OARD: Open annotations for rare diseases and their phenotypes based on real-world data.

Diagnosis for rare genetic diseases often relies on phenotype-driven methods, which hinge on the accuracy and completeness of the rare disease phenotypes in the underlying annotation knowledgebase. Existing knowledgebases are often manually curated with additional annotations found in published case reports. Despite their potential, real-world data such as electronic health records (EHRs) have not been fully exploited to derive rare disease annotations. Here, we present open annotation for rare diseases (OARD), a real-world-data-derived resource with annotation for rare-disease-related phenotypes. This resource is derived from the EHRs of two academic health institutions containing more than 10 million individuals spanning wide age ranges and different disease subgroups. By leveraging ontology mapping and advanced natural-language-processing (NLP) methods, OARD automatically and efficiently extracts concepts for both rare diseases and their phenotypic traits from billing codes and lab tests as well as over 100 million clinical narratives. The rare disease prevalence derived by OARD is highly correlated with those annotated in the original rare disease knowledgebase. By performing association analysis, we identified more than 1 million novel disease-phenotype association pairs that were previously missed by human annotation, and >60% were confirmed true associations via manual review of a list of sampled pairs. Compared to the manual curated annotation, OARD is 100% data driven and its pipeline can be shared across different institutions. By supporting privacy-preserving sharing of aggregated summary statistics, such as term frequencies and disease-phenotype associations, it fills an important gap to facilitate data-driven research in the rare disease community.

NeuronBridge: an intuitive web application for neuronal morphology search across large data sets.

BACKGROUND: Neuroscience research in Drosophila is benefiting from large-scale connectomics efforts using electron microscopy (EM) to reveal all the neurons in a brain and their connections. To exploit this knowledge base, researchers relate a connectome's structure to neuronal function, often by studying individual neuron cell types. Vast libraries of fly driver lines expressing fluorescent reporter genes in sets of neurons have been created and imaged using confocal light microscopy (LM), enabling the targeting of neurons for experimentation. However, creating a fly line for driving gene expression within a single neuron found in an EM connectome remains a challenge, as it typically requires identifying a pair of driver lines where only the neuron of interest is expressed in both. This task and other emerging scientific workflows require finding similar neurons across large data sets imaged using different modalities. RESULTS: Here, we present NeuronBridge, a web application for easily and rapidly finding putative morphological matches between large data sets of neurons imaged using different modalities. We describe the functionality and construction of the NeuronBridge service, including its user-friendly graphical user interface (GUI), extensible data model, serverless cloud architecture, and massively parallel image search engine. CONCLUSIONS: NeuronBridge fills a critical gap in the Drosophila research workflow and is used by hundreds of neuroscience researchers around the world. We offer our software code, open APIs, and processed data sets for integration and reuse, and provide the application as a service at http://neuronbridge.janelia.org .

Repeat it without me: Crowdsourcing the T1 mapping common ground via the ISMRM reproducibility challenge.

PURPOSE: T1 mapping is a widely used quantitative MRI technique, but its tissue-specific values remain inconsistent across protocols, sites, and vendors. The ISMRM Reproducible Research and Quantitative MR study groups jointly launched a challenge to assess the reproducibility of a well-established inversion-recovery T1 mapping technique, using acquisition details from a seminal T1 mapping paper on a standardized phantom and in human brains. METHODS: The challenge used the acquisition protocol from Barral et al. (2010). Researchers collected T1 mapping data on the ISMRM/NIST phantom and/or in human brains. Data submission, pipeline development, and analysis were conducted using open-source platforms. Intersubmission and intrasubmission comparisons were performed. RESULTS: Eighteen submissions (39 phantom and 56 human datasets) on scanners by three MRI vendors were collected at 3 T (except one, at 0.35 T). The mean coefficient of variation was 6.1% for intersubmission phantom measurements, and 2.9% for intrasubmission measurements. For humans, the intersubmission/intrasubmission coefficient of variation was 5.9/3.2% in the genu and 16/6.9% in the cortex. An interactive dashboard for data visualization was also developed: https://rrsg2020.dashboards.neurolibre.org. CONCLUSION: The T1 intersubmission variability was twice as high as the intrasubmission variability in both phantoms and human brains, indicating that the acquisition details in the original paper were insufficient to reproduce a quantitative MRI protocol. This study reports the inherent uncertainty in T1 measures across independent research groups, bringing us one step closer to a practical clinical baseline of T1 variations in vivo.

