When speaking to infants, adults often produce speech that differs systematically from that directed to other adults. To quantify the acoustic properties of this speech style across a wide variety of languages and cultures, we extracted results from empirical studies on the acoustic features of infant-directed speech. We analysed data from 88 unique studies (734 effect sizes) on the following five acoustic parameters that have been systematically examined in the literature: fundamental frequency (f0), f0 variability, vowel space area, articulation rate and vowel duration. Moderator analyses were conducted in hierarchical Bayesian robust regression models to examine how these features change with infant age and differ across languages, experimental tasks and recording environments. The moderator analyses indicated that f0, articulation rate and vowel duration became more similar to adult-directed speech over time, whereas f0 variability and vowel space area exhibited stability throughout development. These results point the way for future research to disentangle different accounts of the functions and learnability of infant-directed speech by conducting theory-driven comparisons among different languages and using computational models to formulate testable predictions.
Anxiety has been related to decreased physical exploration, but past findings on the interaction between anxiety and exploration during decision making were inconclusive. Here we examined how latent factors of trait anxiety relate to different exploration strategies when facing volatility-induced uncertainty. Across two studies (total N = 985), we demonstrated that people used a hybrid of directed, random and undirected exploration strategies, which were respectively sensitive to relative uncertainty, total uncertainty and value difference. Trait somatic anxiety, that is, the propensity to experience physical symptoms of anxiety, was inversely correlated with directed exploration and undirected exploration, manifesting as a lesser likelihood for choosing the uncertain option and reducing choice stochasticity regardless of uncertainty. Somatic anxiety is also associated with underestimation of relative uncertainty. Together, these results reveal the selective role of trait somatic anxiety in modulating both uncertainty-driven and value-driven exploration strategies.
The success and failure of past cultures across the Arctic was tightly coupled to the ability of past peoples to exploit the full range of resources available to them. There is substantial evidence for the hunting of birds, caribou and seals in prehistoric Greenland. However, the extent to which these communities relied on fish and cetaceans is understudied because of taphonomic processes that affect how these taxa are presented in the archaeological record. To address this, we analyse DNA from bulk bone samples from 12 archaeological middens across Greenland covering the Palaeo-Inuit, Norse and Neo-Inuit culture. We identify an assemblage of 42 species, including nine fish species and five whale species, of which the bowhead whale (Balaena mysticetus) was the most commonly detected. Furthermore, we identify a new haplotype in caribou (Rangifer tarandus), suggesting the presence of a distinct lineage of (now extinct) dwarfed caribou in Greenland 3,000 years ago. Seersholm et al. analysed permafrozen middens from Inuit and Viking settlements to uncover evidence of diet in prehistoric Greenland. Using ancient DNA, they identified 42 different species and found that whales were surprisingly common.
Intense sociality has been a catalyser for human culture and civilization. Within this context, our relationships at a personal level play a pivotal role in our health and well-being. These relationships are, however, sensitive to the time we invest in them. To understand how and why this should be, we rst outline the evolutionary background in primate sociality from which our human social world has emerged. We then review de ning features of that human sociality, putting forward a framework within which one can understand new evidence on the consequences of mass social isolation during the COVID-19 pandemic, including mental health deterioration, stress, sleep disturbance and substance misuse. We outline recent research insights on the neural basis of prolonged social isolation, highlighting especially higher-order neural circuits such as the default network. Our survey of studies witnesses the various negative e ects of prolonged social deprivation and the multifaceted drivers of day-today pandemic experiences. Humans, like all anthropoid primates, are intensely social. We now have considerable evidence that interindividual differences in social embed-dedness affect a variety of health and fitness indicators. In humans, the single best predictor of physical health and well-being, as well as future longevity, is the number and quality of close friendships, with the more conventional suspects (such as diet, obesity, alcohol consumption and air quality) ranking a distant second 1,2. Indeed, the frequency of social engagement predicts psychological health and well-being 3 , self-rated feelings of happiness, satisfaction with life, and trust in one's local community 4. . m. m. m. m. m. m The COVID-19 lockdowns of the past two years were a global stress test-large-scale social deprivation in a more dramatic extent and form than ever before in recorded history. At the peak of public health restrictions, >3.6 billion people worldwide were subject to government-imposed stay-at-home orders. On the individual scale, we know that we respond poorly to isolation. However, existing psychological and neuroscience research had little to say about the possible consequences of mass isolation. In contrast, there have been many large-scale epidemiological studies of the effects of social deprivation in the elderly 5. Almost all of these investigations yielded strong signals for detrimental effects on cognitive capacity, psychological and physical well-being, and even longevity. It became clear that the chronic experience of social isolation escalated the risk of depression and dementias, as well as cardiovascular disease and certain types of cancer 6-8. The present review provides a frame of reference that can help situate current and future findings on the ongoing mass social isolation by incorporating established knowledge on human sociality and its underlying neurobiological mechanisms. To this end, we first place human sociality within the broader context of anthropoid primate sociality, with its behavioural and neurobiological determinants. Our aim is to provide a more grounded explanation as to why the neurobiol-ogy of human sociality takes the form it does. We then survey some of the unfolding evidence with direct relevance to the neurobiological and psychological consequences of the large-scale lockdown during COVID-19 and subsequent social rehabilitation.
