Knowledge Partitioning in Categorization: Constraints on Exemplar Models.

The authors present 2 experiments that establish the presence of knowledge partitioning in perceptual categorization. Many participants learned to rely on a context cue, which did not predict category membership but identified partial boundaries, to gate independent partial categorization strategies. When participants partitioned their knowledge, a strategy used in 1 context was unaffected by knowledge demonstrably present in other contexts. An exemplar model, attentional learning covering map, was shown to be unable to accommodate knowledge partitioning. Instead, a mixture-of-experts model, attention to rules and instances in a unified model (ATRIUM), could handle the results. The success of ATRIUM resulted from its assumption that people memorize not only exemplars but also the way in which they are to be classified. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Simplified learning in complex situations: Knowledge partitioning in function learning.

The authors explored the phenomenon that knowledge is not always integrated and consistent but may be partitioned into independent parcels that may contain mutually contradictory information. In 4 experiments, using a function learning paradigm, a binary context variable was paired with the continuous stimulus variable of a to-be-learned function. In the first 2 experiments, when context predicted the slope of a quadratic function, generalization was context specific. Because context did not predict function values, it is suggested that people use context to gate separate learning of simpler partial functions. The 3rd experiment showed that partitioning also occurs with a decreasing linear function, whereas the 4th study showed that partitioning is absent for a linearly increasing function. The results support the notion that people simplify complex learning tasks by acquiring independent parcels of knowledge. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Population of Linear Experts: Knowledge Partitioning and Function Learning.

Knowledge partitioning is a theoretical construct holding that knowledge is not always integrated and homogeneous but may be separated into independent parcels containing mutually contradictory information. Knowledge partitioning has been observed in research on expertise, categorization, and function learning. This article presents a theory of function learning (the population of linear experts model--POLE) that assumes people partition their knowledge whenever they are presented with a complex task. The authors show that POLE is a general model of function learning that accommodates both benchmark results and recent data on knowledge partitioning. POLE also makes the counterintuitive prediction that a person's distribution of responses to repeated test stimuli should be multimodal. The authors report 3 experiments that support this prediction. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Beyond nonutilization: Irrelevant cues can gate learning in probabilistic categorization.

In probabilistic categorization, also known as multiple cue probability learning (MCPL), people learn to predict a discrete outcome on the basis of imperfectly valid cues. In MCPL, normatively irrelevant cues are usually ignored, which stands in apparent conflict with recent research in deterministic categorization that has shown that people sometimes use irrelevant cues to gate access to partial knowledge encapsulated in independent partitions. The authors report 2 experiments that sought support for the existence of such knowledge partitioning in probabilistic categorization. The results indicate that, as in other areas of concept acquisition (such as function learning and deterministic categorization), a significant proportion of participants partitioned their knowledge on the basis of an irrelevant cue. The authors show by computational modeling that knowledge partitioning cannot be accommodated by 2 exemplar models (Generalized Context Model and Rapid Attention Shifts 'N Learning), whereas a rule-based model (General Recognition Theory) can capture partitioned performance. The authors conclude by pointing to the necessity of a mixture-of-experts approach to capture performance in MCPL and by identifying reduction of complexity as a possible explanation for partitioning. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Building object representations from parts: Tests of a stochastic sampling model.

In 2 experiments, the perceptual processing assumptions of the extended generalized context model (EGCM) of categorization were tested. The model assumes that object parts are sampled independently and in parallel in the earliest stages of categorization. In both experiments, participants categorized images of artificial objects under various levels of time pressure. Each participant also categorized partial objects, which were obtained by removing object components. The EGCM assumes that categorization judgments under time pressure can rely on incomplete object representations. The model successfully predicts performance in the speeded categorization task from the classification of partial objects. The results provide strong support for the EGCM, which performed consistently better than 2 alternative models. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The time course of categorization.

The extended generalized context model (EGCM) is presented as a formal model of the time course of categorization of complex stimuli. The model explains the effects of time constraints on categorization. The EGCM accurately accounts for existing data on categorization under time pressure. The model was tested further in 2 experiments. In both experiments, processing time in a perceptual categorization task was restricted by unpredictable peremptory response signals. In Experiment 1, restrictions of processing time had systematic effects on response proportions, and these effects were well explained by the EGCM. Experiment 2 showed that perceptual salience and utility have independent effects on the time course of categorization, as predicted by the EGCM. The EGCM's relation to other models of the time course of categorization is discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Race and gender on the brain: Electrocortical measures of attention to the race and gender of multiply categorizable individuals.