The Coastal Carbon Library and Atlas: Open source soil data and tools supporting blue carbon research and policy.

Quantifying carbon fluxes into and out of coastal soils is critical to meeting greenhouse gas reduction and coastal resiliency goals. Numerous 'blue carbon' studies have generated, or benefitted from, synthetic datasets. However, the community those efforts inspired does not have a centralized, standardized database of disaggregated data used to estimate carbon stocks and fluxes. In this paper, we describe a data structure designed to standardize data reporting, maximize reuse, and maintain a chain of credit from synthesis to original source. We introduce version 1.0.0. of the Coastal Carbon Library, a global database of 6723 soil profiles representing blue carbon-storing systems including marshes, mangroves, tidal freshwater forests, and seagrasses. We also present the Coastal Carbon Atlas, an R-shiny application that can be used to visualize, query, and download portions of the Coastal Carbon Library. The majority (4815) of entries in the database can be used for carbon stock assessments without the need for interpolating missing soil variables, 533 are available for estimating carbon burial rate, and 326 are useful for fitting dynamic soil formation models. Organic matter density significantly varied by habitat with tidal freshwater forests having the highest density, and seagrasses having the lowest. Future work could involve expansion of the synthesis to include more deep stock assessments, increasing the representation of data outside of the U.S., and increasing the amount of data available for mangroves and seagrasses, especially carbon burial rate data. We present proposed best practices for blue carbon data including an emphasis on disaggregation, data publication, dataset documentation, and use of standardized vocabulary and templates whenever appropriate. To conclude, the Coastal Carbon Library and Atlas serve as a general example of a grassroots F.A.I.R. (Findable, Accessible, Interoperable, and Reusable) data effort demonstrating how data producers can coordinate to develop tools relevant to policy and decision-making.

Ambivalent Sexism and Tolerance of Violence Against Women in India.

We examined associations between sexist beliefs and tolerance of violence against women in India using a nationally representative probability sample of adults (n = 133,398). Research consistently indicates that hostile sexism fosters tolerance of violence against women. However, benevolent sexism is sometimes associated with higher tolerance and sometimes with lower tolerance of violence. We proposed that this inconsistency could be resolved by considering the source of violence: Is violence perpetrated by outsiders or intimate partners? Results of a multigroup structural equation model showed that endorsement of hostile sexism was related to greater tolerance of violence regardless of the source. In contrast, endorsement of benevolent sexism was associated with lower tolerance of violence from outsiders but was simultaneously associated with higher tolerance of spousal violence. These opposing processes indicate that although benevolent sexism promises women protection from violence, the very same ideology legitimizes spousal violence, thereby reinforcing men's power within intimate relationships.

Preregistered Replication and Extension of "Moral Hypocrisy: Social Groups and the Flexibility of Virtue".

The tendency for people to consider themselves morally good while behaving selfishly is known as moral hypocrisy. Influential work by Valdesolo and DeSteno (2007) found evidence for intergroup moral hypocrisy such that people were more forgiving of transgressions when they were committed by an in-group member than an out-group member. We conducted two experiments to examine moral hypocrisy and group membership in an online paradigm with Prolific workers from the United States: a direct replication of the original work with minimal groups (N = 610; nationally representative) and a conceptual replication with political groups (N = 606; 50% Democrats and 50% Republicans). Although the results did not replicate the original findings, we observed evidence of in-group favoritism in minimal groups and out-group derogation in political groups. The current research finds mixed evidence of intergroup moral hypocrisy and has implications for understanding the contextual dependencies of intergroup bias and partisanship.

Caricaturing Shapes in Visual Memory.