Statistical inference is the optimal process for forming and maintaining accurate beliefs about uncertain environments. However, human inference comes with costs due to its associated biases and limited precision. Indeed, biased or imprecise inference can trigger variable beliefs and unwarranted changes in behaviour. Here, by studying decisions in a sequential categorization task based on noisy visual stimuli, we obtained converging evidence that humans reduce the variability of their beliefs by updating them only when the reliability of incoming sensory information is judged as sufficiently strong. Instead of integrating the evidence provided by all stimuli, participants actively discarded as much as a third of stimuli. This conditional belief updating strategy shows good test–retest reliability, correlates with perceptual confidence and explains human behaviour better than previously described strategies. This seemingly suboptimal strategy not only reduces the costs of imprecise computations but also, counterintuitively, increases the accuracy of resulting decisions.
Assortative mating (AM) is a pattern characterized by phenotypic similarities between mating partners. Detecting the evidence of AM has been challenging due to the lack of large-scale datasets that include phenotypic data on both partners, especially in populations of non-European ancestries. Gametic phase disequilibrium between trait-associated alleles is a signature of parental AM on a polygenic trait, which can be detected even without partner data. Here, using polygenic scores for 81 traits in the Japanese population using BioBank Japan Project genome-wide association studies data (n = 172,270), we found evidence of AM on the liability to type 2 diabetes and coronary artery disease, as well as on dietary habits. In cross-population comparison using United Kingdom Biobank data (n = 337,139) we found shared but heterogeneous impacts of AM between populations.
Social tipping can accelerate behaviour change consistent with policy objectives in diverse domains from social justice to climate change. Hypothetically, however, group identities might undermine tipping in ways that policymakers do not anticipate. To examine this, we implemented an experiment around the 2020 US federal elections. The participants faced consistent incentives to coordinate their choices. Once the participants had established a coordination norm, an intervention created pressure to tip to a new norm. Our control treatment used neutral labels for choices. Our identity treatment used partisan political images. This simple pay-off-irrelevant relabelling generated extreme differences. The control groups developed norms slowly before intervention but transitioned to new norms rapidly after intervention. The identity groups developed norms rapidly before intervention but persisted in a state of costly disagreement after intervention. Tipping was powerful but unreliable. It supported striking cultural changes when choice and identity were unlinked, but even a trivial link destroyed tipping entirely.
There has been increasing interest in using neuroimaging measures to predict psychiatric disorders. However, predictions usually rely on large brain networks and large disorder heterogeneity. Thus, they lack both anatomical and behavioural specificity, preventing the advancement of targeted interventions. Here we address both challenges. First, using resting-state functional magnetic resonance imaging, we parcellated the amygdala, a region implicated in mood disorders, into seven nuclei. Next, a questionnaire factor analysis provided subclinical mental health dimensions frequently altered in anxious-depressive individuals, such as negative emotions and sleep problems. Finally, for each behavioural dimension, we identified the most predictive resting-state functional connectivity between individual amygdala nuclei and highly specific regions of interest, such as the dorsal raphe nucleus in the brainstem or medial frontal cortical regions. Connectivity in circumscribed amygdala networks predicted behaviours in an independent dataset. Our results reveal specific relations between mental health dimensions and connectivity in precise subcortical networks.
