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Abstract Deficiencies in response inhibition are associated with numerous mental health conditions, warranting innovative treatments. Transcranial direct current stimulation (tDCS), a non-invasive brain stimulation technique, modulates cortical excitability and has shown promise in improving response inhibition. However, tDCS effects on response inhibition often yield contradictory findings. Previous research emphasized the importance of inter-individual factors that are mostly ignored in conventional meta-analyses of mean effects. We aimed to fill this gap and promote the complementary use of the coefficient of variation ratio and standardized mean effects. The systematic literature search included single-session and sham-controlled tDCS studies utilizing stop-signal task or Go-NoGo tasks, analyzing 88 effect sizes from 53 studies. Considering the impact of inter-individual factors, we hypothesized that variances increase in the active versus sham tDCS. However, the results showed that variances between both groups did not differ. Additionally, analyzing standardized mean effects supported previous research showing an improvement in the stop-signal task but not in the Go-NoGo task following active tDCS. These findings suggest that inter-individual differences do not increase variances in response inhibition, implying that the heterogeneity cannot be attributed to higher variance in response inhibition during and after active tDCS. Furthermore, methodological considerations are crucial for tDCS efficacy.

Abstract Background Minor physical anomalies (MPAs) are congenital morphological abnormalities linked to disruptions of fetal development. MPAs are common in 22q11.2 deletion syndrome (22q11DS) and psychosis spectrum disorders (PS) and likely represent a disruption of early embryologic development that may help identify overlapping mechanisms linked to psychosis in these disorders. Methods Here, 2D digital photographs were collected from 22q11DS (n = 150), PS (n = 55), and typically developing (TD; n = 93) individuals. Photographs were analyzed using two computer-vision techniques: (1) DeepGestalt algorithm (Face2Gene (F2G)) technology to identify the presence of genetically mediated facial disorders, and (2) Emotrics—a semi-automated machine learning technique that localizes and measures facial features. Results F2G reliably identified patients with 22q11DS; faces of PS patients were matched to several genetic conditions including FragileX and 22q11DS. PCA-derived factor loadings of all F2G scores indicated unique and overlapping facial patterns that were related to both 22q11DS and PS. Regional facial measurements of the eyes and nose were smaller in 22q11DS as compared to TD, while PS showed intermediate measurements. Conclusions The extent to which craniofacial dysmorphology 22q11DS and PS overlapping and evident before the impairment or distress of sub-psychotic symptoms may allow us to identify at-risk youths more reliably and at an earlier stage of development.

Abstract Human cortical maturation has been posited to be organized along the sensorimotor-association axis, a hierarchical axis of brain organization that spans from unimodal sensorimotor cortices to transmodal association cortices. Here, we investigate the hypothesis that the development of functional connectivity during childhood through adolescence conforms to the cortical hierarchy defined by the sensorimotor-association axis. We tested this pre-registered hypothesis in four large-scale, independent datasets (total n = 3355; ages 5–23 years): the Philadelphia Neurodevelopmental Cohort (n = 1207), Nathan Kline Institute-Rockland Sample (n = 397), Human Connectome Project: Development (n = 625), and Healthy Brain Network (n = 1126). Across datasets, the development of functional connectivity systematically varied along the sensorimotor-association axis. Connectivity in sensorimotor regions increased, whereas connectivity in association cortices declined, refining and reinforcing the cortical hierarchy. These consistent and generalizable results establish that the sensorimotor-association axis of cortical organization encodes the dominant pattern of functional connectivity development.

Abstract Schizophrenia is characterized by the misattribution of emotional significance to neutral faces, accompanied by overactivations of the limbic system. To understand the disorder’s genetic and environmental contributors, investigating healthy first-degree relatives is crucial. However, inconsistent findings exist regarding their ability to recognize neutral faces, with limited research exploring the cerebral correlates of neutral face processing in this population. Thus, we here investigated brain responses to neutral face processing in healthy first-degree relatives through an image-based meta-analysis of functional magnetic resonance imaging studies. We included unthresholded group-level T-maps from 5 studies comprising a total of 120 first-degree relatives and 150 healthy controls. In sensitivity analyses, we ran a combined image- and coordinate-based meta-analysis including 7 studies (157 first-degree relatives, 207 healthy controls) aiming at testing the robustness of the results in a larger sample of studies. Our findings revealed a pattern of decreased brain responses to neutral faces in relatives compared with healthy controls, particularly in limbic areas such as the bilateral amygdala, hippocampus, and insula. The same pattern was observed in sensitivity analyses. These results contrast with the overactivations observed in patients, potentially suggesting that this trait could serve as a protective factor in healthy relatives. However, further research is necessary to test this hypothesis.

Abstract Background Geographical variations in mood and psychotic disorders have been found in upper-income countries. We looked for geographic variation in these disorders in Colombia, a middle-income country. We analyzed electronic health records from the Clínica San Juan de Dios Manizales (CSJDM), which provides comprehensive mental healthcare for the one million inhabitants of Caldas. Methods We constructed a friction surface map of Caldas and used it to calculate the travel-time to the CSJDM for 16,295 patients who had received an initial diagnosis of mood or psychotic disorder. Using a zero-inflated negative binomial regression model, we determined the relationship between travel-time and incidence, stratified by disease severity. We employed spatial scan statistics to look for patient clusters. Results We show that travel-times (for driving) to the CSJDM are less than 1 h for ~50% of the population and more than 4 h for ~10%. We find a distance-decay relationship for outpatients, but not for inpatients: for every hour increase in travel-time, the number of expected outpatient cases decreases by 20% (RR = 0.80, 95% confidence interval [0.71, 0.89], p = 5.67E-05). We find nine clusters/hotspots of inpatients. Conclusions Our results reveal inequities in access to healthcare: many individuals requiring only outpatient treatment may live too far from the CSJDM to access healthcare. Targeting of resources to comprehensively identify severely ill individuals living in the observed hotspots could further address treatment inequities and enable investigations to determine factors generating these hotspots.

