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Considerable behavioral evidence has been cited in support ofthe COVIS dual-system model of category learning (Ashby &Valentin, 2016). The validity of the inferences drawn fromthese data critically depend on the accurate identification ofparticipants’ categorization strategies. In the COVIS literature,participants’ strategies are identified using a model-based anal-ysis inspired by General Recognition Theory (Maddox, 1999).Here, we examine the accuracy of this analysis in a model-recovery simulation. We find that participants can appear tobe using implicit, procedural strategies when their responseswere actually generated by explicit rule-based strategies. Theimplications of this for the COVIS literature are discussed.

Behavioral evidence for the COVIS dual-process model of category learning has been widely reported in over a hundred publications (Ashby & Valentin, 2016). It is generally accepted that the validity of such evidence depends on the accurate identification of individual participants' categorization strategies, a task that usually falls to Decision Bound analysis (Maddox & Ashby, 1993). Here, we examine the accuracy of this analysis in a series of model-recovery simulations. In Simulation 1, over a third of simulated participants using an Explicit (conjunctive) strategy were misidentified as using a Procedural strategy. In Simulation 2, nearly all simulated participants using a Procedural strategy were misidentified as using an Explicit strategy. In Simulation 3, we re-examined a recently reported COVIS-supporting dissociation (Smith et al., 2014]) and found that these misidentification errors permit an alternative, single-process, explanation of the results. Implications for due process in the future evaluation of dual-process theories, including recommendations for future practice, are discussed.

The inverse base rate effect (IBRE) is a nonrational behavioral phenomenon in predictive learning. Canonically, participants learn that the AB stimulus compound leads to one outcome and that AC leads to another outcome, with AB being presented three times as often as AC. When subsequently presented with BC, the outcome associated with AC is preferentially selected, in opposition to the underlying base rates of the outcomes. The current leading explanation is based on error‐driven learning. A key component of this account is prediction error, a concept previously linked to a number of brain areas including the anterior cingulate, the striatum, and the dorsolateral prefrontal cortex. The present work is the first fMRI study to directly examine the IBRE. Activations were noted in brain areas linked to prediction error, including the caudate body, the anterior cingulate, the ventromedial prefrontal cortex, and the right dorsolateral prefrontal cortex. Analyzing the difference in activations for singular key stimuli (B and C), as well as frequency matched controls, supports the predictions made by the error‐driven learning account. [ABSTRACT FROM AUTHOR]

Formal modeling in psychology is failing to live up to its potential due to a lack of effective collaboration. As a first step towards solving this problem, we have produced a set of freely available tools for distributed collaboration. This article describes those tools and the conceptual framework behind them. We also provide concrete examples of how these tools can be used. The approach we propose enhances, rather than supplants, more traditional forms of publication. All the resources for this project are freely available from the catlearn website http//catlearn.r-forge.r-project.org/. [ABSTRACT FROM AUTHOR]