Rising partisan animosity is associated with a reduction in support for democracy and an increase in support for political violence. Here we provide a multi-level review of interventions designed to reduce partisan animosity, which we define as negative thoughts, feelings and behaviours towards a political outgroup. We introduce the TRI framework to capture three levels of intervention—thoughts (correcting misconceptions and highlighting commonalities), relationships (building dialogue skills and fostering positive contact) and institutions (changing public discourse and transforming political structures)—and connect these levels by highlighting the importance of motivation and mobilization. Our review encompasses both interventions conducted as part of academic research projects and real-world interventions led by practitioners in non-profit organizations. We also explore the challenges of durability and scalability, examine self-fulfilling polarization and interventions that backfire, and discuss future directions for reducing partisan animosity. Rachel Hartman and colleagues review interventions designed to reduce partisan animosity in the United States and introduce a framework to categorize interventions across three levels: thoughts, relationships and institutions.
Decades of research indicate that some of the epistemic practices that support scientific enquiry emerge as part of intuitive reasoning in early childhood. Here, we ask whether adults and young children can use intuitive statistical reasoning and metacognitive strategies to estimate how much information they might need to solve different discrimination problems, suggesting that they have some of the foundations for ‘intuitive power analyses’. Across five experiments, both adults (N = 290) and children (N = 48, 6–8 years) were able to precisely represent the relative difficulty of discriminating populations and recognized that larger samples were required for populations with greater overlap. Participants were sensitive to the cost of sampling, as well as the perceptual nature of the stimuli. These findings indicate that both young children and adults metacognitively represent their own ability to make discriminations even in the absence of data, and can use this to guide efficient and effective exploration. Adults and children can represent the relative difficulty of discriminating two populations and recognize that larger samples are required for populations with greater overlap. This suggests that they have foundations for ‘intuitive power analyses’.
Non-random mating affects the genetic makeup of populations and challenges the validity of popular genetics methods. A new study explores the unique patterns of non-random mating in the Japanese population and underscores the importance of large-scale genetic studies outside European-descended groups.
The low representation of academics with disabilities is a longstanding problem on which progress has been slow. Drawing on my research on disability-related barriers and my experiences of disability, I make six practical suggestions for how academic staff and people with disabilities can help make academia more disability inclusive.
Lotteries have been shown to motivate behaviour change in many settings, but their value as a policy tool is relatively untested. We implemented a pre-registered, citywide experiment to test the effects of three high-pay-off, geographically targeted lotteries designed to motivate adult Philadelphians to get their COVID-19 vaccine. In each drawing, the residents of a randomly selected ‘treatment’ zip code received half the lottery prizes, boosting their chances of winning to 50×–100× those of other Philadelphians. The first treated zip code, which drew considerable media attention, may have experienced a small bump in vaccinations compared with the control zip codes: average weekly vaccinations rose by an estimated 61 per 100,000 people per week (+11%). After pooling the results from all three zip codes treated during our six-week experiment, however, we do not detect evidence of any overall benefits. Furthermore, our 95% confidence interval provides a 9% upper bound on the net benefits of treatment in our study. A citywide experiment tested the effects of three high-pay-off, geo-targeted lotteries to motivate adults to get a COVID-19 vaccine. Zip-code-targeted lotteries in which residents were given 50–100× boosts in their chances of a win did not result in higher vaccine uptake.
Despite the special role of tenure-track faculty in society, training future researchers and producing scholarship that drives scientific and technological innovation, the sociodemographic characteristics of the professoriate have never been representative of the general population. Here we systematically investigate the indicators of faculty childhood socioeconomic status and consider how they may limit efforts to diversify the professoriate. Combining national-level data on education, income and university rankings with a 2017–2020 survey of 7,204 US-based tenure-track faculty across eight disciplines in STEM, social science and the humanities, we show that faculty are up to 25 times more likely to have a parent with a Ph.D. Moreover, this rate nearly doubles at prestigious universities and is stable across the past 50 years. Our results suggest that the professoriate is, and has remained, accessible disproportionately to the socioeconomically privileged, which is likely to deeply shape their scholarship and their reproduction.
Prior research has found mixed results on how economic inequality is related to various outcomes. These contradicting findings may in part stem from a predominant focus on the Gini coefficient, which only narrowly captures inequality. Here, we conceptualize the measurement of inequality as a data reduction task of income distributions. Using a uniquely fine-grained dataset of N = 3,056 US county-level income distributions, we estimate the fit of 17 previously proposed models and find that multi-parameter models consistently outperform single-parameter models (i.e., models that represent single-parameter measures like the Gini coefficient). Subsequent simulations reveal that the best-fitting model—the two-parameter Ortega model—distinguishes between inequality concentrated at lower- versus top-income percentiles. When applied to 100 policy outcomes from a range of fields (including health, crime and social mobility), the two Ortega parameters frequently provide directionally and magnitudinally different correlations than the Gini coefficient. Our findings highlight the importance of multi-parameter models and data-driven methods to study inequality. Moving beyond the Gini coefficient in studying inequality, Blesch et al. identify two parameters that capture inequality concentrated at the top and bottom. The results challenge mixed associations between inequality and policy outcomes.