Abstract About 15–40% of patients with schizophrenia are treatment resistance (TR) and require clozapine. Identifying individuals who have higher risk of development of TR early in the course of illness is important to provide personalized intervention. A total of 1400 patients with FEP enrolled in the early intervention for psychosis service or receiving the standard psychiatric service between July 1, 1998, and June 30, 2003, for the first time were included. Clozapine prescriptions until June 2015, as a proxy of TR, were obtained. Premorbid information, baseline characteristics, and monthly clinical information were retrieved systematically from the electronic clinical management system (CMS). Training and testing samples were established with random subsampling. An automated machine learning (autoML) approach was used to optimize the ML algorithm and hyperparameters selection to establish four probabilistic classification models (baseline, 12-month, 24-month, and 36-month information) of TR development. This study found 191 FEP patients (13.7%) who had ever been prescribed clozapine over the follow-up periods. The ML pipelines identified with autoML had an area under the receiver operating characteristic curve ranging from 0.676 (baseline information) to 0.774 (36-month information) in predicting future TR. Features of baseline information, including schizophrenia diagnosis and age of onset, and longitudinal clinical information including symptoms variability, relapse, and use of antipsychotics and anticholinergic medications were important predictors and were included in the risk calculator. The risk calculator for future TR development in FEP patients (TRipCal) developed in this study could support the continuous development of data-driven clinical tools to assist personalized interventions to prevent or postpone TR development in the early course of illness and reduce delay in clozapine initiation.

Background: Adverse childhood experiences (ACEs) are associated with impaired cognitive function in adult life in the general population as well as in people living with schizophrenia (PLS). Research on cognitive function in PLS in low- and middle-income countries (LMIC) is, however, limited. The objectives of this study were to investigate the association between ACE types and various cognitive domains in a sample of PLS and matched medical controls, and to determine the moderating effect of group membership (PLS vs. medical controls) on these associations, in the South African setting. Methods: Participants (n PLS = 520; n medical controls = 832) completed the Childhood Trauma Questionnaire-Short Form, the Structured Clinical Interview for DSM-IV (SCID-I), and the University of Pennsylvania Computerized Neurocognitive Battery (PennCNB). An efficiency or speed score was used to assess performance across 9 cognitive domains. The association between exposure to different ACE types and 9 cognitive domains was examined using partial correlations and multiple linear regression models, adjusting for sex, age and education years. Finally, potential moderating effects of group membership (PLS vs. medical controls) on the association between ACEs and cognitive domains were tested. Results: In the entire sample, emotional and physical abuse predicted worse performance on sensorimotor and emotion identification domains. Also, emotional abuse was negatively associated with motor function, physical abuse was negatively associated with spatial processing, and physical neglect was negatively associated with face memory and emotion identification. In contrast, emotional neglect was related to better performance on abstraction and mental flexibility. No moderating effect of group membership was found on any of these associations. Conclusion: Exposure to ACEs was associated with social and non-social cognition in adulthood, although the magnitude of these relationships was small and similar between PLS and matched medical controls. The nature of these associations differed across ACE subtype, suggesting the need for a nuanced approach to studying a range of mechanisms that may underlie different associations. However, a number of ACE subtypes were associated with worse performance on emotional identification, indicating that some underlying mechanisms may have more transversal impact. These findings contribute to the sparse body of literature on ACEs and cognition in PLS in LMIC.

Summary: During adolescence, the brain undergoes extensive changes in white matter structure that support cognition. Data-driven approaches applied to cortical surface properties have led the field to understand brain development as a spatially and temporally coordinated mechanism that follows hierarchically organized gradients of change. Although white matter development also appears asynchronous, previous studies have relied largely on anatomical tract-based atlases, precluding a direct assessment of how white matter structure is spatially and temporally coordinated. Harnessing advances in diffusion modeling and machine learning, we identified 14 data-driven patterns of covarying white matter structure in a large sample of youth. Fiber covariance networks aligned with known major tracts, while also capturing distinct patterns of spatial covariance across distributed white matter locations. Most networks showed age-related increases in fiber network properties, which were also related to developmental changes in executive function. This study delineates data-driven patterns of white matter development that support cognition.

Background: Impairment in intrinsic motivation (IM), the drive to satisfy internal desires like mastery, may play a key role in disability in psychosis. However, we have limited knowledge regarding relative impairments in IM compared to extrinsic motivation (EM) or general motivation (GM), in part due to limitations in existing measures. Methods: Here we address this gap using a novel Trait Intrinsic and Extrinsic Motivation self-report scale in a sample of n = 243 participants including those with schizophrenia, psychosis-risk, and healthy controls. Each of the 7 IM and 6 EM items used a 7-point Likert scale assessing endorsement of dispositional statements. Bifactor analyses of these items yielded distinct IM, EM, and GM factor scores. Convergent and discriminant validity were examined in relation to General Causality Orientation Scale (GCOS-CP) and Quality of Life 3-item IM measure (QLS-IM). Utility was assessed in relation to psychosis-spectrum (PS) status and CAINS clinical amotivation. Results: IM and EM showed acceptable inter-item consistency (IM: α = 0.88; EM: α = 0.66); the bifactor model exhibited fit that varied from good to borderline to inadequate depending on the specific fit metric (SRMR = 0.038, CFI = 0.94, RMSEA = 0.106 ± 0.014). IM scores correlated with established IM measures: GCOS-CP Autonomy (rho = 0.38, p 0.05). Two-year stability in an available longitudinal subset (n = 35) was strong (IM: rho = 0.64, p

IntroductionEvidence suggests that executive function (EF) may play a key role in development of PTSD, possibly influenced by factors such as trauma type and timing. Since EF can be improved through intervention, it may be an important target for promoting resilience to trauma exposure. However, more research is needed to understand the relation between trauma exposure, EF, and PTSD. The goal of this study was to improve understanding of EF as a potential antecedent or protective factor for the development of PTSD among military personnel.MethodIn a cohort of U.S. Marines and Navy personnel (N = 1,373), the current study tested the association between exposure to traumatic events (pre-deployment and during deployment) and PTSD severity, and whether EF moderated these associations. Three types of pre-deployment trauma exposure were examined: cumulative exposure, which included total number of events participants endorsed as having happened to them, witnessed, or learned about; direct exposure, which included total number of events participants endorsed as having happened to them; and interpersonal exposure, which included total number of interpersonally traumatic events participants’ endorsed. EF was measured using the Penn Computerized Neurocognitive Battery.ResultsEF was associated with less PTSD symptom severity at pre-deployment, even when adjusting for trauma exposure, alcohol use, traumatic brain injury, and number of years in the military. EF also moderated the relation between cumulative trauma exposure and interpersonal trauma exposure and PTSD, with higher EF linked to a 20 and 33% reduction in expected point increase in PTSD symptoms with cumulative and interpersonal trauma exposure, respectively. Finally, higher pre-deployment EF was associated with reduced PTSD symptom severity at post-deployment, independent of deployment-related trauma exposure and adjusting for pre-deployment PTSD.ConclusionOur results suggest that EF plays a significant, if small role in the development of PTSD symptoms after trauma exposure among military personnel. These findings provide important considerations for future research and intervention and prevention, specifically, incorporating a focus on improving EF in PTSD treatment.