When representing high-level stimuli, such as faces and animals, we tend to emphasize salient features-such as a face's prominent cheekbones or a bird's pointed beak. Such mental caricaturing leaves traces in memory, which exaggerates these distinctive qualities. How broadly does this phenomenon extend? Here, in six experiments (N = 700 adults), we explored how memory automatically caricatures basic units of visual processing-simple geometric shapes-even without task-related demands to do so. Participants saw a novel shape and then immediately adjusted a copy of that shape to match what they had seen. Surprisingly, participants reconstructed shapes in exaggerated form, amplifying curvature, enlarging salient parts, and so on. Follow-up experiments generalized this bias to new parameters, ruled out strategic responding, and amplified the effects in serial transmission. Thus, even the most basic stimuli we encounter are remembered as caricatures of themselves.

Can Invalid Information Be Ignored When It Is Detected?

With the rapid spread of information via social media, individuals are prone to misinformation exposure that they may utilize when forming beliefs. Over five experiments (total N = 815 adults, recruited through Amazon Mechanical Turk in the United States), we investigated whether people could ignore quantitative information when they judged for themselves that it was misreported. Participants recruited online viewed sets of values sampled from Gaussian distributions to estimate the underlying means. They attempted to ignore invalid information, which were outlier values inserted into the value sequences. Results indicated participants were able to detect outliers. Nevertheless, participants' estimates were still biased in the direction of the outlier, even when they were most certain that they detected invalid information. The addition of visual warning cues and different task scenarios did not fully eliminate systematic over- and underestimation. These findings suggest that individuals may incorporate invalid information they meant to ignore when forming beliefs.

When and Why People Conceal Infectious Disease.

People sick with infectious illnesses face negative social outcomes, like exclusion, and may take steps to conceal their illnesses from others. In 10 studies of past, current, and projected illness, we examined the prevalence and predictors of infection concealment in adult samples of U.S. university students, health-care employees, and online crowdsourced workers (total N = 4,110). About 75% reported concealing illness in interpersonal interactions, possibly placing others in harm's way. Concealment motives were largely social (e.g., wanting to attend events like parties) and achievement oriented (e.g., completing work objectives). Disease characteristics, including potential harm and illness immediacy, also influenced concealment decisions. People imagining harmful (vs. mild) infections concealed illness less frequently, whereas participants who were actually sick concealed frequently regardless of illness harm, suggesting state-specific biases underlying concealment decisions. Disease concealment appears to be a widely prevalent behavior by which concealers trade off risks to others in favor of their own goals, creating potentially important public-health consequences.

Perceptions of Falling Behind "Most White People": Within-Group Status Comparisons Predict Fewer Positive Emotions and Worse Health Over Time Among White (but Not Black) Americans.

Despite the persistence of anti-Black racism, White Americans report feeling worse off than Black Americans. We suggest that some White Americans may report low well-being despite high group-level status because of perceptions that they are falling behind their in-group. Using census-based quota sampling, we measured status comparisons and health among Black (N = 452, Wave 1) and White (N = 439, Wave 1) American adults over a period of 6 to 7 weeks. We found that Black and White Americans tended to make status comparisons within their own racial groups and that most Black participants felt better off than their racial group, whereas most White participants felt worse off than their racial group. Moreover, we found that White Americans' perceptions of falling behind "most White people" predicted fewer positive emotions at a subsequent time, which predicted worse sleep quality and depressive symptoms in the future. Subjective within-group status did not have the same consequences among Black participants.

Dissociable Codes in Motor Working Memory.

Working memory has been comprehensively studied in sensory domains, like vision, but little attention has been paid to how motor information (e.g., kinematics of recent movements) is maintained and manipulated in working memory. "Motor working memory" (MWM) is important for short-term behavioral control and skill learning. Here, we employed tasks that required participants to encode and recall reaching movements over short timescales. We conducted three experiments (N = 65 undergraduates) to examine MWM under varying cognitive loads, delays, and degrees of interference. The results support a model of MWM that includes an abstract code that flexibly transfers across effectors, and an effector-specific code vulnerable to interfering movements, even when interfering movements are irrelevant to the task. Neither code was disrupted by increasing visuospatial working memory load. These results echo distinctions between representational formats in other domains, suggesting that MWM shares a basic computational structure with other working memory subsystems.