Balancing social utility and equity in distributing limited vaccines is a critical policy concern for protecting against the prolonged COVID-19 pandemic and future health emergencies. What is the nature of the trade-off between maximizing collective welfare and minimizing disparities between more and less privileged communities? To evaluate vaccination strategies, we propose an epidemic model that explicitly accounts for both demographic and mobility differences among communities and their associations with heterogeneous COVID-19 risks, then calibrate it with large-scale data. Using this model, we find that social utility and equity can be simultaneously improved when vaccine access is prioritized for the most disadvantaged communities, which holds even when such communities manifest considerable vaccine reluctance. Nevertheless, equity among distinct demographic features may conflict; for example, low-income neighbourhoods might have fewer elder citizens. We design two behaviour-and-demography-aware indices, community risk and societal risk, which capture the risks communities face and those they impose on society from not being vaccinated, to inform the design of comprehensive vaccine distribution strategies. Our study provides a framework for uniting utility and equity-based considerations in vaccine distribution and sheds light on how to balance multiple ethical values in complex settings for epidemic control. The authors use data-informed computational modelling and show that prioritizing vaccination efforts for the most disadvantaged communities can simultaneously improve equity and prevent the spread of disease.
The COVID-19 pandemic has increased negative emotions and decreased positive emotions globally. Left unchecked, these emotional changes might have a wide array of adverse impacts. To reduce negative emotions and increase positive emotions, we tested the effectiveness of reappraisal, an emotion-regulation strategy that modifies how one thinks about a situation. Participants from 87 countries and regions (n = 21,644) were randomly assigned to one of two brief reappraisal interventions (reconstrual or repurposing) or one of two control conditions (active or passive). Results revealed that both reappraisal interventions (vesus both control conditions) consistently reduced negative emotions and increased positive emotions across different measures. Reconstrual and repurposing interventions had similar effects. Importantly, planned exploratory analyses indicated that reappraisal interventions did not reduce intentions to practice preventive health behaviours. The findings demonstrate the viability of creating scalable, low-cost interventions for use around the world.
Vaccine hesitancy (VH) is considered a top-10 global health threat. The concept of VH has been described and applied inconsistently. This systematic review aims to clarify VH by analysing how it is operationalized. We searched PubMed, Embase and PsycINFO databases on 14 January 2022. We selected 422 studies containing operationalizations of VH for inclusion. One limitation is that studies of lower quality were not excluded. Our qualitative analysis reveals that VH is conceptualized as involving (1) cognitions or affect, (2) behaviour and (3) decision making. A wide variety of methods have been used to measure VH. Our findings indicate the varied and confusing use of the term VH, leading to an impracticable concept. We propose that VH should be defined as a state of indecisiveness regarding a vaccination decision. This systematic review of 422 studies of vaccine hesitancy finds that the term is used inconsistently. Vaccine hesitancy should be defined as a psychological state of indecisiveness that people may experience when making a vaccination decision.
Marginalized scholars are often excluded from key scientific conferences owing to visa and travel restrictions, which increases inequity among academics.
Every year, many scholars are prevented from presenting their accepted research at scientific conventions for reasons related to structural barriers surrounding conference attendance. In such contexts it is partly financial disparities that divide attendees from those invisibly absent, but there are additional issues that foster nonattendance, including travel bans pertaining to ethnic origin and acquisition of visas. These barriers produce synthetic selection effects that, over time, lead to systematic discrepancies between academics based on unjust sources of variation.
Open and accessible link to article in Nature Human Behaviour:
The COVID-19 pandemic and associated lockdowns triggered worldwide changes in the daily routines of human experience. The Blursday database provides repeated measures of subjective time and related processes from participants in nine countries tested on 14 questionnaires and 15 behavioural tasks during the COVID-19 pandemic. A total of 2,840 participants completed at least one task, and 439 participants completed all tasks in the first session. The database and all data collection tools are accessible to researchers for studying the effects of social isolation on temporal information processing, time perspective, decision-making, sleep, metacognition, attention, memory, self-perception and mindfulness. Blursday includes quantitative statistics such as sleep patterns, personality traits, psychological well-being and lockdown indices. The database provides quantitative insights on the effects of lockdown (stringency and mobility) and subjective confinement on time perception (duration, passage of time and temporal distances). Perceived isolation affects time perception, and we report an inter-individual central tendency effect in retrospective duration estimation.