Delay discounting is a measure of impulsive choice relevant in adolescence as it predicts many real-life outcomes, including obesity and academic achievement. However, resting-state functional networks underlying individual differences in delay discounting during youth remain incompletely described. Here we investigate the association between multivariate patterns of functional connectivity and individual differences in impulsive choice in a large sample of children, adolescents, and adults. A total of 293 participants (9–23 years) completed a delay discounting task and underwent 3T resting-state fMRI. A connectome-wide analysis using multivariate distance-based matrix regression was used to examine whole-brain relationships between delay discounting and functional connectivity. These analyses revealed that individual differences in delay discounting were associated with patterns of connectivity emanating from the left dorsal prefrontal cortex, a default mode network hub. Greater delay discounting was associated with greater functional connectivity between the dorsal prefrontal cortex and other default mode network regions, but reduced connectivity with regions in the dorsal and ventral attention networks. These results suggest delay discounting in children, adolescents, and adults is associated with individual differences in relationships both within the default mode network and between the default mode and networks involved in attentional and cognitive control.

ABSTRACT: Diffusion MRI is the dominant non-invasive imaging method used to characterize white matter organization in health and disease. Increasingly, fiber-specific properties within a voxel are analyzed using fixels. While tools for conducting statistical analyses of fixel-wise data exist, currently available tools support only a limited number of statistical models. Here we introduce ModelArray, an R package for mass-univariate statistical analysis of fixel-wise data. At present, ModelArray supports linear models as well as generalized additive models (GAMs), which are particularly useful for studying nonlinear effects in lifespan data. In addition, ModelArray also aims for scalable analysis. With only several lines of code, even large fixel-wise datasets can be analyzed using a standard personal computer. Detailed memory profiling revealed that ModelArray required only limited memory even for large datasets. As an example, we applied ModelArray to fixel-wise data derived from diffusion images acquired as part of the Philadelphia Neurodevelopmental Cohort (n = 938). ModelArray revealed anticipated nonlinear developmental effects in white matter. Moving forward, ModelArray is supported by an open-source software development model that can incorporate additional statistical models and other imaging data types. Taken together, ModelArray provides a flexible and efficient platform for statistical analysis of fixel-wise data.

The amygdala contains androgen receptors and is involved in various affective and social functions. An interaction between testosterone and the amygdala’s functioning is likely. We investigated the amygdala’s resting-state functional connectivity (rsFC) network in association with testosterone in 94 healthy young adult women and men (final data available for analysis from 42 women and 39 men). Across the whole sample, testosterone was positively associated with the rsFC between the right amygdala and the right middle occipital gyrus, and it further predicted lower agreeableness scores. Significant sex differences appeared for testosterone and the functional connectivity between the right amygdala and the right superior frontal gyrus (SFG), showing higher testosterone levels with lower connectivity in women. Sex further predicted the openness and agreeableness scores. Our results show that testosterone modulates the rsFC between brain areas involved in affective processing and executive functions. The data indicate that the cognitive control of the amygdala via the frontal cortex is dependent on the testosterone levels in a sex-specific manner. Testosterone seems to express sex-specific patterns (1) in networks processing affect and cognition, and (2) in the frontal down-regulation of the amygdala. The sex-specific coupling between the amygdala and the frontal cortex in interaction with the hormone levels may drive sex-specific differences in a variety of behavioral phenomena that are further associated with psychiatric illnesses that show sex-specific prevalence rates.

Studies of brain network development typically focus on a single scale. Here, the authors derived personalized functional networks across scales, and find that network development systematically adheres to and strengthens hierarchical cortical organization.

Abstract The goal of this study was to compare brain structure between individuals with generalized anxiety disorder (GAD) and healthy controls. Previous studies have generated inconsistent findings, possibly due to small sample sizes, or clinical/analytic heterogeneity. To address these concerns, we combined data from 28 research sites worldwide through the ENIGMA-Anxiety Working Group, using a single, pre-registered mega-analysis. Structural magnetic resonance imaging data from children and adults (5–90 years) were processed using FreeSurfer. The main analysis included the regional and vertex-wise cortical thickness, cortical surface area, and subcortical volume as dependent variables, and GAD, age, age-squared, sex, and their interactions as independent variables. Nuisance variables included IQ, years of education, medication use, comorbidities, and global brain measures. The main analysis (1020 individuals with GAD and 2999 healthy controls) included random slopes per site and random intercepts per scanner. A secondary analysis (1112 individuals with GAD and 3282 healthy controls) included fixed slopes and random intercepts per scanner with the same variables. The main analysis showed no effect of GAD on brain structure, nor interactions involving GAD, age, or sex. The secondary analysis showed increased volume in the right ventral diencephalon in male individuals with GAD compared to male healthy controls, whereas female individuals with GAD did not differ from female healthy controls. This mega-analysis combining worldwide data showed that differences in brain structure related to GAD are small, possibly reflecting heterogeneity or those structural alterations are not a major component of its pathophysiology.

