Reward-Related Brain Activity Mediates the relationship between Decision-Making Deficits and Pediatric Depression Symptom Severity.

BACKGROUND: The mechanisms linking neural and behavioral indices of reduced reward sensitivity in depression, particularly in children, remain unclear. Reward positivity (RewP), a neural index of reward processing, has been consistently associated with depression. Separately, recent studies using the drift-diffusion model (DDM) on behavioral data have delineated computational indices of reward sensitivity. Therefore, the present study examined whether RewP is a neural mediator of DDM-based indices of reward processing in predicting pediatric depression across varying levels of symptom severity. METHODS: A community sample of 166 girls, aged 8 to 14 years, completed two tasks. The first was a reward guessing task from which RewP was computed using electroencephalography; the second was a probabilistic reward-based decision-making task. On this second task, DDM analysis was applied to behavioral data to quantify the efficiency of accumulating reward-related evidence (drift rate) and potential baseline bias (starting point) towards the differently rewarded choices. Depression severity was measured using the self-report Children's Depression Inventory (CDI). RESULTS: RewP was correlated with drift rate, but not starting point bias, towards the more rewarded choice. Furthermore, RewP completely mediated the association between a slower drift rate towards the more rewarded option and higher depression symptom severity. CONCLUSION: Our findings suggest that reduced neural sensitivity to reward feedback might be a neural mechanism underscoring behavioral insensitivity to reward in children and adolescents with higher depression symptom severity, offering novel insights into the relationship between neural and computational indices of reward processing in this context.

Neural response to monetary and social rewards in adolescent girls and their parents.

Functional magnetic resonance imaging (fMRI) studies have indicated that the mesocorticolimbic dopamine system is heavily involved in all stages of reward processing. However, the majority of research has been conducted using monetary rewards and it is unclear to what extent other types of rewards, such as social rewards, evoke similar or different neural activation. There have also been few investigations into potential differences or similarities between reward processing in parents and offspring. The present study examined fMRI neural activation in response to monetary and social reward in a sample of 14-22-year-old adolescent girls (N = 145) and a biological parent (N = 124) and compared activation across adolescent-parent dyads (N = 82). Across all participants, both monetary and social reward elicited bilateral striatal activation, which did not differ between reward types or between adolescents and their parents. Neural activation in response to the different reward types were positively correlated in the striatum among adolescents and in the mPFC and OFC among parents. Overall, the present study suggests that both monetary and social reward elicit striatal activation regardless of age and provides evidence that neural mechanisms underlying reward processing may converge differentially among youth and adults.

The Prospective Predictive Power of Parent-Reported Personality Traits and Facets in First-Onset Depression in Adolescent Girls.

Certain personality traits and facets are well-known risk factors that predict first-onset depression during adolescence. However, prior research predominantly relied on self-reported data, which has limitations as a source of personality information. Reports from close informants have the potential to increase the predictive power of personality on first-onsets of depression in adolescents. With easy access to adolescents' behaviors across settings and time, parents may provide important additional information about their children's personality. The same personality trait(s) and facet(s) rated by selves (mean age 14.4 years old) and biological parents at baseline were used to prospectively predict depression onsets among 442 adolescent girls during a 72-month follow-up. First, bivariate logistic regression was used to examine whether parent-reported personality measures predicted adolescent girls' depression onsets; then multivariate logistic regression was used to test whether parent reports provided additional predictive power above and beyond self-reports of same trait or facet. Parent-reported personality traits and facets predicted adolescents' depression onsets, similar to findings using self-reported data. After controlling for the corresponding self-report measures, parent-reported higher openness (at the trait level) and higher depressivity (at the facet-level) incrementally predicted first-onset of depression in the sample. Findings demonstrated additional variance contributed by parent-reported personality measures and validated a multi-informant approach in using personality to prospectively predict onsets of depression in adolescent girls.

Knowledge of Threat Biases Perceptual Decision Making in Anxiety: Evidence From Signal Detection Theory and Drift Diffusion Modeling.

