Where should I search next? Messages embedded in storybooks influence children's strategic exploration in Turkey and the United States.

Despite the vital role of curiosity-driven exploration in learning, our understanding of how to enhance children's curiosity remains limited. Here, we tested whether hearing a strategic curiosity story with curiosity-promoting themes (e.g., strategically approaching uncertainty, adapting flexibly to new information) versus a control story with traditional pedagogical themes (e.g., following rules, learning from others) would influence children's strategic exploration across two cultures. Three- to 6-year-olds from the United States (N = 138) and Turkey (N = 88) were randomly assigned to hear one of these stories over Zoom, before playing a game in which they searched for sea creatures across five fish tanks. All tanks had the same number of hiding spots but varied in the number of creatures they contained. Time was limited and children could not return to prior tanks, pushing them to allocate search effort strategically. Results indicated that across both countries, children in the strategic curiosity condition explored the virtual "aquarium" more broadly; they moved through tanks more rapidly than children in the control condition and were more likely to explore all five tanks before time ran out. Children in the strategic curiosity condition also showed relatively more strategic search, adapting their search based on the likelihood of finding creatures in each tank. While further research is needed to pinpoint which elements of our stories produced differences in search behavior and whether they did so by enhancing or inhibiting children's strategic exploration, storybooks appear to be a promising method for shaping children's exploration across multiple countries. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Biocatalytic reductive amination as a route to isotopically labelled amino acids suitable for analysis of large proteins by NMR.

We demonstrate an atom-efficient and easy to use H2-driven biocatalytic platform for the enantioselective incorporation of 2H-atoms into amino acids. By combining the biocatalytic deuteration catalyst with amino acid dehydrogenase enzymes capable of reductive amination, we synthesised a library of multiply isotopically labelled amino acids from low-cost isotopic precursors, such as 2H2O and 15NH4+. The chosen approach avoids the use of pre-labeled 2H-reducing agents, and therefore vastly simplifies product cleanup. Notably, this strategy enables 2H, 15N, and an asymmetric centre to be introduced at a molecular site in a single step, with full selectivity, under benign conditions, and with near 100% atom economy. The method facilitates the preparation of amino acid isotopologues on a half-gram scale. These amino acids have wide applicability in the analytical life sciences, and in particular for NMR spectroscopic analysis of proteins. To demonstrate the benefits of the approach for enabling the workflow of protein NMR chemists, we prepared l-[α-2H,15N, ß-13C]-alanine and integrated it into a large (>400 kDa) heat-shock protein oligomer, which was subsequently analysable by methyl-TROSY techniques, revealing new structural information.

Neural evidence of switch processes during semantic and phonetic foraging in human memory.

Humans may retrieve words from memory by exploring and exploiting in "semantic space" similar to how nonhuman animals forage for resources in physical space. This has been studied using the verbal fluency test (VFT), in which participants generate words belonging to a semantic or phonetic category in a limited time. People produce bursts of related items during VFT, referred to as "clustering" and "switching." The strategic foraging model posits that cognitive search behavior is guided by a monitoring process which detects relevant declines in performance and then triggers the searcher to seek a new patch or cluster in memory after the current patch has been depleted. An alternative body of research proposes that this behavior can be explained by an undirected rather than strategic search process, such as random walks with or without random jumps to new parts of semantic space. This study contributes to this theoretical debate by testing for neural evidence of strategically timed switches during memory search. Thirty participants performed category and letter VFT during functional MRI. Responses were classified as cluster or switch events based on computational metrics of similarity and participant evaluations. Results showed greater hippocampal and posterior cerebellar activation during switching than clustering, even while controlling for interresponse times and linguistic distance. Furthermore, these regions exhibited ramping activity which increased during within-patch search leading up to switches. Findings support the strategic foraging model, clarifying how neural switch processes may guide memory search in a manner akin to foraging in patchy spatial environments.

Descriptive norms caused increases in mask wearing during the COVID-19 pandemic.

Human sociality is governed by two types of social norms: injunctive norms, which prescribe what people ought to do, and descriptive norms, which reflect what people actually do. The process by which these norms emerge and their causal influences on cooperative behavior over time are not well understood. Here, we study these questions through social norms influencing mask wearing during the COVID-19 pandemic. Leveraging 2 years of data from the United States (18 time points; n = 915), we tracked mask wearing and perceived injunctive and descriptive mask wearing norms as the pandemic unfolded. Longitudinal trends suggested that norms and behavior were tightly coupled, changing quickly in response to public health recommendations. In addition, longitudinal modeling revealed that descriptive norms caused future increases in mask wearing across multiple waves of data collection. These cross-lagged causal effects of descriptive norms were large, even after controlling for non-social beliefs and demographic variables. Injunctive norms, by contrast, had less frequent and generally weaker causal effects on future mask wearing. During uncertain times, cooperative behavior is more strongly driven by what others are actually doing, rather than what others think ought to be done.