Investigating Inattentional Blindness Through the Lens of Fear Chemosignals.

Inattentional blindness is a phenomenon wherein people fail to perceive obvious stimuli within their vision, sometimes leading to dramatic consequences. Research on the effects of fear chemosignals suggests that they facilitate receivers' sensory acquisition. We aimed to examine the interplay between these phenomena, investigating whether exposure to fear chemosignals (vs. rest body odors) can reduce the inattentional-blindness handicap. Utilizing a virtual-reality aquarium, we asked participants to count how many morsels a school of fish consumed while two unexpected stimuli swam by. We predicted that participants exposed to fear chemosignals (N = 131) would detect unexpected stimuli significantly more often than participants exposed to rest body odors (N = 125). All participants were adult Portuguese university students aged 18 to 40 years. The results confirmed our hypothesis, χ2(1) = 6.10, p = .014, revealing that exposure to fear chemosignals significantly increased the detection of unexpected stimuli by about 10%. The implications of our findings open a novel avenue for reducing the adverse consequences of inattentional blindness.

Cutting Through the Noise: Auditory Scenes and Their Effects on Visual Object Processing.

Despite the intuitive feeling that our visual experience is coherent and comprehensive, the world is full of ambiguous and indeterminate information. Here we explore how the visual system might take advantage of ambient sounds to resolve this ambiguity. Young adults (ns = 20-30) were tasked with identifying an object slowly fading in through visual noise while a task-irrelevant sound played. We found that participants demanded more visual information when the auditory object was incongruent with the visual object compared to when it was not. Auditory scenes, which are only probabilistically related to specific objects, produced similar facilitation even for unheard objects (e.g., a bench). Notably, these effects traverse categorical and specific auditory and visual-processing domains as participants performed across-category and within-category visual tasks, underscoring cross-modal integration across multiple levels of perceptual processing. To summarize, our study reveals the importance of audiovisual interactions to support meaningful perceptual experiences in naturalistic settings.

The Basic Units of Working Memory Manipulation Are Boolean Maps, Not Objects.

Determining the manipulation unit of working memory is one of the fundamental questions in understanding how working memory functions. The prevalent object-based theory in cognitive research predicts that memory manipulation is performed on the level of objects. Here we show instead that the basic units of working memory manipulation are Boolean maps, a data structure describing what can be perceived in an instant. We developed four new manipulation tasks (with data from 80 adults) and showed that manipulation times only increased when the number of Boolean maps manipulated increased. Increasing the number of orientations manipulated did not induce longer manipulation times, consistent with a key prediction of the Boolean map theory. Our results show that Boolean maps are the manipulation unit of working memory.

Sensitivity to the Instrumental Value of Choice Increases Across Development.

Across development, people tend to demonstrate a preference for contexts in which they have the opportunity to make choices. However, it is not clear how children, adolescents, and adults learn to calibrate this preference based on the costs and benefits of agentic choice. Here, in both a primary, in-person, reinforcement-learning experiment (N = 92; age range = 10-25 years) and a preregistered online replication study (N = 150; age range = 8-25 years), we found that participants overvalued agentic choice but also calibrated their agency decisions to the reward structure of the environment, increasingly selecting agentic choice when choice had greater instrumental value. Regression analyses and computational modeling of participant choices revealed that participants' bias toward agentic choice-reflecting its intrinsic value-remained consistent across age, whereas sensitivity to the instrumental value of agentic choice increased from childhood to early adulthood.

White by Another Name? Can Anti-Christian Bias Claims Serve as a Racial Dog Whistle?