Background: Threat biases are considered key factors in the development and maintenance of anxiety. However, these biases are poorly operationalized and remain unquantified. Furthermore, it is unclear whether and how prior knowledge of threat and its uncertainty induce these biases and how they manifest in anxiety. Method: Participants (n = 55) used prestimulus cues to decide whether the subsequently presented stimuli were threatening or neutral. The cues either provided no information about the probability (high uncertainty) or indicated high probability (low uncertainty) of encountering threatening or neutral targets. We used signal detection theory and hierarchical drift diffusion modeling to quantify bias. Results: High-uncertainty threat cues improved discrimination of subsequent threatening and neutral stimuli more than neutral cues. However, anxiety was associated with worse discrimination of threatening versus neutral stimuli following high-uncertainty threat cues. Using hierarchical drift diffusion modeling, we found that threat cues biased decision making not only by shifting the starting point of evidence accumulation toward the threat decision but also by increasing the efficiency with which sensory evidence was accumulated for both threat-related and neutral decisions. However, higher anxiety was associated with a greater shift of starting point toward the threat decision but not with the efficiency of evidence accumulation. Conclusions: Using computational modeling, these results highlight the biases by which knowledge regarding uncertain threat improves perceptual decision making but impairs it in case of anxiety.

Metal-assisted core-shell plasmonic nanoparticles for small molecule biothiol analysis and enantioselective recognition.

Cysteine (Cys) enantiomorphs, important small-molecule biothiols, participate in various antioxidative, flavoring, and poison-removing processes in the food industry. Current cysteine enantiomorph analysis methods require effective strategies for distinguishing them due to their similar structures and reactivity. Herein, we present a metal ion-assisted enantiomorph-selective surface-enhanced Raman scattering (SERS) biosensor based on an amphiphilic polymer matrix (APM), which can promote cysteine enantiomorph (L/D-Cys) identification. The highly selective molecular orientation is perhaps caused by the intermolecular hydrogen bonding with chiral isomers (metal centers). The experimental results show that the SERS biosensor has a sensitivity-distincting factor toward L-Cys and D-Cys. The linear range is from 1 mmol L-1 to 1 nmol L-1, along with a low limit of detection of 0.77 pmol L-1. Moreover, the fabricated Cu-APM biosensor exhibits remarkable stability and high repeatability, with an RSD of 3.7%. Real food cysteine enantiomorph detection was performed with L-Cys-containing samples of onion, cauliflower, garlic, and apple, and D-Cys-containing samples of vinegar, black garlic, cheese, and beer. The results show that the Cu-APM biosensor can be utilized as a powerful tool for real-time determination of Cys enantiomorphs in different food samples. Thus, the metal-ion-assisted enantiomorph-selective SERS biosensor has potential as an adaptable tool for enantiomorph detection and food sample analysis.

Understanding anxiety through uncertainty quantification.

Uncertainty has been a central concept in psychological theories of anxiety. However, this concept has been plagued by divergent connotations and operationalizations. The lack of consensus hinders the current search for cognitive and biological mechanisms of anxiety, jeopardizes theory creation and comparison, and restrains translation of basic research into improved diagnoses and interventions. Drawing upon uncertainty decomposition in Bayesian Decision Theory, we propose a well-defined conceptual structure of uncertainty in cognitive and clinical sciences, with a focus on anxiety. We discuss how this conceptual structure provides clarity and can be naturally applied to existing frameworks of psychopathology research. Furthermore, it allows formal quantification of various types of uncertainty that can benefit both research and clinical practice in the era of computational psychiatry.

Anti-galvanic reaction induced interfacial engineering to reconstruct ternary colloid satellite platform for exceptionally high-performance redox-responsive sensor.

The anti-galvanic reaction (AGR), which is a classic galvanic reaction (GR) with an opposite effect, is a unique phenomenon associated with the quantum size effect. This reaction involves the interaction between metal ions and nanoclusters, offering opportunities to create well-defined nanomaterials and diverse reductive behavior. In hence, in our work, we utilize the AGR to generate gold (Au), silver (Ag), and copper (Cu) satellite nanoclusters which have superior electromagnetic properties for Surface-enhanced Raman spectroscopy (SERS) sensor. As the AGR process, weak oxidant Cu2+ is selected to etched matrix Au@Ag NPs, reduced to Cu(0) or Cu(1) and generated the ultrasmall metal nanoparticles (Ag). To facilitate the AGR, we introduce the nucleophilic thiol 4-mercaptopyridine (4-Mpy) to bridge the metal ions or ultrasmall metal nanoparticles to reconstruct the satellite nanoclusters. These experimental displays that the AGR based biosensors has highly sensitivity for reductive molecule glucose. The liner ranges from 1 mmol/L to 1 nmol/L and alongs with a correlation coefficient and detection limit (LOD) of 0.999 and 0.14 nmol/L. Moreover, the AGR based biosensors exhibits remarkable stability and high repeatability with RSD 1.3 %. The food samples are tested to further investigate the accuracy and reliability of the method, which provides a novel and effective SERS method for the reduction molecules detection.