People are on the move in unprecedented numbers within and between countries. How does demographic change affect local intergroup dynamics? Complementing accounts that emphasize stereotypical features of groups as determinants of their treatment, we propose the group reference dependence hypothesis: violence and negative attitudes towards each minoritized group will depend on the number and size of other minoritized groups in a community. Specifically, as groups increase or decrease in rank in terms of their size (for example, to the largest minority within a community), discriminatory behaviour and attitudes towards them should change accordingly. We test this hypothesis for hate crimes in US counties between 1990 and 2010 and attitudes in the United States and United Kingdom over the past two decades. Consistent with this prediction, we find that as Black, Hispanic/Latinx, Asian and Arab populations increase in rank relative to one another, they become more likely to be targeted with hate crimes and more negative attitudes. The rank effect holds above and beyond group size/proportion, growth rate and many other alternative explanations. This framework makes predictions about how demographic shifts may affect coalitional structures in the coming years and helps explain previous findings in the literature. Our results also indicate that attitudes and behaviours towards social categories are not intransigent or driven only by features associated with those groups, such as stereotypes. Cikara et al. propose and test the group reference dependence hypothesis, stating that violence and negative attitudes towards minoritized groups depend on the number and size of other minoritized groups in a community. Using data on hate crimes in US counties between 1990 and 2010, they show that as groups increase in rank in terms of their size, hate crimes against them become more likely.
Common genetic variants explain less variation in complex phenotypes than inferred from family-based studies, and there is a debate on the source of this ‘missing heritability’. We investigated the contribution of rare genetic variants to tobacco use with whole-genome sequences from up to 26,257 unrelated individuals of European ancestries and 11,743 individuals of African ancestries. Across four smoking traits, single-nucleotide-polymorphism-based heritability (hSNP2) was estimated from 0.13 to 0.28 (s.e., 0.10–0.13) in European ancestries, with 35–74% of it attributable to rare variants with minor allele frequencies between 0.01% and 1%. These heritability estimates are 1.5–4 times higher than past estimates based on common variants alone and accounted for 60% to 100% of our pedigree-based estimates of narrow-sense heritability (hped2, 0.18–0.34). In the African ancestry samples, hSNP2 was estimated from 0.03 to 0.33 (s.e., 0.09–0.14) across the four smoking traits. These results suggest that rare variants are important contributors to the heritability of smoking. The team of authors led by Seon-Kyeong Jang use whole-genome sequencing data and show that rare genetic variants explain much of the ‘missing heritability’ in smoking behaviours. These results help address a long-standing mystery in behavioural genetics.
Mental health, neuroscience and neuroethics researchers must engage local African communities to enable discourses on cultural understandings of mental illness. To ensure that these engagements are both ethical and innovative, they must be facilitated with cultural competence and humility, because serious consideration of different contextual and local factors is critical.
Data has tremendous potential to build resilience in government. To realize this potential, we need a new, human-centred, distinctly public sector approach to data science and AI, in which these technologies do not just automate or turbocharge what humans can already do well, but rather do things that people cannot.
When academics support refugee scholars, everyone benefits. Scholars who are refugees face complex challenges, including bureaucratic, cultural, linguistic and academic barriers. Ahmad Al Ajlan discusses key steps that academic communities can take to support and integrate their refugee colleagues.
Policing efforts to thwart crime typically rely on criminal infraction reports, which implicitly manifest a complex relationship between crime, policing and society. As a result, crime prediction and predictive policing have stirred controversy, with the latest artificial intelligence-based algorithms producing limited insight into the social system of crime. Here we show that, while predictive models may enhance state power through criminal surveillance, they also enable surveillance of the state by tracing systemic biases in crime enforcement. We introduce a stochastic inference algorithm that forecasts crime by learning spatio-temporal dependencies from event reports, with a mean area under the receiver operating characteristic curve of ~90% in Chicago for crimes predicted per week within ~1,000 ft. Such predictions enable us to study perturbations of crime patterns that suggest that the response to increased crime is biased by neighbourhood socio-economic status, draining policy resources from socio-economically disadvantaged areas, as demonstrated in eight major US cities. Rotaru et al. introduce a transparent crime forecasting algorithm that reveals inequities in police enforcement and suggests an enforcement bias in eight US cities.