The degree to which perceivers automatically attend to and encode social category information was investigated. Event-related brain potentials were used to assess attentional and working-memory processes on-line as participants were presented with pictures of Black and White males and females. The authors found that attention was preferentially directed to Black targets very early in processing (by about 100 ms after stimulus onset) in both experiments. Attention to gender also emerged early but occurred about 50 ms later than attention to race. Later working-memory processes were sensitive to more complex relations between the group memberships of a target individual and the surrounding social context. These working-memory processes were sensitive to both the explicit categorization task participants were performing as well as more implicit, task-irrelevant categorization dimensions. Results are consistent with models suggesting that information about certain category dimensions is encoded relatively automatically. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Partial knowledge of abstract words in patients with cortical degenerative conditions.

Partial knowledge is a common but rarely studied consequence of damage to conceptual representations and is characterized by the retained ability to retrieve crude, superordinate information but not specific, detailed information about a conceptual entity. Previous studies have described partial knowledge for concrete items particularly following semantic dementia (SD). The present study was designed to investigate the occurrence of partial knowledge effects in the conceptual domain of abstract words. A novel 3-level synonym comprehension test was administered to 9 patients with SD, 20 patients with probable Alzheimer's disease (AD), and 40 healthy control subjects. All subject groups showed weaker performance on tasks requiring a fine specification of word meaning compared with those for which a broad sense of meaning or valence was necessary. However, this gradient of partial knowledge was significantly greater for SD and AD subjects than for controls. These results demonstrate that partial knowledge is a general property of a degraded knowledge base and is not restricted to the concrete word domain. It constitutes a normal phenomenon that is exacerbated in the context of neurodegenerative disease. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A Causal-Model Theory of Conceptual Representation and Categorization.

This article presents a theory of categorization that accounts for the effects of causal knowledge that relates the features of categories. According to causal-model theory, people explicitly represent the probabilistic causal mechanisms that link category features and classify objects by evaluating whether they were likely to have been generated by those mechanisms. In 3 experiments, participants were taught causal knowledge that related the features of a novel category. Causal-model theory provided a good quantitative account of the effect of this knowledge on the importance of both individual features and interfeature correlations to classification. By enabling precise model fits and interpretable parameter estimates, causal-model theory helps place the theory-based approach to conceptual representation on equal footing with the well-known similarity-based approaches. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Visual Search and the Collapse of Categorization.

Categorization researchers typically present single objects to be categorized. But real-world categorization often involves object recognition within complex scenes. It is unknown how the processes of categorization stand up to visual complexity or why they fail facing it. The authors filled this research gap by blending the categorization and visual-search paradigms into a visual-search and categorization task in which participants searched for members of target categories in complex displays. Participants have enormous difficulty in this task. Despite intensive and ongoing category training, they detect targets at near-chance levels unless displays are extremely simple or target categories extremely focused. These results, discussed from the perspectives of categorization and visual search, might illuminate societally important instances of visual search (e.g., diagnostic medical screening). (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Decision boundaries in one-dimensional categorization.

Decision-boundary theories of categorization are often difficult to distinguish from exemplar based theories of categorization. The authors developed a version of the decision-boundary theory, called the single-cutoff model, that can be distinguished from the exemplar theory. The authors present 2 experiments that test this decision-boundary model. The results of both experiments point strongly to the absence of single cutoffs in most participants, and no participant displayed use of the optimal boundary. The range of nonoptimal solutions shown by individual participants was accounted for by an exemplar-based adaptive-learning model. When combined with the results of previous research, this suggests that a comprehensive model of categorization must involve both rules and exemplars, and possibly other representations as well. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Integrating Novel Dimensions to Eliminate Category Exceptions: When More Is Less.

Category learning can be characterized as a process of discovering the dimensions that represent stimuli efficiently and effectively. Categories that are overlapping when represented in 1 dimensionality may be separate in a higher dimensional cue set. The authors report 2 experiments in which participants were shown an additional cue after learning to use 2 imperfect cues. The results revealed that participants can integrate new information into their categorization cue set. The authors discovered wide individual differences, however, with many participants favoring simpler, but less accurate, cue sets. Some participants demonstrated the ability to discard information previously used when new, more accurate information was introduced. The categorization model RASHNL (J. K. Kruschke & M. K. Johansen, 1999) gave qualitatively accurate fits of the data. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The GSR in the detection of guilt.