Hallucination-Proneness is Associated With a Decrease in Robust Averaging of Perceptual Evidence.

BACKGROUND AND HYPOTHESIS: Hallucinations are characterized by disturbances in perceptual decision-making about environmental stimuli. When integrating across multiple stimuli to form a perceptual decision, typical observers engage in "robust averaging" by down-weighting extreme perceptual evidence, akin to a statistician excluding outlying data. Furthermore, observers adapt to contexts with more unreliable evidence by increasing this down-weighting strategy. Here, we test the hypothesis that hallucination-prone individuals (n = 38 high vs n = 91 low) would show a decrease in this robust averaging and diminished sensitivity to changes in evidence variance. STUDY DESIGN: We used a multielement perceptual averaging task to elicit dichotomous judgments about the "average color" (red/blue) of an array of stimuli in trials with varied strength (mean) and reliability (variance) of decision-relevant perceptual evidence. We fitted computational models to task behavior, with a focus on a log-posterior-ratio (LPR) model which integrates evidence as a function of the log odds of each perceptual option and produces a robust averaging effect. STUDY RESULTS: Hallucination-prone individuals demonstrated less robust averaging, seeming to weigh inlying and outlying extreme or untrustworthy evidence more equally. Furthermore, the model that integrated evidence as a function of the LPR of the two perceptual options and produced robust averaging showed poorer fit for the group prone to hallucinations. Finally, the weighting strategy in hallucination-prone individuals remained insensitive to evidence variance. CONCLUSIONS: Our findings provide empirical support for theoretical proposals regarding evidence integration aberrations in psychosis and alterations in the perceptual systems that track statistical regularities in environmental stimuli.

Virus-Like Magnetic Heterostructure: an Outstanding Metal-Complex Active Platform Enables High-Efficiency Separation and Catalysis.

Assembled heterostructure systems, as emerging functional materials, have broad applications ranging from enzyme and drug payload to catalysis and purification. However, these require trial- and -error design process and complex experimental environment to generate heterostructure materials. Here, this study describes an easy-to-execute strategy to fabricate magnetic heterostructure as multifunctional delivery system. We utilize first-row transition metal copper and nitroso/amino ligand as modules to assemble around Fe3 O4 magnetic nanoparticles by excessed mild stimuli and fabricate the magnetic heterostructure materials (Fe3 O4 @ TACN NPs (tetraamminecopper (II) nitrate)). Notably, the Fe3 O4 @ TACN NPs present with cat's-whisker structure containing ligand and metal center. The nitroso-group ligands exhibit strong binding affinity to heme-structure enzyme, ensuring effective capture and isolate of cytochrome C (Cyt-c), resulting in their excellent isolation property. The copper complex-powered magnetic heterostructure materials can effectively isolation Cyt-c from complex biological sample (pork heart). Importantly, the Fe3 O4 @ TACN NPs coordinated with heme-structure, induced methionine 80 (Met80) disassociates from heme prosthetic group, and contributed to peroxidase-like (POD-like) activities increasing. These results exhibit that copper complex-powered magnetic heterostructure materials can not only satisfy the Cyt-c isolation and immobilization in an alkaline medium, but also be of the potential for improving the immobilization enzyme reactor performance.

The interpersonal computational psychiatry of social coordination in schizophrenia.

Impairments in social coordination form a core dimension of various psychiatric disorders, including schizophrenia. Advances in interpersonal and computational psychiatry support a major change in studying social coordination in schizophrenia. Although these developments provided novel perspectives to study how interpersonal activities shape coordination and to examine computational mechanisms, direct attempts to integrate the two methodologies have been sparse. Here, we propose an interpersonal computational framework that (1) leverages the active inference framework to model aberrant social coordination processes in schizophrenia and (2) incorporates dynamical system models to dissect intrapersonal and interpersonal synchronisation to inform a statistical model based on active inference. We discuss how this interpersonal computational psychiatry framework can elucidate the aberrant processes leading to psychopathology, with schizophrenia as an example, and highlight how it might aid clinical intervention and practice. Finally, we discuss challenges and opportunities for using the framework in studying social coordination impairments.

