Knowledge that Transforms

Studies over the past 40 years have shown that Americans can recall about half the U.S. presidents. Do people know the presidents even though they are unable to access them for recall? We investigated this question using the powerful cues of a recognition test. Specifically, we tested the ability of 326 online subjects to recognize U.S. presidents when presented with their full names among various types of lures. The hit rate for presidential recognition was .88, well above the proportion produced in free recall but far from perfect. Presidents Franklin Pierce and Chester Arthur were recognized less than 60% of the time. Interestingly, four nonpresidents were falsely recognized at relatively high rates, and Alexander Hamilton was more frequently identified as president than were several actual presidents. Even on a recognition test, knowledge of American presidents is imperfect and prone to error. The false alarm data support the theory that false fame can arise from contextual familiarity.

The general view in psychological science is that natural categories obey a coherent, family-resemblance principle. In this investigation, we documented an example of an important exception to this principle: Results of a multidimensional-scaling study of igneous, metamorphic, and sedimentary rocks (Experiment 1) suggested that the structure of these categories is disorganized and dispersed. This finding motivated us to explore what might be the optimal procedures for teaching dispersed categories, a goal that is likely critical to science education in general. Subjects in Experiment 2 learned to classify pictures of rocks into compact or dispersed high-level categories. One group learned the categories through focused high-level training, whereas a second group was required to simultaneously learn classifications at a subtype level. Although high-level training led to enhanced performance when the categories were compact, subtype training was better when the categories were dispersed. We provide an interpretation of the results in terms of an exemplar-memory model of category learning.

Because linguistic communication is inherently noisy and uncertain, adult language comprehenders integrate bottom-up cues from speech perception with top-down expectations about what speakers are likely to say. Further, in line with the predictions of ideal-observer models, past results have shown that adult comprehenders flexibly adapt how much they rely on these two kinds of cues in proportion to their changing reliability. Do children also show evidence of flexible, expectation-based language comprehension? We presented preschoolers with ambiguous utterances that could be interpreted in two different ways, depending on whether the children privileged perceptual input or top-down expectations. Across three experiments, we manipulated the reliability of both their perceptual input and their expectations about the speaker's intended meaning. As predicted by noisy-channel models of speech processing, results showed that 4- and 5-year-old-but perhaps not younger-children flexibly adjusted their interpretations as cues changed in reliability.

Childhood adversity is associated with poor health outcomes in adulthood; the hypothalamic-pituitary-adrenal (HPA) axis has been proposed as a crucial biological intermediary of these long-term effects. Here, we tested whether childhood adversity was associated with diurnal cortisol parameters and whether this link was partially explained by self-esteem. In both adults and youths, childhood adversity was associated with lower levels of cortisol at awakening, and this association was partially driven by low self-esteem. Further, we found a significant indirect pathway through which greater adversity during childhood was linked to a flatter cortisol slope via self-esteem. Finally, youths who had a caregiver with high self-esteem experienced a steeper decline in cortisol throughout the day compared with youths whose caregiver reported low self-esteem. We conclude that self-esteem is a plausible psychological mechanism through which childhood adversity may get embedded in the activity of the HPA axis across the life span.

How do people get attention to operate at peak efficiency in high-pressure situations? We tested the hypothesis that the general mechanism that allows this is the maintenance of multiple target representations in working and long-term memory. We recorded subjects' event-related potentials (ERPs) indexing the working memory and long-term memory representations used to control attention while performing visual search. We found that subjects used both types of memories to control attention when they performed the visual search task with a large reward at stake, or when they were cued to respond as fast as possible. However, under normal circumstances, one type of target memory was sufficient for slower task performance. The use of multiple types of memory representations appears to provide converging top-down control of attention, allowing people to step on the attentional accelerator in a variety of high-pressure situations.

