The book presents the case that cognitive science should turn its attention to developing theories of human cognition that cover the full range of human perceptual, cognitive, and action phenomena. Cognitive science has now produced a massive number of high-quality regularities with many microtheories that reveal important mechanisms. The need for integration is pressing and will continue to increase. Equally important, cognitive science now has the theoretical concepts and tools to support serious attempts at unified theories. The argument is made (...) entirely by presenting an exemplar unified theory of cognition both to show what a real unified theory would be like and to provide convincing evidence that such theories are feasible. The exemplar is SOAR, a cognitive architecture, which is realized as a software system. After a detailed discussion of the architecture and its properties, with its relation to the constraints on cognition in the real world and to existing ideas in cognitive science, SOAR is used as theory for a wide range of cognitive phenomena: immediate responses ; discrete motor skills ; memory and learning ; problem solving ; language ; and development. The treatments vary in depth and adequacy, but they clearly reveal a single, highly specific, operational theory that works over the entire range of human cognition, SOAR is presented as an exemplar unified theory, not as the sole candidate. Cognitive science is not ready yet for a single theory – there must be multiple attempts. But cognitive science must begin to work toward such unified theories. (shrink)

Considerable evidence supports the sequential two-system model of moral judgement, as proposed by Greene and others. We tested whether judgement speed and/or personal/impersonal moral dilemmas can predict the kind of moral judgements subjects make for each dilemma, and whether personal dilemmas create difficulty in moral judgements. Our results showed that neither personal/impersonal conditions nor spontaneous/thoughtful-reflection conditions were reliable predictors of utilitarian or deontological moral judgements. Yet, we found support for an alternative view, in which, when the two types of responses (...) are in conflict; the resolution of this conflict depends on both the subject and the dilemma. While thinking about this conflict, subjects sometimes change their minds in both directions, as suggested by the data from a mouse-tracking task. (shrink)

The “self” shapes the way in which we process the world around us. It makes sense then, that self-related information is reliably prioritised over non self-related information in cognition. How mig...

Diffusion models are widely-used and successful accounts of the time course of two-choice decision making. Most diffusion models assume constant boundaries, which are the threshold levels of evidence that must be sampled from a stimulus to reach a decision. We summarize theoretical results from statistics that relate distributions of decisions and response times to diffusion models with time-varying boundaries. We then develop a computational method for finding time-varying boundaries from empirical data, and apply our new method to two problems. The (...) first problem involves finding the time-varying boundaries that make diffusion models equivalent to the alternative sequential sampling class of accumulator models. The second problem involves finding the time-varying boundaries, at the individual level, that best fit empirical data for perceptual stimuli that provide equal evidence for both decision alternatives. We discuss the theoretical and modeling implications of using time-varying boundaries in diffusion models, as well as the limitations and potential of our approach to their inference. (shrink)

Individuals with high anxiety show bias for threatening information, but it is unclear whether this bias affects memory. Recognition memory studies have shown biases for recognising and rejecting threatening items in anxiety, prompting the need to identify moderating factors of this effect. This study focuses on the role of semantic similarity: the use of many semantically related threatening words could increase familiarity for those items and obscure anxiety-related differences in memory. To test this, two recognition memory experiments varied the proportion (...) of threatening words in lists to manipulate the semantic-similarity effects. When similarity effects were reduced, participants with high trait anxiety were biased to respond “new” to threatening words, whereas when similarity effects were strong there was no effect of anxiety on memory bias. Analysis of the data with the drift diffusion model showed that the bias was due to differences in processing of the threatening stimuli rather than a simple response bias. These data suggest that the semantic similarity of the threatening words significantly affects the presence or absence of anxiety-related threat bias in recognition memory. The results indicate that trait anxiety is associated with a bias to decide that threatening stimuli were not previously studied, but only when semantic-similarity effects are controlled. Implications for theories of anxiety and future studies in this domain are discussed. (shrink)