Avoidance is a key characteristic of adaptive and maladaptive fear. Here, we review past and contemporary theories of avoidance learning. Based on the theories, experimental findings and clinical observations reviewed, we distill key principles of how adaptive and maladaptive avoidance behavior is acquired and maintained. We highlight clinical implications of avoidance learning theories and describe intervention strategies that could reduce maladaptive avoidance and prevent its return. We end with a brief overview of recent developments and avenues for further research.

Most data analyses rely on models. To complement statistical models, psychologists have developed cognitive models, which translate observed variables into psychologically interesting constructs. Response time models, in particular, assume that response time and accuracy are the observed expression of latent variables including 1) ease of processing, 2) response caution, 3) response bias, and 4) non-decision time. Inferences about these psychological factors hinge upon the validity of the models' parameters. Here, we use a blinded, collaborative approach to assess the validity of such model-based inferences. Seventeen teams of researchers analyzed the same 14 data sets. In each of these two-condition data sets, we manipulated properties of participants' behavior in a two-alternative forced choice task. The contributing teams were blind to the manipulations, and had to infer what aspect of behavior was changed using their method of choice. The contributors chose to employ a variety of models, estimation methods, and inference procedures. Our results show that, although conclusions were similar across different methods, these "modeler's degrees of freedom" did affect their inferences. Interestingly, many of the simpler approaches yielded as robust and accurate inferences as the more complex methods. We recommend that, in general, cognitive models become a typical analysis tool for response time data. In particular, we argue that the simpler models and procedures are sufficient for standard experimental designs. We finish by outlining situations in which more complicated models and methods may be necessary, and discuss potential pitfalls when interpreting the output from response time models.

Fear conditioning is one of the prime paradigms of behavioural neuroscience and a source of tremendous insight in the fundamentals of learning and memory and the psychology and neurobiology of emotion. It is also widely regarded as a model for the pathogenesis of anxiety disorders in a diathesis-stress model of psychopathology. Starting from the apparent paradox between the adaptive nature of fear conditioning and the dysfunctional nature of pathological anxiety, we present a critique of the human fear conditioning paradigm as an experimental model for psychopathology. We discuss the potential benefits of expanding the human fear conditioning paradigm by (1) including action tendencies as an important index of fear and (2) paying more attention to "weak" (i.e., ambiguous) rather than "strong" fear learning situations (Lissek et al., 2006), such as contained in selective learning procedures. We present preliminary data that illustrate these ideas and discuss the importance of response systems divergence in understanding individual differences in vulnerability for the development of pathological anxiety.

In a classic 1978 Memory &Cognition article, Geoff Loftus explained why noncrossover interactions are removable. These removable interactions are tied to the scale of measurement for the dependent variable and therefore do not allow unambiguous conclusions about latent psychological processes. In the present article, we present concrete examples of how this insight helps prevent experimental psychologists from drawing incorrect conclusions about the effects of forgetting and aging. In addition, we extend the Loftus classification scheme for interactions to include those on the cusp between removable and nonremovable. Finally, we use various methods (i.e., a study of citation histories, a questionnaire for psychology students and faculty members, an analysis of statistical textbooks, and a review of articles published in the 2008 issue of Psychology andAging) to show that experimental psychologists have remained generally unaware of the concept of removable interactions. We conclude that there is more to interactions in a 2 × 2 design than meets the eye.

With the discovery of the blocking effect, learning theory took a huge leap forward, because blocking provided a crucial clue that surprise is what drives learning. This in turn stimulated the development of novel association-formation theories of learning. Eventually, the ability to explain blocking became nothing short of a touchstone for the validity of any theory of learning, including propositional and other nonassociative theories. The abundance of publications reporting a blocking effect and the importance attributed to it suggest that it is a robust phenomenon. Yet, in the current article we report 15 failures to observe a blocking effect despite the use of procedures that are highly similar or identical to those used in published studies. Those failures raise doubts regarding the canonical nature of the blocking effect and call for a reevaluation of the central status of blocking in theories of learning. They may also illustrate how publication bias influences our perspective toward the robustness and reliability of seemingly established effects in the psychological literature.