With the increasing availability of neuroimaging data from multiple modalities—each providing a different lens through which to study brain structure or function—new techniques for comparing, integrating, and interpreting information within and across modalities have emerged. Recent developments include hypothesis tests of associations between neuroimaging modalities, which can be used to determine the statistical significance of intermodal associations either throughout the entire brain or within anatomical subregions or functional networks. While these methods provide a crucial foundation for inference on intermodal relationships, they cannot be used to answer questions about where in the brain these associations are most pronounced. In this paper, we introduce a new method, called CLEAN-R, that can be used both to test intermodal correspondence throughout the brain and also to localize this correspondence. Our method involves first adjusting for the underlying spatial autocorrelation structure within each modality before aggregating information within small clusters to construct a map of enhanced test statistics. Using structural and functional magnetic resonance imaging data from a subsample of children and adolescents from the Philadelphia Neurodevelopmental Cohort, we conduct simulations and data analyses where we illustrate the high statistical power and nominal type I error levels of our method. By constructing an interpretable map of group-level correspondence using spatially-enhanced test statistics, our method offers insights beyond those provided by earlier methods.

The Brain Imaging Data Structure (BIDS) is a specification accompanied by a software ecosystem that was designed to create reproducible and automated workflows for processing neuroimaging data. BIDS Apps flexibly build workflows based on the metadata detected in a dataset. However, even BIDS valid metadata can include incorrect values or omissions that result in inconsistent processing across sessions. Additionally, in large-scale, heterogeneous neuroimaging datasets, hidden variability in metadata is difficult to detect and classify. To address these challenges, we created a Python-based software package titled “Curation of BIDS” (CuBIDS), which provides an intuitive workflow that helps users validate and manage the curation of their neuroimaging datasets. CuBIDS includes a robust implementation of BIDS validation that scales to large samples and incorporates DataLad––a version control software package for data––as an optional dependency to ensure reproducibility and provenance tracking throughout the entire curation process. CuBIDS provides tools to help users perform quality control on their images’ metadata and identify unique combinations of imaging parameters. Users can then execute BIDS Apps on a subset of participants that represent the full range of acquisition parameters that are present, accelerating pipeline testing on large datasets.

Dysregulated frontostriatal circuitries are viewed as a common target for the treatment of aberrant behaviors in various psychiatric and neurological disorders. Accordingly, experimental neurofeedback paradigms have been applied to modify the frontostriatal circuitry. The human frontostriatal circuitry is topographically and functionally organized into the “limbic,” the “associative,” and the “motor” subsystems underlying a variety of affective, cognitive, and motor functions. We conducted a systematic review of the literature regarding functional magnetic resonance imaging-based neurofeedback studies that targeted brain activations within the frontostriatal circuitry. Seventy-nine published studies were included in our survey. We assessed the efficacy of these studies in terms of imaging findings of neurofeedback intervention as well as behavioral and clinical outcomes. Furthermore, we evaluated whether the neurofeedback targets of the studies could be assigned to the identifiable frontostriatal subsystems. The majority of studies that targeted frontostriatal circuitry functions focused on the anterior cingulate cortex, the dorsolateral prefrontal cortex, and the supplementary motor area. Only a few studies (n = 14) targeted the connectivity of the frontostriatal regions. However, post-hoc analyses of connectivity changes were reported in more cases (n = 32). Neurofeedback has been frequently used to modify brain activations within the frontostriatal circuitry. Given the regulatory mechanisms within the closed loop of the frontostriatal circuitry, the connectivity-based neurofeedback paradigms should be primarily considered for modifications of this system. The anatomical and functional organization of the frontostriatal system needs to be considered in decisions pertaining to the neurofeedback targets.

Stress is an important factor in the development, triggering, and maintenance of psychotic symptoms. Still, little is known about the neural correlates of cognitively regulating stressful events in schizophrenia. The current study aimed at investigating the cognitive down-regulation of negative, stressful reactions during a neuroimaging psychosocial stress paradigm (non-regulated stress versus cognitively regulated stress). In a randomized, repeated-measures within-subject design, we assessed subjective reactions and neural activation in schizophrenia patients (SZP) and matched healthy controls in a neuroimaging psychosocial stress paradigm. In general, SZP exhibited an increased anticipation of stress compared to controls (p = 0.020). During non-regulated stress, SZP showed increased negative affect (p = 0.033) and stronger activation of the left parietal operculum/posterior insula (p < 0.001) and right inferior frontal gyrus/anterior insula (p = 0.005) than controls. Contrarily, stress regulation compared to non-regulated stress led to increased subjective reactions in controls (p = 0.003) but less deactivation in SZP in the ventral anterior cingulate cortex (p = 0.027). Our data demonstrate stronger reactions to and anticipation of stress in patients and difficulties with cognitive stress regulation in both groups. Considering the strong association between mental health and stress, the investigation of cognitive regulation in individuals vulnerable to stress, including SZP, has crucial implications for improving stress intervention trainings.

Abstract Psychopathology is rooted in neurodevelopment. However, clinical and biological heterogeneity, together with a focus on case-control approaches, have made it difficult to link dimensions of psychopathology to abnormalities of neurodevelopment. Here, using the Philadelphia Neurodevelopmental Cohort, we built normative models of cortical volume and tested whether deviations from these models better predicted psychiatric symptoms compared to raw cortical volume. Specifically, drawing on the p-factor hypothesis, we distilled 117 clinical symptom measures into six orthogonal psychopathology dimensions: overall psychopathology, anxious-misery, externalizing disorders, fear, positive psychosis symptoms, and negative psychosis symptoms. We found that multivariate patterns of deviations yielded improved out-of-sample prediction of psychopathology dimensions compared to multivariate patterns of raw cortical volume. We also found that correlations between overall psychopathology and deviations in ventromedial prefrontal, inferior temporal, and dorsal anterior cingulate cortices were stronger than those observed for specific dimensions of psychopathology (e.g., anxious-misery). Notably, these same regions are consistently implicated in a range of putatively distinct disorders. Finally, we performed conventional case-control comparisons of deviations in a group of individuals with depression and a group with attention-deficit hyperactivity disorder (ADHD). We observed spatially overlapping effects between these groups that diminished when controlling for overall psychopathology. Together, our results suggest that modeling cortical brain features as deviations from normative neurodevelopment improves prediction of psychiatric symptoms in out-of-sample testing, and that p-factor models of psychopathology may assist in separating biomarkers that are disorder-general from those that are disorder-specific.