COVID-19 and friendships: Agreeableness and neuroticism are associated with more concern about COVID-19 and friends' risky behaviors.

Given the importance of friendships during challenging times and the mixed associations between personality traits and disease-related behaviors, we investigated the correlations between personality traits and perceptions of friendships during the COVID-19 pandemic. Data were collected as part of a longitudinal investigation of the correlations between the pandemic and various cooperative relationships. In this investigation, we found that agreeableness and neuroticism predicted participants being more concerned about COVID-19 and bothered by friends' risky behavior, and extraversion predicted enjoying helping friends during the pandemic. Our results suggest that personality differences are associated with how individuals cope with friends' risky behaviors during the COVID-19 pandemic.

A pharmacophore-based approach to demonstrating the scope of alcohol dehydrogenases.

Barriers to the ready adoption of biocatalysis into asymmetric synthesis for early stage medicinal chemistry are addressed, using ketone reduction by alcohol dehydrogenase as a model reaction. An efficient substrate screening approach is used to show the wide substrate scope of commercial alcohol dehydrogenase enzymes, with a high tolerance to chemical groups employed in drug discovery (heterocycle, trifluoromethyl and nitrile/nitro groups) observed. We use our screening data to build a preliminary predictive pharmacophore-based screening tool using Forge software, with a precision of 0.67/1, demonstrating the potential for developing substrate screening tools for commercially available enzymes without publicly available structures. We hope that this work will facilitate a culture shift towards adopting biocatalysis alongside traditional chemical catalytic methods in early stage drug discovery.

Quantifying changes in societal optimism from online sentiment.

Individuals can hold contrasting views about distinct times: for example, dread over tomorrow's appointment and excitement about next summer's vacation. Yet, psychological measures of optimism often assess only one time point or ask participants to generalize about their future. Here, we address these limitations by developing the optimism curve, a measure of societal optimism that compares positivity toward different future times that was inspired by the Treasury bond yield curve. By performing sentiment analysis on over 3.5 million tweets that reference 23 future time points (2 days to 30 years), we measured how positivity differs across short-, medium-, and longer-term future references. We found a consistent negative association between positivity and the distance into the future referenced: From August 2017 to February 2020, the long-term future was discussed less positively than the short-term future. During the COVID-19 pandemic, this relationship inverted, indicating declining near-future- but stable distant-future-optimism. Our results demonstrate that individuals hold differentiated attitudes toward the near and distant future that shift in aggregate over time in response to external events. The optimism curve uniquely captures these shifting attitudes and may serve as a useful tool that can expand existing psychometric measures of optimism.

Social Search and Resource Clustering as Emergent Stable States.

Social search has stably evolved across various species and is often used by humans to search for resources (such as food, information, social partners). In turn, these resources frequently come distributed in patches or clusters. In the current work, we use an ecologically inspired agent-based model to investigate whether social search and clustering are stable outcomes of the dynamical mutual interactions between the two. While previous research has studied unidirectional influences of social search on resource clustering and vice versa, the current work investigates the consequential patterns emerging from their two-way interactions over time. In our model, consumers evolved search strategies (ranging from competitive to social) as adaptations to their environmental resource structures, and resources varied in distributions (ranging from random to clustered) that were shaped by agents' consumption patterns. Across four experiments, we systematically analyzed the patterns of influence that search strategies and environment structure have on each other to identify stable attractor states of both. In Experiment 1, we fixed resource clustering at various levels and observed its influence on social search, and in Experiment 2, we observed the influence of social search on resource distribution. In both these experiments we found that increasing levels of one variable produced increases in the other; however, at very high levels of the manipulated variable, the dependent variable tended to fall. Finally in Experiments 3 and 4, we studied the dynamics that arose when resource clustering and social search could both change and mutually influence each other, finding that low levels of social search and clustering were stable attractor states. Our simple 2D model yielded results that qualitatively resemble those across a wide range of search domains (from physical search for food to abstract search for information), highlighting some stable outcomes of mutually interacting consumer/resource systems.

Eating sustainably: Conviction or convenience?