Towards a global partnership model in interprofessional education for cross-sector problem-solving.

OBJECTIVES: A partnership model in interprofessional education (IPE) is important in promoting a sense of global citizenship while preparing students for cross-sector problem-solving. However, the literature remains scant in providing useful guidance for the development of an IPE programme co-implemented by external partners. In this pioneering study, we describe the processes of forging global partnerships in co-implementing IPE and evaluate the programme in light of the preliminary data available. METHODS: This study is generally quantitative. We collected data from a total of 747 health and social care students from four higher education institutions. We utilized a descriptive narrative format and a quantitative design to present our experiences of running IPE with external partners and performed independent t-tests and analysis of variance to examine pretest and posttest mean differences in students' data. RESULTS: We identified factors in establishing a cross-institutional IPE programme. These factors include complementarity of expertise, mutual benefits, internet connectivity, interactivity of design, and time difference. We found significant pretest-posttest differences in students' readiness for interprofessional learning (teamwork and collaboration, positive professional identity, roles, and responsibilities). We also found a significant decrease in students' social interaction anxiety after the IPE simulation. CONCLUSIONS: The narrative of our experiences described in this manuscript could be considered by higher education institutions seeking to forge meaningful external partnerships in their effort to establish interprofessional global health education.

Self-schemas and information processing biases as mechanisms underlying sexual orientation disparities in depressive symptoms: Results from a longitudinal, population-based study.

Sexual minority individuals experience higher prevalence of major depression and more frequent depressive symptoms compared to heterosexual individuals. Although existing theories have suggested cognitive mechanisms that may explain these disparities, empirical tests are limited by a reliance on cross-sectional designs, self-reported measures, and nonprobability samples. We analyzed data from a longitudinal, population-based study of young adults (N = 1,065; n = 497 sexual minority) who completed validated measures of depressive symptoms over a 3-year period; at Wave 2, participants completed the self-referent encoding task, a behavioral task assessing self-schemas and information processing biases. Self-schemas were measured with the drift rate, which was estimated via the composite of endorsement of positive or negative words as self-referential (or not) and the reaction time for these decisions. Information processing biases were operationalized as the total number of negative words that were both endorsed as self-referential and recalled after the task, divided by the total number of words endorsed and recalled. Compared to heterosexuals, sexual minorities displayed significantly higher negative self-schemas and recalled a significantly higher proportion of negative words endorsed as self-referential, relative to total number of words. In turn, these differences in self-schemas and information processing biases mediated the sexual orientation disparity in depressive symptoms. Moreover, among sexual minorities, perceived discrimination predicted greater negative self-schemas and information processing biases, which mediated the prospective association between discrimination and depressive symptoms. These findings provide the strongest evidence to date for cognitive risk factors that underlie sexual orientation disparities in depression, highlighting potential intervention targets. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Linking the past to the future by predictive processing: Implications for psychopathology.

Most theories of psychopathology have focused on etiology at a specific level (e.g., genetic, neurobiological, psychological, or environmental) to explain specific symptoms or disorders. A few biopsychosocial theories have provided explanations that attempt to integrate different levels and disorders to some extent. However, these theories lack a framework in which different levels of analysis are integrated and thus do not explain the mechanism by which etiological factors interact and perturb neurobiology which in turn leads to psychopathology. We propose that predictive processing (PP), which originated in theoretical neurobiology literature, may provide a conceptually parsimonious and biologically plausible framework to achieve such integration. In PP, the human brain can be cast as implementing a generative model whose task is to minimize the surprise of sensory evidence by inferring its causes and actively controlling future sensory signals via action. This account offers a unifying model of perception, action, and emotion implicated in psychopathology. Furthermore, we show that PP can explain how different factors or levels result in psychopathology via updates of the generative model (the depth of the PP framework). Finally, we demonstrate the transdiagnostic appeal of PP by showing how perturbations within this framework can explain a broad range of psychopathology (the breadth of the PP framework), with a focus on bridging well-established psychosocial theories of psychopathology and PP. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Students' interaction anxiety and social phobia in interprofessional education in Hong Kong: mapping a new research direction.