Understanding how human populations naturally respond to and cope with risk is important for fields ranging from psychology to public health. We used geophysical and individual-level mobile-phone data (mobile-apps, telecommunications, and Web usage) of 157,358 victims of the 2013 Ya'an earthquake to diagnose the effects of the disaster and investigate how experiencing real risk (at different levels of intensity) changes behavior. Rather than limiting human activity, higher earthquake intensity resulted in graded increases in usage of communications apps (e.g., social networking, messaging), functional apps (e.g., informational tools), and hedonic apps (e.g., music, videos, games). Combining mobile data with a field survey ( N = 2,000) completed 1 week after the earthquake, we use an instrumental-variable approach to show that only increases in hedonic behavior reduced perceived risk. Thus, hedonic behavior could potentially serve as a population-scale coping and recovery strategy that is often missing in risk management and policy considerations.

This article introduces a generative model of category representation that uses computer vision methods to extract category-consistent features (CCFs) directly from images of category exemplars. The model was trained on 4,800 images of common objects, and CCFs were obtained for 68 categories spanning subordinate, basic, and superordinate levels in a category hierarchy. When participants searched for these same categories, targets cued at the subordinate level were preferentially fixated, but fixated targets were verified faster when they followed a basic-level cue. The subordinate-level advantage in guidance is explained by the number of target-category CCFs, a measure of category specificity that decreases with movement up the category hierarchy. The basic-level advantage in verification is explained by multiplying the number of CCFs by sibling distance, a measure of category distinctiveness. With this model, the visual representations of real-world object categories, each learned from the vast numbers of image exemplars accumulated throughout everyday experience, can finally be studied.

Research has shown that people who feel powerful are more likely to act than those who feel powerless, whereas people who feel ambivalent are less likely to act than those whose reactions are univalent (entirely positive or entirely negative). But what happens when powerful people also are ambivalent? On the basis of the self-validation theory of judgment, we hypothesized that power and ambivalence would interact to predict individuals' action. Because power can validate individuals' reactions, we reasoned that feeling powerful strengthens whatever reactions people have during a decision. It can strengthen univalent reactions and increase action orientation, as shown in past research. Among people who hold an ambivalent judgment, however, those who feel powerful would be less action oriented than those who feel powerless. Two experiments provide evidence for this hypothesized interactive effect of power and ambivalence on individuals' action tendencies during both positive decisions (promoting an employee; Experiment 1) and negative decisions (firing an employee; Experiment 2). In summary, when individuals' reactions are ambivalent, power increases the likelihood of inaction.

Associative activation is commonly assumed to rely on associative strength, such that if A is strongly associated with B, B is activated whenever A is activated. We challenged this assumption by examining whether the activation of associations is state dependent. In three experiments, subjects performed a free-association task while the level of a simultaneous load was manipulated in various ways. In all three experiments subjects in the low-load conditions provided significantly more diverse and original associations compared with subjects in the high-load conditions, who exhibited high consensus. In an additional experiment, we found increased semantic priming of immediate associations under high load and of remote associations under low load. Taken together, these findings imply that activation of associations is an exploratory process by default, but is narrowed to exploiting the more immediate associations under conditions of high load. We propose a potential mechanism for processing associations in exploration and in exploitation modes, and suggest clinical implications.

Both repeated practice and sleep improve long-term retention of information. The assumed common mechanism underlying these effects is memory reactivation, either on-line and effortful or off-line and effortless. In the study reported here, we investigated whether sleep-dependent memory consolidation could help to save practice time during relearning. During two sessions occurring 12 hr apart, 40 participants practiced foreign vocabulary until they reached a perfect level of performance. Half of them learned in the morning and relearned in the evening of a single day. The other half learned in the evening of one day, slept, and then relearned in the morning of the next day. Their retention was assessed 1 week later and 6 months later. We found that interleaving sleep between learning sessions not only reduced the amount of practice needed by half but also ensured much better long-term retention. Sleeping after learning is definitely a good strategy, but sleeping between two learning sessions is a better strategy.