How accurate is a lie detector in determining guilt? "Forty-nine male college students, after random assortment into four groups, were required to enact one, both, or neither of two mock crimes. All were then given a guilty knowledge test, employing the GSR, which used six standard questions relating to each of the two crimes. A simple, objective, and a priori scoring system was used to determine guilt. Forty-four or 89.8% of the Ss were assigned to their correct group, against a chance expectancy of 25%. Considering the crimes separately, all Ss innocent of a crime were correctly classified, while 44 or 50 interrogations of guilty Ss gave guilty classifications, a total of 93.9% correct classification against a chance expectancy of 50%… . Detection of guilty knowledge… is demonstrably capable of very high validity in those situations where it can be used." (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Categorization of novel animals by patients with Alzheimer's disease and corticobasal degeneration.

We taught a novel animal category by rule-based and similarity-based processes to participants with Alzheimer's disease (AD), corticobasal degeneration (CBD), and healthy age-matched participants. Healthy participants successfully categorized by either process. AD patients' rule-based categorization was impaired, while their similarity-based categorization resembled that of healthy participants. Correlations of AD patients' performance with measures of executive functioning suggested a deficit in the cognitive resources necessary for engaging rule-based categorization. The contribution of limited executive resources to categorization difficulty in AD was further demonstrated in a second experiment in which features determining category membership were of lower salience. CBD patients were relatively impaired at similarity-based processing, suggesting that qualitatively distinct categorization processes can be selectively compromised in patients with focal neurodegenerative diseases. Moreover, AD patients' impaired categorization correlated with performance on a measure of semantic memory, implicating this categorization deficit in AD patients' semantic memory difficulty. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Problem structure and the use of base-rate information from experience.

This article is concerned with the use of base-rate information that is derived from experience in classifying examples of a category. The basic task involved simulated medical decision making in which participants learned to diagnose hypothetical diseases on the basis of symptom information. Alternative diseases differed in their relative frequency or base rates of occurrence. In five experiments initial learning was followed by a series of transfer tests designed to index the use of base-rate information. On these tests, patterns of symptoms were presented that suggested more than one disease and were therefore ambiguous. The results reveal a consistent but complex pattern. Depending on the category structure and the nature of the ambiguous tests, participants use base-rate information appropriately, ignore base-rate information, or use base-rate information inappropriately (predict that the rare disease is more likely to be present). To our knowledge, no current categorization model predicts this pattern of results. To account for these results, a new model is described incorporating the ideas of property or symptom competition and context-sensitive retrieval. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A rose by any other name is not the same: The role of orthographic knowledge in homophone confusion errors.

Homophone confusion errors were examined in a series of 6 experiments. Across a variety of tasks, readers consistently made more errors on homophone trials than on control trials. These effects were established in Experiment 1 using a semantic-decision task in which participants judged whether pairs of words were related or unrelated. For both related and unrelated trials, error rates were higher for homophones as compared with controls. Results such as these have previously been taken as evidence for the role of phonology in lexical access and reading. However, differences in orthographic knowledge (more specifically, knowledge of spelling-to-meaning correspondences) across participants and homophone items significantly predicted homophone errors across all tasks. In addition, spelling tasks and multiple-choice questionnaires revealed differences in orthographic knowledge across participants and homophone items. Although these results do not rule out a role for phonology in lexical access, they indicate that homophone confusion errors may also be due to factors other than phonology. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Accentuation and sensitization effects in the categorization of multifaceted stimuli.

Categorization affects perceptions in ways that are assumed to underlie social stereotypes. Research on categorization, however, has focused either on very simple stimuli or on judgmental tasks that focus attention only on single dimensions. To more fully understand the role of categorization in social perception, it is important to examine its effects in the case of multifaceted stimuli and holistic judgments. In 3 studies, participants formed an impression of a focal category of multifaceted stimuli either by itself or in the context of another category. They then judged the typicality of exemplars to the focal category. Results showed that categorization in the presence of a context produced both accentuation and sensitization effects: Participants accentuated between-category differences on relevant dimensions, and they were less sensitive to exemplar differences on irrelevant dimensions. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Object naming and semantic knowledge in temporal lobe epilepsy.

Object-naming impairment is common among temporal lobe epilepsy (TLE) patients, but other aspects of semantic memory have received limited attention in this population. This study examined object-naming ability and depth of semantic knowledge in healthy controls (n?=?29) and patients with early onset TLE (n?=?21). After administration of the Boston Naming Test (BNT), the authors asked participants to provide detailed definitions of 6 BNT objects. The TLE group demonstrated a significant deficit relative to controls in both object-naming ability and semantic knowledge for the target objects, even after controlling for IQ. In a multiple regression analysis that included other neuropsychological test scores as independent variables, the semantic knowledge score was the only significant predictor of patients' object-naming performance. Thus, at the group level, early onset TLE patients have a semantic knowledge deficit that contributes to dysnomia. (PsycINFO Database Record (c) 2010 APA, all rights reserved)