Environmentally sustainable food consumption is one component of addressing climate change. Previous research has largely approached sustainable food consumption by investigating individual behaviors, without a broader conceptualization of what motivates food consumers to act sustainably. Using a representative sample of Indiana consumers, we explore sustainability across a range of food behaviors through latent class analysis, controlling for environmental attitudes, spatial access to food, and consumer demographics. This approach allows us to go beyond consumer segmentation analysis to explore how consumers conceptualize sustainable food behavior. The largest class of consumers (44% of the sample) appear either unwilling or unable to pay more for sustainability but are more likely to engage in sustainable behaviors that intersect with self-oriented attributes such as health benefits and lower cost. A second class (34%) consists of consumers who seem to be primarily motivated by the single issue of buying organic, are on average higher income, more educated, have better access to food, and are not opposed to paying for sustainability. Consumers in the smallest and most highly motivated group (9%) in terms of sustainability attitudes and self-perceived sustainability focus on local food production and are generally rural dwelling with less income. Only 13% of consumers engage in few to no sustainable behaviors, and these people notably exhibit the least sustainable attitudes. These findings illustrate the ways in which food sustainability is more nuanced than often characterized-much of it is driven by convenience and self-interest rather than reputation with respect to sustainability or conviction about environmental outcomes. This work also highlights how a combination of social, psychological, and spatial barriers exists and shape how different consumer groups conceptualize sustainable food consumption.

Embodied and embedded ecological rationality: A common vertebrate mechanism for action selection underlies cognition and heuristic decision-making in humans.

The last common ancestor shared by humans and other vertebrates lived over half a billion years ago. In the time since that ancestral line diverged, evolution by natural selection has produced an impressive diversity-from fish to birds to elephants-of vertebrate morphology; yet despite the great species-level differences that otherwise exist across the brains of many animals, the neural circuitry that underlies motor control features a functional architecture that is virtually unchanged in every living species of vertebrate. In this article, we review how that circuitry facilitates motor control, trial-and-error-based procedural learning, and habit formation; we then develop a model that describes how this circuitry (embodied in an agent) works to build and refine sequences of goal-directed actions that are molded to fit the structure of the environment (in which the agent is embedded). We subsequently review evidence suggesting that this same functional circuitry became further adapted to regulate cognitive control in humans as well as motor control; then, using examples of heuristic decision-making from the ecological rationality tradition, we show how the model can be used to understand how that circuitry operates analogously in both cognitive and motor domains. We conclude with a discussion of how the model encourages a shift in perspective regarding ecological rationality's "adaptive toolbox"-namely, to one that views heuristic processes and other forms of goal-directed cognition as likely being implemented by the same neural circuitry (and in the same fashion) as goal-directed action in the motor domain-and how this change of perspective can be useful.

Younger people and people with higher subjective SES experienced more negative effects of the pandemic on their friendships.

Friendships provide social support and mental health benefits, yet the COVID-19 pandemic has limited interactions with friends. In August 2020, we asked participants (N = 634) about their friendships during the pandemic as part of a larger study. We found that younger people and people with higher subjective SES reported more negative effects on their friendships, including feeling more isolated and lonelier. We also found that stress, isolation, and guilt were associated with greater COVID-related social risk-taking, such as making and visiting new friends in person. Our results suggest the pandemic is affecting friendships differently across demographic groups and these negative effects might motivate social risk-taking.

Semantic Search in Psychosis: Modeling Local Exploitation and Global Exploration.

Impairments in category verbal fluency task (VFT) performance have been widely documented in psychosis. These deficits may be due to disturbed "cognitive foraging" in semantic space, in terms of altered salience of cues that influence individuals to search locally within a subcategory of semantically related responses ("clustering") or globally between subcategories ("switching"). To test this, we conducted a study in which individuals with schizophrenia (n = 21), schizotypal personality traits (n = 25), and healthy controls (n = 40) performed VFT with "animals" as the category. Distributional semantic model Word2Vec computed cosine-based similarities between words according to their statistical usage in a large text corpus. We then applied a validated foraging-based search model to these similarity values to obtain salience indices of frequency-based global search cues and similarity-based local cues. Analyses examined whether diagnosis predicted VFT performance, search strategies, cue salience, and the time taken to switch between vs search within clusters. Compared to control and schizotypal groups, individuals with schizophrenia produced fewer words, switched less, and exhibited higher global cue salience, indicating a selection of more common words when switching to new clusters. Global cue salience negatively associated with vocabulary ability in controls and processing speed in schizophrenia. Lastly, individuals with schizophrenia took a similar amount of time to switch to new clusters compared to control and schizotypal groups but took longer to transition between words within clusters. Findings of altered local exploitation and global exploration through semantic memory provide preliminary evidence of aberrant cognitive foraging in schizophrenia.

Simple Threshold Rules Solve Explore/Exploit Trade-offs in a Resource Accumulation Search Task.

