f noise or complex-systems approach to cognitive science has delivered promises of progress, colorful verbiage, and statistical analyses of phenomena whose relevance for cognition remains unclear. What the complex-systems approach has arguably failed to deliver are concrete insights about how people perceive, think, decide, and act. Without formal models that implement the proposed abstract concepts, the complex-systems approach to cognitive science runs the danger of becoming a philosophical exercise in futility. The complex-systems (...)
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  7. Denny Borsboom, Eric-Jan Wagenmakers & Jan-Willem Romeijn (2011). Mechanistic Curiosity Will Not Kill the Bayesian Cat. Behavioral and Brain Sciences 34 (4):192-193.
    Jones & Love (J&L) suggest that Bayesian approaches to the explanation of human behavior should be constrained by mechanistic theories. We argue that their proposal misconstrues the relation between process models, such as the Bayesian model, and mechanisms. While mechanistic theories can answer specific issues that arise from the study of processes, one cannot expect them to provide constraints in general.
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  8. Gilles Dutilh, Eric-Jan Wagenmakers, Ingmar Visser & Han L. J. van der Maas (2011). A Phase Transition Model for the Speed-Accuracy Trade-Off in Response Time Experiments. Cognitive Science 35 (2):211-250.
    Most models of response time (RT) in elementary cognitive tasks implicitly assume that the speed-accuracy trade-off is continuous: When payoffs or instructions gradually increase the level of speed stress, people are assumed to gradually sacrifice response accuracy in exchange for gradual increases in response speed. This trade-off presumably operates over the entire range from accurate but slow responding to fast but chance-level responding (i.e., guessing). In this article, we challenge the assumption of continuity and propose a phase transition model for (...)
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  9. Birte U. Forstmann, Eric-Jan Wagenmakers, Tom Eichele, Scott Brown & John T. Serences (2011). Reciprocal Relations Between Cognitive Neuroscience and Formal Cognitive Models: Opposites Attract? Trends in Cognitive Sciences 15 (6):272-279.
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  10. Don van Ravenzwaaij, Scott Brown & Eric-Jan Wagenmakers (2011). An Integrated Perspective on the Relation Between Response Speed and Intelligence. Cognition 119 (3):381-393.
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  11. Marieke Jepma, Erik T. Te Beek, Eric-Jan Wagenmakers, Joop Van Gerven & Sander Nieuwenhuis (2010). The Role of the Noradrenergic System in the Exploration-Exploitation Trade-Off: A Pharmacological Study. Frontiers in Human Neuroscience 4:170.
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  12. Eric-Jan Wagenmakers (2009). How Do Individuals Reason in the Wason Card Selection Task? Behavioral and Brain Sciences 32 (1):104-104.
    The probabilistic approach to human reasoning is exemplified by the information gain model for the Wason card selection task. Although the model is elegant and original, several key aspects of the model warrant further discussion, particularly those concerning the scope of the task and the choice process of individuals.
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  13. Richard M. Shiffrin, Michael D. Lee, Eric-Jan Wagenmakers & W. J. Kim (2008). Model Evaluation and Selection: Established Methods and Recent Developments. Cognitive Science 32.
     
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