Human neonates can discriminate phonemes, but the neural mechanism underlying this ability is poorly understood. Here we show that the neonatal brain can learn to discriminate natural vowels from backward vowels, a contrast unlikely to have been learnt in the womb. Using functional near-infrared spectroscopy, we examined the neuroplastic changes caused by 5 h of postnatal exposure to random sequences of natural and reversed (backward) vowels (T1), and again 2 h later (T2). Neonates in the experimental group were trained with the same stimuli as those used at T1 and T2. Compared with controls, infants in the experimental group showed shorter haemodynamic response latencies for forward vs backward vowels at T1, maximally over the inferior frontal region. At T2, neural activity differentially increased, maximally over superior temporal regions and the left inferior parietal region. Neonates thus exhibit ultra-fast tuning to natural phonemes in the first hours after birth.
We must often infer latent properties of the world from noisy and changing observations. Complex, probabilistic approaches to this challenge such as Bayesian inference are accurate but cognitively demanding, relying on extensive working memory and adaptive processing. Simple heuristics are easy to implement but may be less accurate. What is the appropriate balance between complexity and accuracy? Here we model a hierarchy of strategies of variable complexity and find a power law of diminishing returns: increasing complexity gives progressively smaller gains in accuracy. The rate of diminishing returns depends systematically on the statistical uncertainty in the world, such that complex strategies do not provide substantial benefits over simple ones when uncertainty is either too high or too low. In between, there is a complexity dividend. In two psychophysical experiments, we confirm specific model predictions about how working memory and adaptivity should be modulated by uncertainty. Tavoni et al. show that complex inference strategies are worth the cognitive effort only in environments of moderate statistical complexity.
The frequency of a cultural trait can influence its tendency to be copied. We develop a maximum-likelihood method to measure such frequency-dependent selection from time series data, and we apply it to baby names and purebred dog preferences over the past century. The form of negative frequency dependence we infer among names explains their diversity patterns, and it replicates across the United States, France, Norway and the Netherlands. We find different growth rates for male versus female names, attributable to different rates of innovation, whereas biblical names enjoy a genuine selective advantage at all frequencies, which explains their predominance among top names. We show how frequency dependence emerges from a host of underlying selective mechanisms, including a preference for novelty that recapitulates boom–bust fads among dog owners. Our analysis of cultural evolution through frequency-dependent selection provides a quantitative account of social pressures to conform or to be different. Newberry and Plotkin show that the frequency of a cultural trait can influence its tendency to be copied. They develop a method to measure frequency-dependent selection and describe how it relates to the dynamics and diversity of first names and dog breed preferences, in different countries and cultures.
Humans differentially weight different stimuli in averaging tasks, which has been interpreted as reflecting encoding bias. We examine the alternative hypothesis that stimuli are encoded with noise and then optimally decoded. Under a model of efficient coding, the amount of noise should vary across stimuli and depend on statistics of the stimuli. We investigate these predictions through a task in which the participants are asked to compare the averages of two series of numbers, each sampled from a prior distribution that varies across blocks of trials. The participants encode numbers with a bias and a noise that both depend on the number. Infrequently occurring numbers are encoded with more noise. We show how an efficient-coding, Bayesian-decoding model accounts for these patterns and best captures the participants’ behaviour. Finally, our results suggest that Wei and Stocker’s “law of human perception”, which relates the bias and variability of sensory estimates, also applies to number cognition. Prat-Carrabin and Woodford show that the bias and variance in participants’ estimates of numbers both depend on the numbers and on the prior, suggesting an optimal use of limited representational capacities through efficient coding and Bayesian decoding.
The transition to remote learning in the context of coronavirus disease 2019 (COVID-19) might have led to dramatic setbacks in education. Taking advantage of the fact that São Paulo State featured in-person classes for most of the first school quarter of 2020 but not thereafter, we estimate the effects of remote learning in secondary education using a differences-in-differences strategy that contrasts variation in students’ outcomes across different school quarters, before and during the pandemic. We also estimate intention-to-treat effects of reopening schools in the pandemic through a triple-differences strategy, contrasting changes in educational outcomes across municipalities and grades that resumed in-person classes or not over the last school quarter in 2020. We find that, under remote learning, dropout risk increased by 365% while test scores decreased by 0.32 s.d., as if students had only learned 27.5% of the in-person equivalent. Partially resuming in-person classes increased test scores by 20% relative to the control group.