BACKGROUND: Interprofessional education (IPE) has been promoted as a breakthrough in healthcare because of the impact when professionals work as a team. However, despite its inception dating back to the 1960s, its science has taken a long time to advance. There is a need to theorize IPE to cultivate creative insights for a nuanced understanding of IPE. This study aims to propose a research agenda on social interaction by understanding the measurement scales used and guiding researchers to contribute to the discussion of social processes in IPE. METHOD: This quantitative research was undertaken in a cross-institutional IPE involving 925 healthcare students (Medicine, Nursing, Social Work, Chinese Medicine, Pharmacy, Speech Language Pathology, Clinical Psychology, Food and Nutritional Science and Physiotherapy) from two institutions in Hong Kong. Participants completed the Social Interaction Anxiety Scale (SIAS-6) and Social Phobia Scale (SPS-6). We applied a construct validation approach: within-network and between-network validation. We performed confirmatory factors analysis, t-test, analysis of variance and regression analysis. RESULTS: CFA results indicated that current data fit the a priori model providing support to within-network validity [RMSEA=.08, NFI=.959, CFI=.965, IFI=.965, TLI=.955]. The criteria for acceptable fit were met. The scales were invariant between genders, across year levels and disciplines. Results indicated that social interaction anxiety and social phobia negatively predicted behavioural engagement (F = 25.093, p<.001, R2=.065) and positively predicted behavioural disaffection (F = 22.169, p<.001, R2=.057) to IPE, suggesting between-network validity. CONCLUSIONS: Our data provided support for the validity of the scales when used among healthcare students in Hong Kong. SIAS-6 and SPS-6 have sound psychometric properties based on students' data in Hong Kong. We identified quantitative, qualitative and mixed methods research designs to guide researchers in getting involved in the discussion of students' social interactions in IPE.Key MessagesThe Social Anxiety Scale (SIAS-6) and Social Phobia Scale (SPS-6) scales have sound psychometric properties based on the large-scale healthcare students' data in IPE in Hong Kong.Social interaction anxiety and social phobia negatively predicted students' behavioural engagement with IPE and positively predicted behavioural disaffection. The scales are invariant in terms of gender, year level and discipline.Quantitative, qualitative and mixed methods studies are proposed to aid researchers to contribute in healthcare education literature using the SIAS-6 and SPS-6.

Photoluminescence Sensing of Soluble Lead in Children's Crayons Using Perovskite Nanocrystal In Situ Growth on an Aluminum Hydroxide Layer.

In this study, a fluorescence sensing approach for lead ion (Pb2+) was developed using in situ growth of methylamine lead bromine (MAPbBr3) perovskite on an aluminum hydroxide (Al(OH)3) thin layer. The Al(OH)3 thin layer could be obtained on a glass slide by liquid phase deposition and is of a large specific surface area and insoluble in water. After sulfhydryl functionalization, the Al(OH)3 thin layer reveals effective adsorption and excellent enrichment ability to Pb2+ and is additionally used as the substrate for the in situ growth of lead halogen perovskite. The fluorescence sensing of Pb2+ could be realized by the fluorescence intensity of lead halogen perovskite on the Al(OH)3 layer. The linear relationship between the fluorescence intensity and the concentration of Pb2+ was found in the range from 80 to 1500 mg/kg. The detection limit of Pb2+ is found to be 40 mg/kg, which is lower than the maximum permission of lead residue in student products (90 mg/kg) stipulated by the National Standard of the People's Republic of China (GB21027-2020). After being grinded and pre-treated, soluble lead in watercolor paint and crayon samples can be extracted by the sulfhydryl functionalization Al(OH)3 layer, then lead halogen perovskite can be generated in situ on the layer to achieve the fluorescence sensing for the determination of soluble lead in the samples.

The Impact of Interpretation Biases on Psychological Responses to the COVID-19 Pandemic: a Prospective Study.

BACKGROUND: This study investigates the longitudinal role of interpretation biases in the development and maintenance of health anxiety during the pandemic. Individual differences in behavioural responses to the virus outbreak and decision-making were also examined. METHODS: Two hundred seventy-nine individuals from a pre-pandemic study of interpretation bias and health anxiety completed an online survey during the third wave of the COVID-19 pandemic in Hong Kong. Participants' health anxiety, interpretation biases, and COVID-specific behaviours (i.e. practice of social distancing, adherence to preventive measures, information seeking), and health decision-making were assessed. RESULTS: Pre-pandemic tendencies to interpret ambiguous physical sensations as signals for illness did not predict health anxiety during the pandemic, b = -0.020, SE = 0.024, t = -0.843, p = .400, 99% CI [-0.082, 0.042], but were associated with a preference for risky treatment option for COVID-19, b = 0.026, SE = 0.010, Wald = 2.614, p = .009, OR = 1.026, 99% CI [1.001, 1.054]. Interpretation biases and health anxiety symptoms during the pandemic were associated with each other and were both found to be significant predictors of practice of social distancing, adherence to preventive measures, and information seeking behaviour. CONCLUSIONS: This study adds to the growing evidence of the role of interpretation biases in health anxiety and the way that people respond to the ongoing pandemic.

