Refining the visual-cortical hypothesis in category learning

An Eye-Tracking Study of Multiple Feature Value Category Structure Learning: The Role of Unique Features

We examined whether the degree to which a feature is uniquely characteristic of a category can affect categorization above and beyond the typicality of the feature. We developed a multiple feature value category structure with different dimensions within which feature uniqueness and typicality could be manipulated independently. Using eye tracking, we found that the highest attentional weighting (operationalized as number of fixations, mean fixation time, and the first fixation of the trial) was given to a dimension that included a feature that was both unique and highly typical of the category. Dimensions that included features that were highly typical but not unique, or were unique but not highly typical, received less attention. A dimension with neither a unique nor a highly typical feature received least attention. On the basis of these results we hypothesized that subjects categorized via a rule learning procedure in which they performed an ordered evaluation of dimensions, beginning with unique and strongly typical dimensions, and in which earlier dimensions received higher weighting in the decision. This hypothesis accounted for performance on transfer stimuli better than simple implementations of two other common theories of category learning, exemplar models and prototype models, in which all dimensions were evaluated in parallel and received equal weighting.

A parametric investigation of pattern separation processes in the medial temporal lobe

The hippocampus is thought to be involved in memory formation and consolidation, with computational models proposing the process of pattern separation as a means for encoding overlapping memories. Previous research has used semantically related targets and lures to investigate hippocampal responses to mnemonic interference. Here, we attempted to define the response function of the human hippocampus and its inputs during pattern separation by parametrically varying target-lure similarity in a continuous recognition task. We also investigated the effect of task demands (intentional vs incidental encoding) on pattern separation processes. We collected functional magnetic resonance imaging data while participants were shown a series of objects. In the intentional paradigm, participants identified objects as "new" (novel stimuli), "old" (exact repetitions), or "rotated" (previously seen objects that were subsequently rotated by varied degrees). In the incidental paradigm, participants were shown the same stimuli but identified objects as "toy" or "not toy." Activation in the hippocampus was best fit with a power function, consistent with predictions made by computational models of pattern separation processes in the hippocampus. The degree of pattern separation was driven by the information most relevant to the task: pattern separation was seen in the left hippocampus when semantic information was more important to the task and seen in the right hippocampus when spatial information was more important. We also present data illustrating that top-down processes modulate activity in the ventral visual processing stream.

Perceptual fluency can be used as a cue for categorization decisions

Learning in the prototype distortion task is thought to involve perceptual learning in which category members experience an enhanced visual response (Ashby & Maddox. Annual Review of Psychology, 56, 149-178, 2005). This response likely leads to more-efficient processing, which in turn may result in a feeling of perceptual fluency for category members. We examined the perceptual-fluency hypothesis by manipulating fluency independently from category membership. We predicted that when perceptual fluency was induced using subliminal priming, this fluency would be misattributed to category membership and would affect categorization decisions. In a prototype distortion task, the participants were more likely to judge stimuli that were not members of the category as category members when the nonmembers were made perceptually fluent with a matching subliminal prime. This result suggests that perceptual fluency can be used as a cue during some categorization decisions. In addition, the results provided converging evidence that some types of categorization are based on perceptual learning.