BackgroundPrader Willi Syndrome (PWS) is a genetic disorder caused by the absence of expression of the paternal copies of maternally imprinted gene(s) located at 15q11–q13. While the physical and medical characteristics of PWS, including short stature, hyperphagia and endocrine dysfunction are well-characterized, systematic investigation of the long-recognized psychiatric manifestations has been recent.MethodsHere, we report on the first remote (web-based) assessment of neurobehavioral traits, including psychosis-risk symptoms (Prodromal Questionnaire-Brief Version; PQ-B) and sleep behaviors (Pittsburgh Sleep Quality Index), in a cohort of 128 participants with PWS, of whom 48% had a paternal deletion, 36% uniparental disomy, 2.4% an imprinting mutation and 13% unknown mutation (mean age 19.3 years ± 8.4; 53.9% female). We aimed to identify the most informative variables that contribute to psychosis-risk symptoms. Multiple domains of cognition (accuracy and speed) were also assessed in a subset of PWS participants (n = 39) using the Penn Computerized Neurocognitive Battery (Penn-CNB).ResultsIndividuals with PWS reported a range of psychosis-risk symptoms, with over half reporting cognitive disorganization (63.1%) and about one third reporting unusual beliefs (38.6%) and/or suspiciousness (33.3%). Subjectively-reported sleep quality, nap frequency, sleep duration, sleep disturbance, and daytime dysfunction were significant predictors of psychosis-risk symptom frequency and severity (all p's < 0.029). Sleep disturbance ratings were the strongest predictors of psychosis-risk symptoms. Regarding cognition, individuals with PWS showed the most prominent deficits in accuracy on measures of social cognition involving faces, namely Face Memory, Age Differentiation and Emotion Recognition, and greatest slowing on measures of Attention and Emotion Recognition. However, there were no significant differences in psychosis-risk symptoms or cognitive performance as a function of PWS genetic subtype.ConclusionsPWS is associated with a high prevalence of distressing psychosis-risk symptoms, which are associated with sleep disturbance. Findings indicate that self/parent-reported neurobehavioral symptoms and cognition can be assessed remotely in individuals with PWS, which has implications for future large-scale investigations of rare neurogenetic disorders.

Abstract Psychotic symptoms are not only an important feature of severe neuropsychiatric disorders, but are also common in the general population, especially in youth. The genetic etiology of psychosis symptoms in youth remains poorly understood. To characterize genetic risk for psychosis spectrum symptoms (PS), we leverage a community-based multiethnic sample of children and adolescents aged 8–22 years, the Philadelphia Neurodevelopmental Cohort (n = 7225, 20% PS). Using an elastic net regression model, we aim to classify PS status using polygenic scores (PGS) based on a range of heritable psychiatric and brain-related traits in a multi-PGS model. We also perform univariate PGS associations and evaluate age-specific effects. The multi-PGS analyses do not improve prediction of PS status over univariate models, but reveal that the attention deficit hyperactivity disorder (ADHD) PGS is robustly and uniquely associated with PS (OR 1.12 (1.05, 1.18) P = 0.0003). This association is driven by subjects of European ancestry (OR = 1.23 (1.14, 1.34), P = 4.15 × 10−7) but is not observed in African American subjects (P = 0.65). We find a significant interaction of ADHD PGS with age (P = 0.01), with a stronger association in younger children. The association is independent of phenotypic overlap between ADHD and PS, not indirectly driven by substance use or childhood trauma, and appears to be specific to PS rather than reflecting general psychopathology in youth. In an independent sample, we replicate an increased ADHD PGS in 328 youth at clinical high risk for psychosis, compared to 216 unaffected controls (OR 1.06, CI(1.01, 1.11), P = 0.02). Our findings suggest that PS in youth may reflect a different genetic etiology than psychotic symptoms in adulthood, one more akin to ADHD, and shed light on how genetic risk can be investigated across early disease trajectories.

Females and males differ in stress reactivity, coping, and the prevalence rates of stress-related disorders. According to a neurocognitive framework of stress coping, the functional connectivity between the amygdala and frontal regions (including the dorsolateral prefrontal cortex (dlPFC), ventral anterior cingulate cortex (vACC), and medial prefrontal cortex (mPFC)) plays a key role in how people deal with stress. In the current study, we investigated the effects of sex and stressor type in a within-subject counterbalanced design on the resting-state functional connectivity (rsFC) of the amygdala and these frontal regions in 77 healthy participants (40 females). Both stressor types led to changes in subjective ratings, with decreasing positive affect and increasing negative affect and anger. Females showed higher amygdala–vACC and amygdala–mPFC rsFC for social exclusion than for achievement stress, and compared to males. Whereas a higher amygdala–vACC rsFC indicates the activation of emotion processing and coping, a higher amygdala–mPFC rsFC indicates feelings of reward and social gain, highlighting the positive effects of social affiliation. Thus, for females, feeling socially affiliated might be more fundamental than for males. Our data indicate interactions of sex and stressor in amygdala–frontal coupling, which translationally contributes to a better understanding of the sex differences in prevalence rates and stress coping.

Abstract Intelligence quotient (IQ) testing is standard for evaluating cognitive abilities in genomic studies but requires professional expertise in administration and interpretation, and IQ scores do not translate into insights on implicated brain systems that can link genes to behavior. Individuals with 22q11.2 deletion syndrome (22q11.2DS) often undergo IQ testing to address special needs, but access to testing in resource‐limited settings is challenging. The brief Penn Computerized Neurocognitive Battery (CNB) provides measures of cognitive abilities related to brain systems and can screen for cognitive dysfunction. To examine the relation between CNB measures and IQ, we evaluated participants with the 22q11.2DS from Philadelphia and Tel Aviv (N = 117; 52 females; mean age 18.8) who performed both an IQ test and the CNB with a maximum of 5 years between administrations and a subsample (n = 24) who had both IQ and CNB assessments at two time points. We estimated domain‐level CNB scores using exploratory factor analysis (including bifactor for overall scores) and related those scores (intraclass correlations (ICCs)) to the IQ scores. We found that the overall CNB accuracy score showed similar correlations between time 1 and time 2 as IQ (0.775 for IQ and 0.721 for CNB accuracy), correlated well with the IQ scores (ICC = 0.565 and 0.593 for time 1 and time 2, respectively), and correlated similarly with adaptive functioning (0.165 and 0.172 for IQ and CNB, respectively). We provide a crosswalk (from linear equating) between standardized CNB and IQ scores. Results suggest that one can substitute the CNB for IQ testing in future genetic studies that aim to probe specific domains of brain‐behavior relations beyond IQ.