Human languages are based on syntax, a set of rules which allow an infinite number of meaningful sentences to be constructed from a finite set of words. A theory associated with Chomsky and others holds that syntax is a mind-internal, universal structure independent of semantics. This theory, however, has been challenged by studies of the Chinese language showing that syntax is processed under the semantic umbrella, and is secondary and not independent. Here, using intracranial high-density electrocorticography, we find distinct spatiotemporal patterns of neural activity in the left inferior frontal gyrus that are specifically associated with syntactic and semantic processing of Chinese sentences. These results suggest that syntactic processing may occur before semantic processing. Our findings are consistent with the view that the human brain implements syntactic structures in a manner that is independent of semantics.
Misinformation threatens our societies, but little is known about how the production of news by unreliable sources relates to supply and demand dynamics. We exploit the burst of news production triggered by the COVID-19 outbreak through an Italian database partially annotated for questionable sources. We compare news supply with news demand, as captured by Google Trends data. We identify the Granger causal relationships between supply and demand for the most searched keywords, quantifying the inertial behaviour of the news supply. Focusing on COVID-19 news, we find that questionable sources are more sensitive than general news production to people’s interests, especially when news supply and demand mismatched. We introduce an index assessing the level of questionable news production solely based on the available volumes of news and searches. We contend that these results can be a powerful asset in informing campaigns against disinformation and providing news outlets and institutions with potentially relevant strategies. Studying news supply and demand amidst the COVID-19 pandemic in Italy, Gravino and coauthors show that news production by unreliable sources is more sensitive to the public interest than reliable news.
Explicit information obtained through instruction profoundly shapes human choice behaviour. However, this has been studied in computationally simple tasks, and it is unknown how model-based and model-free systems, respectively generating goal-directed and habitual actions, are affected by the absence or presence of instructions. We assessed behaviour in a variant of a computationally more complex decision-making task, before and after providing information about task structure, both in healthy volunteers and in individuals suffering from obsessive-compulsive or other disorders. Initial behaviour was model-free, with rewards directly reinforcing preceding actions. Model-based control, employing predictions of states resulting from each action, emerged with experience in a minority of participants, and less in those with obsessive-compulsive disorder. Providing task structure information strongly increased model-based control, similarly across all groups. Thus, in humans, explicit task structural knowledge is a primary determinant of model-based reinforcement learning and is most readily acquired from instruction rather than experience.
Detecting and learning temporal regularities is essential to accurately predict the future. A long-standing debate in cognitive science concerns the existence in humans of a dissociation between two systems, one for handling statistical regularities governing the probabilities of individual items and their transitions, and another for handling deterministic rules. Here, to address this issue, we used finger tracking to continuously monitor the online build-up of evidence, confidence, false alarms and changes-of-mind during sequence processing. All these aspects of behaviour conformed tightly to a hierarchical Bayesian inference model with distinct hypothesis spaces for statistics and rules, yet linked by a single probabilistic currency. Alternative models based either on a single statistical mechanism or on two non-commensurable systems were rejected. Our results indicate that a hierarchical Bayesian inference mechanism, capable of operating over distinct hypothesis spaces for statistics and rules, underlies the human capability for sequence processing. Maheu et al. show that human probabilistic and deterministic sequence processing can be modelled under a hierarchical Bayesian inference model, with distinct hypothesis spaces for statistics and rules, linked by a single probabilistic currency.
Making good decisions requires thinking ahead, but the huge number of actions and outcomes one could consider makes exhaustive planning infeasible for computationally constrained agents, such as humans. How people are nevertheless able to solve novel problems when their actions have long-reaching consequences is thus a long-standing question in cognitive science. To address this question, we propose a model of resource-constrained planning that allows us to derive optimal planning strategies. We find that previously proposed heuristics such as best-first search are near optimal under some circumstances but not others. In a mouse-tracking paradigm, we show that people adapt their planning strategies accordingly, planning in a manner that is broadly consistent with the optimal model but not with any single heuristic model. We also find systematic deviations from the optimal model that might result from additional cognitive constraints that are yet to be uncovered.
When interacting with infants, humans often alter their speech and song in ways thought to support communication. Theories of human child-rearing, informed by data on vocal signalling across species, predict that such alterations should appear globally. Here, we show acoustic differences between infant-directed and adult-directed vocalizations across cultures. We collected 1,615 recordings of infant- and adult-directed speech and song produced by 410 people in 21 urban, rural and small-scale societies. Infant-directedness was reliably classified from acoustic features only, with acoustic profiles of infant-directedness differing across language and music but in consistent fashions. We then studied listener sensitivity to these acoustic features. We played the recordings to 51,065 people from 187 countries, recruited via an English-language website, who guessed whether each vocalization was infant-directed. Their intuitions were more accurate than chance, predictable in part by common sets of acoustic features and robust to the effects of linguistic relatedness between vocalizer and listener. These findings inform hypotheses of the psychological functions and evolution of human communication.
