Henrik Olsson

Exemplar effects in categorization and multiple-cue judgment.

Categorization and multiple-cue judgment are similar tasks, but the influential models in the two areas are different in terms of the computations, processes, and neural substrates that they imply. In categorization, exemplar memory is often emphasized, whereas multiple-cue judgment generally is interpreted in terms of integration of cues that have been abstracted in training. In 3 experiments the authors investigated whether these conclusions derive from genuine differences in the processes or are accidental to the different research methods. The results revealed large individual differences and a shift from exemplar memory to cue abstraction when the criterion is changed from a binary to a continuous variable, especially for a probabilistic criterion. People appear to switch between qualitatively distinct processes in the 2 tasks.

Information integration in multiple cue judgment: a division of labor hypothesis.

There is considerable evidence that judgment is constrained to additive integration of information. The authors propose an explanation of why serial and additive cognitive integration can produce accurate multiple cue judgment both in additive and non-additive environments in terms of an adaptive division of labor between multiple representations. It is hypothesized that, whereas the additive, independent linear effect of each cue can be explicitly abstracted and integrated by a serial, additive judgment process, a variety of sophisticated task properties, like non-additive cue combination, non-linear relations, and inter-cue correlation, are carried implicitly by exemplar memory. Three experiments investigating the effect of additive versus non-additive cue combination verify the predicted shift in cognitive representations as a function of the underlying combination rule.

Cue abstraction and exemplar memory in categorization

In this article, the authors compare 3 generic models of the cognitive processes in a categorization task. The cue abstraction model implies abstraction in training of explicit cue-criterion relations that are mentally integrated to form a judgment, the lexicographic heuristic uses only the most valid cue, and the exemplar-based model relies on retrieval of exemplars. The results from 2 experiments showed that, in lieu of the lexicographic heuristic, most participants spontaneously integrate cues. In contrast to single-system views, exemplar memory appeared to dominate when the feedback was poor, but when the feedback was rich enough to allow the participants to discern the task structure, it was exploited for abstraction of explicit cue-criterion relations.

Type of learning task impacts performance and strategy selection in decision making.

In order to be adaptive, cognition requires knowledge about the statistical structure of the environment. We show that decision performance and the selection between cue-based and exemplar-based inference mechanisms can depend critically on how this knowledge is acquired. Two types of learning tasks are distinguished: learning by comparison, by which the decision maker learns which of two objects has a higher criterion value, and direct criterion learning, by which the decision maker learns an objects criterion value directly. In three experiments, participants were trained either with learning by comparison or with direct criterion learning and subsequently tested with paired-comparison, classification, and estimation tasks. Experiments 1 and 2 showed that although providing less information, learning by comparison led to better generalization (at test), both when generalizing to new objects and when the task format at test differed from the task format during training. Moreover, learning by comparison enabled participants to provide rather accurate continuous estimates. Computational modeling suggests that the advantage of learning by comparison is due to differences in strategy selection: whereas direct criterion learning fosters the reliance on exemplar processing, learning by comparison fosters cue-based mechanisms. The pattern in decision performance reversed when the task environment was changed from a linear (Experiments 1 and 2) to a nonlinear structure (Experiment 3), where direct criterion learning led to better decisions. Our results demonstrate the critical impact of learning conditions for the subsequent selection of decision strategies and highlight the key role of comparison processes in cognition.

Beyond the null ritual : Formal modeling of psychological processes

Rituals shape many aspects of our lives, and they are no less common in scientific research than elsewhere. One that figures prominently in hypothesis testing is the null ritual, the pitting of hypotheses against chance. Although known to be problematic, this practice is still widely used. One way to resist the lure of the null ritual is to increase the precision of theories by casting them as formal models. These can be tested against each other, instead of against chance, which in turn enables a researcher to decide between competing theories based on quantitative measures. This article gives an overview of the advantages of modeling, describes research that is based on it, outlines the difficulties associated with model testing, and summarizes some of the solutions for dealing with these difficulties. Pointers to resources for teaching modeling in university classes are provided.