The Coronavirus Disease 2019 (COVID-19) pandemic brought unprecedented socially isolating measures to mitigate the spread of disease, heightening the importance of public outdoor urban greenspace. Here, we investigated the association between tree-rich greenspace and mental health in a large opportunity sample surveyed using a crowdsourcing research website (www.covid19resilience.org) between April 6th and October 12th, 2020 during the pandemic in the United States. Participants living in the U.S. (N = 2,089, 83.1% females, mean age 42 years, age range 18–90 years) were mapped to 1,080 unique ZIP Codes and mean tree canopy density was calculated with a 250 m buffer around each ZIP Code grouped by quartile as a proxy for nearby greenspace. Four mental health parameters were assessed: (1) COVID-19-related worries; (2) anxiety symptoms; (3) depression symptoms; and (4) a standardized and weighted composite mental health score of all three parameters. Multivariate regression analyses with multilevel models were used to study the association between nearby greenspace and the four mental health outcomes, controlling for participant demographics and ZIP Code urbanicity. In the entire cohort, increased nearby greenspace showed a significant protective effect for depression (Coef. = −0.27; p = 0.0499), and composite mental health scores (Coef. = −0.19; p = 0.038) when comparing ZIP Codes with the most greenspace to ZIP Codes with the least, with no observed effects on COVID-19 related worries or anxiety individually. Stratifying by age suggested protective trends of greenspace on mental health in older subsets of the population (top age quartile, over 51 years old) experiencing less depression (Coef. = −0.45; p = 0.048) and lower composite mental health scores (Coef. = −0.34; – = 0.032) as a function of nearby greenspace. Additionally, younger subsets of the population (second youngest age quartile, 31–38 years) experienced lower COVID-19 related worries (Coef. = −1.34; p = 0.022) as a function of greenspace. These findings may indicate that tree-rich greenspace plays a protective role on mental health during the COVID-19 pandemic, specifically in certain age groups, supporting the use of greenspace-related strategies to help mitigate mental health burden during this challenging and isolating time.

Environment (E) is pivotal in explaining variability in brain and behavior development, including suicidal ideation (SI) and behavior. It is therefore critical to systematically study relationships among environmental exposures (i.e., exposome) and suicidal phenotypes. Here, we evaluated the role of individual-level adversity and neighborhood environment and their interaction (E x E) in association with youth SI. Sample included youth (N = 7,054, ages 11–21) from the Philadelphia Neurodevelopmental Cohort, which investigated clinical phenotypes in a diverse US community population. We examined cross-sectional associations of environmental exposures with lifetime history of SI (n = 671), focusing on interactions between individual-level exposures to assaultive trauma (n = 917) and neighborhood-level socioeconomic status (SES) quantified using geocoded Census data. Models included potential confounds and overall psychopathology. Results showed that assaultive trauma was strongly associated with SI (OR = 3.3, 95%CI 2.7–4, p

Environmental and psychological stressors can adversely affect astronaut cognitive performance in space. This study used a 6° head-down tilt bed rest (HDBR) paradigm to simulate some of the physiologic changes induced by microgravity. Twenty-four participants (mean ± SD age 33.3 ± 9.2 years, N = 16 men) spent 60 consecutive days in strict HDBR. They were studied in three groups of eight subjects each. One group served as Control, whereas the other two groups received either a continuous or intermittent artificial gravity (AG) countermeasure of 30 min centrifugation daily (1 g acceleration at the center of mass and 2 g at the feet). Participants performed all 10 tests of NASA’s Cognition battery and a brief alertness and mood survey repeatedly before, during, and after the HDBR period. Test scores were adjusted for practice and stimulus set difficulty effects. A modest but statistically significant slowing across a range of cognitive domains was found in all three groups during HDBR compared to baseline, most consistently for sensorimotor speed, whereas accuracy was unaffected. These changes were observed early during HDBR and did not further worsen or improve with increasing time in HDBR, except for emotion recognition performance. With increasing time spent in HDBR, participants required longer time to decide which facial emotion was expressed. They were also more likely to select categories with negative valence over categories with neutral or positive valence. Except for workload, which was rated lower in the Control group, continuous or intermittent AG did not modify the effect of HDBR on cognitive performance or subjective responses. Participants expressed several negative survey responses during HDBR relative to baseline, and some of the responses further deteriorated during recovery, which highlights the importance of adequate medical and psychological support during extended duration HDBR studies. In conclusion, 60 days of HDBR were associated with moderate cognitive slowing and changes in emotion recognition performance, but these effects were not mitigated by either continuous or intermittent exposure to AG for 30 min daily.

AbstractBackgroundQuestions remain regarding whether genetic influences on early life psychopathology overlap with cognition and show developmental variation.MethodsUsing data from 9,421 individuals aged 8–21 from the Philadelphia Neurodevelopmental Cohort, factors of psychopathology were generated using a bifactor model of item-level data from a psychiatric interview. Five orthogonal factors were generated: anxious-misery (mood and anxiety), externalizing (attention deficit hyperactivity and conduct disorder), fear (phobias), psychosis-spectrum, and a general factor. Genetic analyses were conducted on a subsample of 4,662 individuals of European American ancestry. A genetic relatedness matrix was used to estimate heritability of these factors, and genetic correlations with executive function, episodic memory, complex reasoning, social cognition, motor speed, and general cognitive ability. Gene × Age analyses determined whether genetic influences on these factors show developmental variation.ResultsExternalizing was heritable (h2 = 0.46, p = 1 × 10−6), but not anxious-misery (h2 = 0.09, p = 0.183), fear (h2 = 0.04, p = 0.337), psychosis-spectrum (h2 = 0.00, p = 0.494), or general psychopathology (h2 = 0.21, p = 0.040). Externalizing showed genetic overlap with face memory (ρg = −0.412, p = 0.004), verbal reasoning (ρg = −0.485, p = 0.001), spatial reasoning (ρg = −0.426, p = 0.010), motor speed (ρg = 0.659, p = 1x10−4), verbal knowledge (ρg = −0.314, p = 0.002), and general cognitive ability (g)(ρg = −0.394, p = 0.002). Gene × Age analyses revealed decreasing genetic variance (γg = −0.146, p = 0.004) and increasing environmental variance (γe = 0.059, p = 0.009) on externalizing.ConclusionsCognitive impairment may be a useful endophenotype of externalizing psychopathology and, therefore, help elucidate its pathophysiological underpinnings. Decreasing genetic variance suggests that gene discovery efforts may be more fruitful in children than adolescents or young adults.