Many countries have introduced cash transfer programmes as part of their poverty reduction and social protection strategies. These programmes have the potential to overcome drivers of HIV risk behaviours and usage of HIV services, but their overall effects on HIV-related outcomes remain unknown. Here we evaluate the effects of cash transfer programmes covering >5% of the impoverished population on country- and individual-level HIV-related outcomes in 42 countries with generalized epidemics. Cash transfer programmes were associated with a lower probability of sexually transmitted infections among females (odds ratio, 0.67; 95% confidence interval (CI), 0.50–0.91; P = 0.01), a higher probability of recent HIV testing among females (odds ratio, 2.61; 95% CI, 1.15–5.88; P = 0.02) and among males (odds ratio, 3.19; 95% CI, 2.45–4.15; P < 0.001), a reduction in new HIV infections (incidence rate ratio, 0.94; 95% CI, 0.89–0.99; P = 0.03) and delayed improvements in antiretroviral coverage (3%; 95% CI, 0.3–5.7 at year 2; P = 0.03) and AIDS-related deaths (incidence rate ratio, 0.91; 95% CI, 0.83–0.99 at year 2; P = 0.03). Anti-poverty programmes can play a greater role in achieving global targets for HIV prevention and treatment. Cash transfers are a popular anti-poverty strategy worldwide. In this study of 42 countries over 24 years, Richterman and Thirumurthy find that large cash transfer programmes were associated with improvements in a variety of HIV-related outcomes.
Growing evidence suggests that relative carbohydrate intake affects depression; however, the association between carbohydrates and depression remains controversial. To test this, we performed a two-sample bidirectional Mendelian randomization (MR) analysis using genetic variants associated with relative carbohydrate intake (N = 268,922) and major depressive disorder (N = 143,265) from the largest available genome-wide association studies. MR evidence suggested a causal relationship between higher relative carbohydrate intake and lower depression risk (odds ratio, 0.42 for depression per one-standard-deviation increment in relative carbohydrate intake; 95% confidence interval, 0.28 to 0.62; P = 1.49 × 10−5). Multivariable MR indicated that the protective effect of relative carbohydrate intake on depression persisted after conditioning on other diet compositions. The mediation analysis via two-step MR showed that this effect was partly mediated by body mass index, with a mediated proportion of 15.4% (95% confidence interval, 6.7% to 24.1%). These findings may inform prevention strategies and interventions directed towards relative carbohydrate intake and depression. Using genomic data and Mendelian randomization techniques, Yao and coauthors show that higher relative carbohydrate intake may have a protective effect, lowering depression risk.
‘Intuitive physics’ enables our pragmatic engagement with the physical world and forms a key component of ‘common sense’ aspects of thought. Current artificial intelligence systems pale in their understanding of intuitive physics, in comparison to even very young children. Here we address this gap between humans and machines by drawing on the field of developmental psychology. First, we introduce and open-source a machine-learning dataset designed to evaluate conceptual understanding of intuitive physics, adopting the violation-of-expectation (VoE) paradigm from developmental psychology. Second, we build a deep-learning system that learns intuitive physics directly from visual data, inspired by studies of visual cognition in children. We demonstrate that our model can learn a diverse set of physical concepts, which depends critically on object-level representations, consistent with findings from developmental psychology. We consider the implications of these results both for AI and for research on human cognition. Piloto et al. introduce a deep-learning system which is able to learn basic rules of the physical world, such as object solidity and persistence.
Economic inequality is associated with preferences for smaller, immediate gains over larger, delayed ones. Such temporal discounting may feed into rising global inequality, yet it is unclear whether it is a function of choice preferences or norms, or rather the absence of sufficient resources for immediate needs. It is also not clear whether these reflect true differences in choice patterns between income groups. We tested temporal discounting and five intertemporal choice anomalies using local currencies and value standards in 61 countries (N = 13,629). Across a diverse sample, we found consistent, robust rates of choice anomalies. Lower-income groups were not significantly different, but economic inequality and broader financial circumstances were clearly correlated with population choice patterns.