Inferring Trajectories of Psychotic Disorders Using Dynamic Causal Modeling.

Introduction: Illness course plays a crucial role in delineating psychiatric disorders. However, existing nosologies consider only its most basic features (e.g., symptom sequence, duration). We developed a Dynamic Causal Model (DCM) that characterizes course patterns more fully using dense timeseries data. This foundational study introduces the new modeling approach and evaluates its validity using empirical and simulated data. Methods: A three-level DCM was constructed to model how latent dynamics produce symptoms of depression, mania, and psychosis. This model was fit to symptom scores of nine patients collected prospectively over four years, following first hospitalization. Simulated subjects based on these empirical data were used to evaluate model parameters at the subject-level. At the group-level, we tested the accuracy with which the DCM can estimate the latent course patterns using Parametric Empirical Bayes (PEB) and leave-one-out cross-validation. Results: Analyses of empirical data showed that DCM accurately captured symptom trajectories for all nine subjects. Simulation results showed that parameters could be estimated accurately (correlations between generative and estimated parameters >= 0.76). Moreover, the model could distinguish different latent course patterns, with PEB correctly assigning simulated patients for eight of nine course patterns. When testing any pair of two specific course patterns using leave-one-out cross-validation, 30 out of 36 pairs showed a moderate or high out-of-samples correlation between the true group-membership and the estimated group-membership values. Conclusion: DCM has been widely used in neuroscience to infer latent neuronal processes from neuroimaging data. Our findings highlight the potential of adopting this methodology for modeling symptom trajectories to explicate nosologic entities, temporal patterns that define them, and facilitate personalized treatment.

Nanoenzyme Reactor-Based Oxidation-Induced Reaction for Quantitative SERS Analysis of Food Antiseptics.

Nanoenzyme reactors based on shell-isolated colloidal plasmonic nanomaterials are well-established and widely applied in catalysis and surface-enhanced Raman scattering (SERS) sensing. In this study, a "double wing with one body" strategy was developed to establish a reduced food antiseptic sensing method using shell-isolated colloidal plasmonic nanomaterials. Gold nano particles (Au NPs) were used to synthesize the colloidal plasmonic nanomaterials, which was achieved by attaching ferrous ions (Fe2+), ferric ions (Fe3+), nitroso (NO-) group, cyanogen (CN-) group, and dopamine (DA) via coordinative interactions. The oxidation-induced reaction was utilized to generate •OH following the Fe2+-mediated Fenton reaction with the shell-isolated colloidal plasmonic nanomaterials. The •OH generated in the cascade reactor had a high oxidative capacity toward acid preservatives. Importantly, with the introduction of the signal molecule DA, the cascade reactor exhibited also induced a Raman signal change by reaction with the oxidation product (malondialdehyde) which improved the sensitivity of the analysis. In addition, the stable shell-isolated structure was effective in realizing a reproducible and quantitative SERS analysis method, which overcomes previous limitations and could extend the use of nanoenzymes to various complex sensing applications.

Structural Brain Correlates of Childhood Inhibited Temperament: An ENIGMA-Anxiety Mega-analysis.

Temperament involves stable behavioral and emotional tendencies that differ between individuals, which can be first observed in infancy or early childhood and relate to behavior in many contexts and over many years.1 One of the most rigorously characterized temperament classifications relates to the tendency of individuals to avoid the unfamiliar and to withdraw from unfamiliar people, objects, and unexpected events. This temperament is referred to as behavioral inhibition or inhibited temperament (IT).2 IT is a moderately heritable trait1 that can be measured in multiple species.3 In humans, levels of IT can be quantified from the first year of life through direct behavioral observations or reports by caregivers or teachers. Similar approaches as well as self-report questionnaires on current and/or retrospective levels of IT1 can be used later in life.