How, and how well, do people switch between exploration and exploitation to search for and accumulate resources? We study the decision processes underlying such exploration/exploitation trade-offs using a novel card selection task that captures the common situation of searching among multiple resources (e.g., jobs) that can be exploited without depleting. With experience, participants learn to switch appropriately between exploration and exploitation and approach optimal performance. We model participants' behavior on this task with random, threshold, and sampling strategies, and find that a linear decreasing threshold rule best fits participants' results. Further evidence that participants use decreasing threshold-based strategies comes from reaction time differences between exploration and exploitation; however, participants themselves report non-decreasing thresholds. Decreasing threshold strategies that "front-load" exploration and switch quickly to exploitation are particularly effective in resource accumulation tasks, in contrast to optimal stopping problems like the Secretary Problem requiring longer exploration.

Stated and revealed preferences in companion animal choice.

Humans often say they prefer certain attributes and trait levels and yet choose options inconsistent with those preferences, a phenomenon known as the stated-revealed preference gap. In this article, we compare preferences and choices in the decision to adopt a dog, a social-choice problem that is largely one-sided. We used existing and newly gathered field data about the dog adoption process to study how people make their choices of companion animals and how those choices can be improved. We found that in the real-world choice of dogs within an animal shelter, individuals generally showed a large amount of overlap between their stated preferences and their ratings of the traits of their chosen dog. However, there was little relationship between an adopter's perceptions of their chosen dog's behavioral traits and third-party in-shelter behavior evaluations of the same dogs, suggesting that it is difficult to predict which dogs will satisfy an adopter's preferences. We also tested which commonly collected factors impact how quickly dogs are adopted from animal shelters. Overall, this work provides insight into the process of combining experimentally collected data and big data to elucidate choice behavior.

Relationship Foraging: Does time spent searching predict relationship length?

Animals foraging for resources often need to alternate between searching for and benefiting from patches of those resources. Here we explore whether such patterns of behavior can usefully be applied to the human search for romantic relationships. Optimal foraging theory suggests that foragers should alter their time spent in patches based on how long they typically spend searching between patches. We test whether human relationship search can be described as a foraging task that fits this OFT prediction. By analyzing a large, demographically representative dataset on marriage and cohabitation timing using survival analysis, we find that the likelihood of a relationship ending per unit time goes down with increased duration of search before that relationship, in accord with the foraging prediction. We consider the possible applications and limits of a foraging perspective on mate search and suggest further directions for study.

Habit formation generates secondary modules that emulate the efficiency of evolved behavior.

We discuss the evolutionary implications of connections drawn between the authors' learned "secondary modules" and the habit-formation system that appears to be ubiquitous among vertebrates. Prior to any subsequent coevolution with social learning, we suggest that aspects of general intelligence likely arose in tandem with mechanisms of adaptive motor control that rely on basal ganglia circuitry.

A Game of Hide and Seek: Expectations of Clumpy Resources Influence Hiding and Searching Patterns.

Resources are often distributed in clumps or patches in space, unless an agent is trying to protect them from discovery and theft using a dispersed distribution. We uncover human expectations of such spatial resource patterns in collaborative and competitive settings via a sequential multi-person game in which participants hid resources for the next participant to seek. When collaborating, resources were mostly hidden in clumpy distributions, but when competing, resources were hidden in more dispersed (random or hyperdispersed) patterns to increase the searching difficulty for the other player. More dispersed resource distributions came at the cost of higher overall hiding (as well as searching) times, decreased payoffs, and an increased difficulty when the hider had to recall earlier hiding locations at the end of the experiment. Participants' search strategies were also affected by their underlying expectations, using a win-stay lose-shift strategy appropriate for clumpy resources when searching for collaboratively-hidden items, but moving equally far after finding or not finding an item in competitive settings, as appropriate for dispersed resources. Thus participants showed expectations for clumpy versus dispersed spatial resources that matched the distributions commonly found in collaborative versus competitive foraging settings.

Hidden processes in structural representations: A reply to Abbott, Austerweil, and Griffiths (2015).

In recent work exploring the semantic fluency task, we found evidence indicative of optimal foraging policies in memory search that mirror search in physical environments. We determined that a 2-stage cue-switching model applied to a memory representation from a semantic space model best explained the human data. Abbott, Austerweil, and Griffiths demonstrate how these patterns could also emerge from a random walk applied to a network representation of memory based on human free-association norms. However, a major representational issue limits any conclusions that can be drawn about the process model comparison: Our process model operated on a memory space constructed from a learning model, whereas their model used human behavioral data from a task that is quite similar to the behavior they attempt to explain. Predicting semantic fluency (e.g., how likely it is to say cat after dog in a sequence of animals) from free association (how likely it is to say cat when given dog as a cue) should be possible with a relatively simple retrieval mechanism. The 2 tasks both tap memory, but they also share a common process of retrieval. Assuming that semantic memory is a network from free-association behavior embeds variance due to the shared retrieval process directly into the representation. A simple process mechanism is then sufficient to simulate semantic fluency because much of the requisite process complexity may already be hidden in the representation. (PsycINFO Database Record