Daniel R. Little

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A recent resurgence in logical-rule theories of categorization has motivated the development of a class of models that predict not only choice probabilities but also categorization response times (RTs; Fifić, Little, & Nosofsky, 2010). The new models combine mental-architecture and random-walk approaches within an integrated framework and predict detailed(More)
According to various influential formal models of cognition, perceptual categorization and old-new recognition recruit the same memory system. By contrast, the prevailing view in the cognitive neuroscience literature is that separate neural systems mediate perceptual categorization and recognition. A direct form of evidence is that separate brain regions(More)
Raven’s Progressive Matrices (Raven, Raven, & Court, 1998) is one of the most prevalent assays of fluid intelligence; however, most theoretical accounts of Raven’s focus on producing models which can generate the correct answer but do not fit human performance data. We provide a computational-level theory which interprets rule induction in Raven’s as(More)
Exemplar-similarity models such as the exemplar-based random walk (EBRW) model (Nosofsky & Palmeri, 1997b) were designed to provide a formal account of multidimensional classification choice probabilities and response times (RTs). At the same time, a recurring theme has been to use exemplar models to account for old-new item recognition and to explain(More)
We formalize and provide tests of a set of logical-rule models for predicting perceptual classification response times (RTs) and choice probabilities. The models are developed by synthesizing mental-architecture, random-walk, and decision-bound approaches. According to the models, people make independent decisions about the locations of stimuli along a set(More)
In this paper, we investigate a new paradigm for studying the development of the colour 'signal' by having observers discriminate and categorize the same set of controlled and calibrated cardinal coloured stimuli. Notably, in both tasks, each observer was free to decide whether two pairs of colors were the same or belonged to the same category. The use of(More)
Despite the fact that categories are often composed of correlated features, the evidence that people detect and use these correlations during intentional category learning has been overwhelmingly negative to date. Nonetheless, on other categorization tasks, such as feature prediction, people show evidence of correlational sensitivity. A conventional(More)
Among the most fundamental results in the area of perceptual classification are the "correlated facilitation" and "filtering interference" effects observed in Garner's (1974) speeded categorization tasks: In the case of integral-dimension stimuli, relative to a control task, single-dimension classification is faster when there is correlated variation along(More)
The relationship between fluid intelligence and working memory is of fundamental importance to understanding how capacity-limited structures such as working memory interact with inference abilities to determine intelligent behavior. Recent evidence has suggested that the relationship between a fluid abilities test, Raven's Progressive Matrices, and working(More)