Mapping the structure of semantic memory

Aggregating snippets from the semantic memories of many individuals may not yield a good map of an individuals semantic memory. The authors analyze the structure of semantic networks that they sampled from individuals through a new snowball sampling paradigm during approximately 6 weeks of 1-hr daily sessions. The semantic networks of individuals have a small-world structure with short distances between words and high clustering. The distribution of links follows a power law truncated by an exponential cutoff, meaning that most words are poorly connected and a minority of words has a high, although bounded, number of connections. Existing aggregate networks mirror the individual link distributions, and so they are not scale-free, as has been previously assumed; still, there are properties of individual structure that the aggregate networks do not reflect. A simulation of the new sampling process suggests that it can uncover the true structure of an individuals semantic memory.

Social Sampling Explains Apparent Biases in Judgments of Social Environments

How people assess their social environments plays a central role in how they evaluate their life circumstances. Using a large probabilistic national sample, we investigated how accurately people estimate characteristics of the general population. For most characteristics, people seemed to underestimate the quality of others’ lives and showed apparent self-enhancement, but for some characteristics, they seemed to overestimate the quality of others’ lives and showed apparent self-depreciation. In addition, people who were worse off appeared to enhance their social position more than those who were better off. We demonstrated that these effects can be explained by a simple social-sampling model. According to the model, people infer how others are doing by sampling from their own immediate social environments. Interplay of these sampling processes and the specific structure of social environments leads to the apparent biases. The model predicts the empirical results better than alternative accounts and highlights the importance of considering environmental structure when studying human cognition.

Knowledge, attitudes and practice about malaria in rural Tigray, Ethiopia

Objective: To assess the knowledge, attitude and practice (KAP) regarding malaria and their determinants in a rural population of northern Ethiopia. Methods: The study was conducted in the district of Samre Saharti, Tigray, northern Ethiopia. A structured questionnaire collecting socio-demographic and malaria-related KAP information was administered to the mothers from a representative sample of households. Results: A total of 1652 questionnaires were available for analysis. Most of the respondents (92.7%) were able to mention at least one symptom of malaria. Mosquito as a cause of malaria was recognized by nearly half of the respondents (48.8%). Most of the households had a bednet (85.9%). To have a literate person at home, to belong to the lowland stratum, to have received some type of health education and to own a radio were associated with the knowledge of malaria. A strong association remained between living in the lowland stratum, to own a radio and to live close to the health post and the use of ITN. Being a housewife, lack of health education and to live further than 60 minutes walking distance to the health post were related to a delay on treatment finding. Conclusion: This study has identified some aspects which the MCP might need to improve. The knowledge about malaria transmission should be strengthened. Promotion of literacy and participation in health education are vital components in terms of malaria knowledge and practice. Issues related to geographical location and accessibility to health post should be also carefully examined.

The cognitive substrate of subjective probability.

The prominent cognitive theories of probability judgment were primarily developed to explain cognitive biases rather than to account for the cognitive processes in probability judgment. In this article the authors compare 3 major theories of the processes and representations in probability judgment: the representativeness heuristic, implemented as prototype similarity, relative likelihood, or evidential support accumulation (ESAM; D. J. Koehler, C. M. White, & R. Grondin, 2003); cue-based relative frequency; and exemplar memory, implemented by probabilities from exemplars (PROBEX; P. Juslin & M. Persson, 2002). Three experiments with different task structures consistently demonstrate that exemplar memory is the best account of the data whereas the results are inconsistent with extant formulations of the representativeness heuristic and cue-based relative frequency.

Do children profit from looking beyond looks? From similarity-based to cue abstraction processes in multiple-cue judgment

The authors investigated the ability of 9- to 11-year-olds and of adults to use similarity-based and rule-based processes as a function of task characteristics in a task that can be considered either a categorization task or a multiple-cue judgment task, depending on the nature of the criterion (binary vs. continuous). Both children and adults relied on similarity-based processes in the categorization task. However, adults relied on cue abstraction in the multiple-cue judgment task, whereas the majority of children continued to rely on similarity-based processes. Reliance on cue abstraction resulted in better judgments for adults but not for children in the multiple-cue judgment task. This suggests that 9- to 11-year-olds may have defaulted to similarity-based processes because they were not able to employ a cue abstraction process efficiently.