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Multi-voxel pattern analysis (MVPA) has led to major changes in how fMRI data are analyzed and interpreted. Many studies now report both MVPA results and results from standard univariate voxel-wise analysis, often with the goal of drawing different conclusions from each. Because MVPA results can be sensitive to latent multidimensional representations and(More)
Category knowledge can be explicit, yet not conform to a perfect rule. For example, a child may acquire the rule "If it has wings, then it is a bird," but then must account for exceptions to this rule, such as bats. The current study explored the neurobiological basis of rule-plus-exception learning by using quantitative predictions from a category learning(More)
Category learning is a complex phenomenon that engages multiple cognitive processes, many of which occur simultaneously and unfold dynamically over time. For example, as people encounter objects in the world, they simultaneously engage processes to determine their fit with current knowledge structures, gather new information about the objects, and adjust(More)
A prerequisite for a pattern analysis using functional magnetic resonance imaging (fMRI) data is estimating the patterns from time series data, which then are input into the pattern analysis. Here we focus on how the combination of study design (order and spacing of trials) with pattern estimator impacts the Type I error rate of the subsequent pattern(More)
How categories are represented continues to be hotly debated across neuroscience and psychology. One topic that is central to cognitive research on category representation but underexplored in neurobiological research concerns the internal structure of categories. Internal structure refers to how the natural variability between-category members is coded so(More)
Recently, there has been a dramatic increase in the number of functional magnetic resonance imaging studies seeking to answer questions about how the brain represents information. Representational questions are of particular importance in connecting neuroscientific and cognitive levels of analysis because it is at the representational level that many formal(More)
We suggest that human category formation relies on contrastive learning mechanisms that seek to reduce prediction error. In keeping with this view, manipulating category contrast leads to systematic distortions in people's memory for category information. Simply by changing the basis of comparison (i.e., the available response options), we can(More)
Familiarity, or memory strength, is a central construct in models of cognition. In previous categorization and long-term memory research, correlations have been found between psychological measures of memory strength and activation in the medial temporal lobes (MTLs), which suggests a common neural locus for memory strength. However, activation alone is(More)
Anticipatory emotions precede behavioral outcomes and provide a means to infer interactions between emotional and cognitive processes. A number of theories hold that anticipatory emotions serve as inputs to the decision process and code the value or risk associated with a stimulus. We argue that current data do not unequivocally support this theory. We(More)
– Mechatronics is integration of mechanical systems, electronics and intelligent computer control. With advances in computing power, size, and cost, university mechatronics courses can offer more flexible, powerful and up-to-date development environments than traditionally available with prepackaged robotics kits such as the widely used Handy Board(More)