Four preregistered experiments (N = 4,307) explored whether anti-Christian bias claims can discreetly signal White allyship among Christian American adults. In Experiments 1 and 2, reading about anti-Christian bias led White, but not Black, Christians to perceive more anti-White bias. Experiments 3 and 4 demonstrate the connection between Christian and White can be leveraged by politicians in the form of a racial dog whistle. In Experiment 3, White Christians perceived a politician concerned about anti-Christian bias as caring more about anti-White bias and more willing to fight for White people (relative to a control). This politician was also perceived as less offensive than a politician concerned about anti-White bias. In Experiment 4, Black Christians perceived a politician concerned about anti-Christian bias as less offensive than one concerned about anti-White bias yet still unlikely to fight for Black people. Results suggest "anti-Christian bias" can provide a relatively palatable way to signal allegiance to White people.

Exploring the Semantic-Inconsistency Effect in Scenes Using a Continuous Measure of Linguistic-Semantic Similarity.

Viewers use contextual information to visually explore complex scenes. Object recognition is facilitated by exploiting object-scene relations (which objects are expected in a given scene) and object-object relations (which objects are expected because of the occurrence of other objects). Semantically inconsistent objects deviate from these expectations, so they tend to capture viewers' attention (the semantic-inconsistency effect). Some objects fit the identity of a scene more or less than others, yet semantic inconsistencies have hitherto been operationalized as binary (consistent vs. inconsistent). In an eye-tracking experiment (N = 21 adults), we study the semantic-inconsistency effect in a continuous manner by using the linguistic-semantic similarity of an object to the scene category and to other objects in the scene. We found that both highly consistent and highly inconsistent objects are viewed more than other objects (U-shaped relationship), revealing that the (in)consistency effect is more than a simple binary classification.

The Formation of Negative Attitudes Toward Novel Groups.

People perceive out-groups, minorities, and novel groups more negatively than in-groups, majorities, and familiar groups. Previous research has argued that such intergroup biases may be caused by the order in which people typically encounter social groups. Groups that are relatively novel to perceivers (e.g., out-groups, minorities) are primarily associated with distinct attributes that differentiate them from familiar groups. Because distinct attributes are typically negative, attitudes toward novel groups are negatively biased. Five experiments (N = 2,615 adults) confirmed the generalizability of the novel groups' disadvantage to different aspects of attitude formation (i.e., evaluations, memory, stereotyping), to cases with more than two groups, and to cases in which groups were majority/minority or in-groups/out-groups. Our findings revealed a remarkably robust influence of learning order in the formation of group attitudes, and they imply that people often perceive novel groups more negatively than they actually are.

Once and Again: Repeated Viewing Affects Judgments of Spontaneity and Preparation.

Reality is fleeting, and any moment can only be experienced once. Rewatching a video, however, allows people to repeatedly observe the exact same moment. We propose that people may fail to fully distinguish between merely observing behavior again (through replay) from that behavior being performed again in the exact same way. Using an assortment of stimuli that included auditions, commercials, and potential trial evidence, we demonstrated through nine experiments (N = 10,412 adults in the United States) that rewatching makes a recorded behavior appear more rehearsed and less spontaneous, as if the actors were simply precisely repeating their actions. These findings contribute to an emerging literature showing that incidental video features, like perspective or slow motion, can meaningfully change evaluations. Replay may inadvertently shape judgments in both mundane and consequential contexts. To understand how a video will influence its viewer, one will need to consider not only its content, but also how often it is viewed.

Learning From Aggregated Opinion.

The capacity to leverage information from others' opinions is a hallmark of human cognition. Consequently, past research has investigated how we learn from others' testimony. Yet a distinct form of social information-aggregated opinion-increasingly guides our judgments and decisions. We investigated how people learn from such information by conducting three experiments with participants recruited online within the United States (N = 886) comparing the predictions of three computational models: a Bayesian solution to this problem that can be implemented by a simple strategy for combining proportions with prior beliefs, and two alternatives from epistemology and economics. Across all studies, we found the strongest concordance between participants' judgments and the predictions of the Bayesian model, though some participants' judgments were better captured by alternative strategies. These findings lay the groundwork for future research and show that people draw systematic inferences from aggregated opinion, often in line with a Bayesian solution.