Virtual environments (VEs), in the recent years, have become more prevalent in neuroscience. These VEs can offer great flexibility, replicability, and control over the presented stimuli in an immersive setting. With recent developments, it has become feasible to achieve higher-quality visuals and VEs at a reasonable investment. Our aim in this project was to develop and implement a novel real-time functional magnetic resonance imaging (rt-fMRI)–based neurofeedback (NF) training paradigm, taking into account new technological advances that allow us to integrate complex stimuli into a visually updated and engaging VE. We built upon and developed a first-person shooter in which the dynamic change of the VE was the feedback variable in the brain–computer interface (BCI). We designed a study to assess the feasibility of the BCI in creating an immersive VE for NF training. In a randomized single-blinded fMRI-based NF-training session, 24 participants were randomly allocated into one of two groups: active and reduced contingency NF. All participants completed three runs of the shooter-game VE lasting 10 min each. Brain activity in a supplementary motor area region of interest regulated the possible movement speed of the player’s avatar and thus increased the reward probability. The gaming performance revealed that the participants were able to actively engage in game tasks and improve across sessions. All 24 participants reported being able to successfully employ NF strategies during the training while performing in-game tasks with significantly higher perceived NF control ratings in the NF group. Spectral analysis showed significant differential effects on brain activity between the groups. Connectivity analysis revealed significant differences, showing a lowered connectivity in the NF group compared to the reduced contingency-NF group. The self-assessment manikin ratings showed an increase in arousal in both groups but failed significance. Arousal has been linked to presence, or feelings of immersion, supporting the VE’s objective. Long paradigms, such as NF in MRI settings, can lead to mental fatigue; therefore, VEs can help overcome such limitations. The rewarding achievements from gaming targets can lead to implicit learning of self-regulation and may broaden the scope of NF applications.

Objective: The limbic system is involved in memory and in processing of emotional stimuli. We measured volume of the hippocampus, amygdala, and thalamus, and assessed their relative contribution to episodic memory and emotion identification in POMS. Method: Sixty-five POMS participants (Mage = 18.3 ± 3.9 years; 48 female (73.8%)), average disease duration = 3.8 ± 3.8 years) and 76 age- and sex-matched controls (Mage = 18.1 ± 4.6 years; 49 female (64.5%)) completed the Penn Computerized Neurocognitive Battery (PCNB); 59 of 65 POMS participants and 69 out of 76 controls underwent 3 T MRI scanning. We derived age-adjusted Z-scores on accuracy and response time (RT) measures of episodic memory and emotion identification of the PCNB. Magnetic resonance imaging (MRI) volumetrics were normalized using the scaling factor computed by SIENAx. On PCNB tests that differed between groups, we used multiple linear regression to assess relationships between regional brain volumes and either episodic memory or emotion identification outcomes controlling for age, sex, accuracy/RT, and parental education. Results: POMS participants were slower and less accurate than controls on the episodic memory domain but did not differ from controls on emotion outcomes. At the subtest level, POMS participants showed reduced accuracy on Word Memory (p = .002) and slower performance on Face Memory (p = .04) subtests. POMS participants had smaller total and regional brain volumes of the hippocampus, amygdala, and thalamus (p values ≤ 0.01). Collapsing across groups, both hippocampal and thalamic volume were significant predictors of Word Memory accuracy; hippocampal volume (B = 0.24, SE = 0.10, p = .02) was more strongly associated with Word Memory performance than thalamic volume (B = 0.16, SE = 0.05, p = .003), though the estimate with was less precise. Conclusions: POMS participants showed reduced episodic memory performance compared to controls. Aspects of episodic memory performance were associated with hippocampal and thalamic volume. Emotion identification was intact, despite volume loss in the amygdala.

Maintaining optimal cognitive performance in astronauts during spaceflight is critical to crewmember safety and mission success. To investigate the combined effects of confinement, isolation, and sleep deprivation on cognitive performance during spaceflight, we administered the computerized neurobehavioral test battery “Cognition” to crew members of simulated spaceflight missions as part of NASA’s ground-based Human Exploration Research Analog project. Cognition was administered to N = 32 astronaut-like subjects in four 1-week missions (campaign 1) and four 2 weeks missions (campaign 2), with four crewmembers per mission. In both campaigns, subjects performed significantly faster on Cognition tasks across time in mission without sacrificing accuracy, which is indicative of a learning effect. On an alertness and affect survey, subjects self-reported significant improvement in several affective domains with time in mission. During the sleep restriction challenge, subjects in campaign 1 were significantly less accurate on a facial emotion identification task during a night of partial sleep restriction. Subjects in campaign 2 were significantly slower and less accurate on psychomotor vigilance, and slower on cognitive throughput and motor praxis tasks during a night of total sleep deprivation. On the survey, subjects reported significantly worsening mood during the sleep loss challenge on several affective domains. These findings suggest that confinement and relative isolation of up to 2 weeks in this environment do not induce a significant negative impact on cognitive performance in any of the domains examined by Cognition, although the concurrent practice effect may have masked some of the mission’s effects. Conversely, a night of total sleep deprivation significantly decreased psychomotor vigilance and cognitive throughput performance in astronaut-like subjects. This underscores the importance of using cognitive tests designed specifically for the astronaut population, and that survey a range of cognitive domains to detect the differential effects of the wide range of stressors common to the spaceflight environment.

