People fixate on blank spaces if visual stimuli previously occupied these regions of space. This so-called "looking at nothing" (LAN) phenomenon is said to be a part of information retrieval from internal memory representations, but the exact nature of the relationship between LAN and memory retrieval is unclear. While evidence exists for an influence of LAN on memory retrieval for visuospatial stimuli, evidence for verbal information is mixed. Here, we tested the relationship between LAN behavior and memory retrieval in an episodic retrieval task where verbal information was presented auditorily during encoding. When participants were allowed to gaze freely during subsequent memory retrieval, LAN occurred, and it was stronger for correct than for incorrect responses. When eye movements were manipulated during memory retrieval, retrieval performance was higher when participants fixated on the area associated with to-be-retrieved information than when fixating on another area. Our results provide evidence for a functional relationship between LAN and memory retrieval that extends to verbal information.

In the field of diagnostic reasoning, it has been argued that memory activation can provide the reasoner with a subset of possible explanations from memory that are highly adaptive for the task at hand. However, few studies have experimentally tested this assumption. Even less empirical and theoretical work has investigated how newly incoming observations affect the availability of explanations in memory over time. In this article we present the results of 2 experiments in which we address these questions. While participants diagnosed sequentially presented medical symptoms, the availability of potential explanations in memory was measured with an implicit probe reaction time task. The results of the experiments were used to test 4 quantitative cognitive models. The models share the general assumption that observations can activate and inhibit explanations in memory. They vary with respect to how newly incoming observations affect the availability of explanations over time. The data of both experiments were predicted best by a model in which all observations in working memory have the same potential to activate explanations from long-term memory and in which these observations do not decay. The results illustrate the power of memory activation processes and show where additional deliberate reasoning strategies might come into play.

A framing bias shows risk aversion in problems framed as "gains" and risk seeking in problems framed as "losses," even when these are objectively equivalent and probabilities and outcomes values are explicitly provided. We test this framing bias in situations where decision makers rely on their own experience, sampling the problem's options (safe and risky) and seeing the outcomes before making a choice. In Experiment 1, we replicate the framing bias in description-based decisions and find risk indifference in gains and losses in experience-based decisions. Predictions of an Instance-Based Learning model suggest that objective probabilities as well as the number of samples taken are factors that contribute to the lack of framing effect. We test these two factors in Experiment 2 and find no framing effect when a few samples are taken but when large samples are taken, the framing effect appears regardless of the objective probability values. Implications of behavioral results and cognitive modeling are discussed.

The search for different options before making a consequential choice is a central aspect of many important decisions, such as mate selection or purchasing a house. Despite its importance, surprisingly little is known about how search and choice are affected by the observed and objective properties of the decision problem. Here, we analyze the effects of two key properties in a binary choice task: the options' observed and objective values, and the variability of payoffs. First, in a large public data set of a binary choice task, we investigate how the observed value and variability relate to decision-makers' efforts and preferences during search. Furthermore, we test how these properties influence the chance of correctly identifying the objectively maximizing option, and how they affect choice. Second, we designed a novel experiment to systematically analyze the role of the objective difference between the options. We find that a larger objective difference between options increases the chance for correctly identifying the maximizing option, but it does not affect behavior during search and choice. Copyright © 2013 John Wiley & Sons, Ltd. key wordsdecisions from experience; information search; bounded rationality; maximization; payoff variability; memoryIn many important real-life decisions, we seek out information about different possibilities before making a choice. For example, most people would not purchase a house without looking at several possibilities or marry a partner without having gotten to know him/her first. While the question of information search was often sidestepped in classical decision literature, significant progress has been made toward a better understanding of search and choice in recent years. For example, we have learned that people seem to generally search for little information before making a choice (for an overview, see Hau, Pleskac, & Hertwig, 2010), and that search can be affected by several characteristics of the decision maker and the choice ecology (for an overview, see Lejarraga, Hertwig, & Gonzalez, 2012). Relatively little is known, however, about how search is related to properties of payoffs that are actually observed during search, and how these properties affect subsequent choice. COSTS OF INFORMATION SEARCH VERSUS ACCURACY OF CHOICEA general finding in the decision-making literature is that people tend to search for "little" information before making a consequential choice between different options (e.g., Hau et al., 2010;. This behavior can be advantageous. For example, relying on smaller amounts of information reduces the explicit (e.g., monetary) and implicit (e.g., cognitive) costs of information search (Hau, Pleskac, Kiefer, & Hertwig, 2008), reduces demands on working-memory capacity (Kareev, 2000;Rakow, Demes, & Newell, 2008), tends to amplify differences between the options and thereby renders choice easier , and maximizes the time available for other decisions (Vul, Goodman, Griffiths, & Tenenbaum, 2009). As suggested by the statistical law of large nu...