Disparate diagnostic categories from the Diagnostic and Statistical Manual of Mental Disorders (DSM), including generalized anxiety disorder, major depressive disorder and post-traumatic stress disorder, share common behavioral and phenomenological dysfunctions. While high levels of comorbidity and common features across these disorders suggest shared mechanisms, past research in psychopathology has largely proceeded based on the syndromal taxonomy established by the DSM rather than on a biologically-informed framework of neural, cognitive and behavioral dysfunctions. In line with the National Institute of Mental Health’s Research Domain Criteria (RDoC) framework, we present a Human Connectome Study Related to Human Disease that is intentionally designed to generate and test novel, biologically-motivated dimensions of psychopathology. The Dimensional Connectomics of Anxious Misery study is collecting neuroimaging, cognitive and behavioral data from a heterogeneous population of adults with varying degrees of depression, anxiety and trauma, as well as a set of healthy comparators (to date, n = 97 and n = 24, respectively). This sample constitutes a dataset uniquely situated to elucidate relationships between brain circuitry and dysfunctions of the Negative Valence construct of the RDoC framework. We present a comprehensive overview of the eligibility criteria, clinical procedures and neuroimaging methods of our project. After describing our protocol, we present group-level activation maps from task fMRI data and independent components maps from resting state data. Finally, using quantitative measures of neuroimaging data quality, we demonstrate excellent data quality relative to a subset of the Human Connectome Project of Young Adults (n = 97), as well as comparable profiles of cortical thickness from T1-weighted imaging and generalized fractional anisotropy from diffusion weighted imaging. This manuscript presents results from the first 121 participants of our full target 250 participant dataset, timed with the release of this data to the National Institute of Mental Health Data Archive in fall 2020, with the remaining half of the dataset to be released in 2021.

Alterations in resting-state functional connectivity (rsFC) have been demonstrated in Posttraumatic Stress Disorder (PTSD). However, such reports have primarily focused on adult participants, whereas findings in adolescents with PTSD are mixed and not entirely consistent with the adult literature. Here, we examined rsFC in a non-treatment seeking adolescent sample with posttraumatic stress symptoms (PTSS; n = 59) relative to asymptomatic controls (n = 226). We also examined differences between trauma-exposed and non-exposed control subgroups (TEC n = 73 and Non-TEC n = 153) to examine alterations associated with more general trauma exposure. Finally, we compared the PTSS and TEC groups, to confirm that the reported alterations in PTSS were not driven by trauma exposure. Using a seed-based approach, we examined connectivity of default-mode (DMN) and salience (SN) networks, where alterations have been previously reported. Results suggest that PTSS are associated with less within-DMN connectivity and greater SN-DMN connectivity, as well as altered connectivity with attention regions. Trauma exposure is associated with greater within-SN connectivity. Additionally, we report findings from exploratory connectome-based analysis, which demonstrate a number of topological alterations within DMN in the PTSS group. Overall, our findings replicate prior reports of altered rsFC in PTSD and extend them to non-treatment seeking, trauma-exposed adolescents, who did or did not report PTSS. They specifically highlight SN-DMN desegregation, lower within-DMN and greater within-SN connectivity, as well as altered connectivity with attention regions, in trauma-exposed adolescents. Future research is required to confirm that adolescents with diagnosed PTSD have similar/exacerbated connectivity patterns.

Co-morbidity and symptom overlap make it difficult to associate psychiatric disorders with unique neural signatures. Here, the authors use a data-driven approach to show that the symptom dimensions of mood, psychosis, fear and externalizing behavior exhibit unique patterns of functional dysconnectivity.

Abstract Positive self-evaluation is a major psychological resource modulating stress coping behavior. Sex differences have been reported in self-esteem as well as stress reactions, but so far their interactions have not been investigated. Therefore, we investigated sex-specific associations of self-esteem and stress reaction on behavioral, hormonal and neural levels. We applied a commonly used fMRI-stress task in 80 healthy participants. Men compared to women showed higher activation during stress in hippocampus, precuneus, superior temporal gyrus (STG) and insula. Furthermore, men outperformed women in the stress task and had higher cortisol and testosterone levels than women after stress. Self-esteem had an impact on precuneus, insula and STG activation during stress across the whole group. During stress, men recruit regions associated with emotion and stress regulation, self-referential processing and cognitive control more strongly than women. Self-esteem affects stress processing, however in a sex-independent fashion: participants with lower self-esteem show higher activation of regions involved in emotion and stress regulation, self-referential processing and cognitive control. Taken together, our data suggest that men are more engaged during the applied stress task. Across women and men, lower self-esteem increases the effort in emotion and stress processing and cognitive control, possibly leading to self-related thoughts in stressful situations.

Human brain development is characterized by an increased control of neural activity, but how this happens is not well understood. Here, authors show that white matter connectivity in 882 youth, aged 8-22, becomes increasingly specialized locally and is optimized for network control.

Cognitive function evolves significantly over development, enabling flexible control of human behavior. Yet, how these functions are instantiated in spatially distributed and dynamically interacting networks, or graphs, that change in structure from childhood to adolescence is far from understood. Here we applied a novel machine-learning method to track continuously overlapping and time-varying subgraphs in the brain at rest within a sample of 200 healthy youth (ages 8–11 and 19–22) drawn from the Philadelphia Neurodevelopmental Cohort. We uncovered a set of subgraphs that capture surprisingly integrated and dynamically changing interactions among known cognitive systems. We observed that subgraphs that were highly expressed were especially transient, flexibly switching between high and low expression over time. This transience was particularly salient in a subgraph predominantly linking frontoparietal regions of the executive system, which increases in both expression and flexibility from childhood to young adulthood. Collectively, these results suggest that healthy development is accompanied by an increasing precedence of executive networks and a greater switching of the regions and interactions subserving these networks.

The 22q11.2 deletion syndrome (22q11DS) is an uncommon genetic disorder with an increased risk of psychosis. Although the neural substrates of psychosis and schizophrenia are not well understood, aberrations in cortical networks represent intriguing potential mechanisms. Investigations of anatomic networks within 22q11DS are sparse. We investigated group differences in anatomic network structure in 48 individuals with 22q11DS and 370 typically developing controls by analyzing covariance patterns in cortical thickness among 68 regions of interest using graph theoretical models. Subjects with 22q11DS had less robust geographic organization relative to the control group, particularly in the occipital and parietal lobes. Multiple global graph theoretical statistics were decreased in 22q11DS. These results are consistent with prior studies demonstrating decreased connectivity in 22q11DS using other neuroimaging methodologies.

Altered facial expressions of emotions are characteristic impairments in schizophrenia. Ratings of affect have traditionally been limited to clinical rating scales and facial muscle movement analysis, which require extensive training and have limitations based on methodology and ecological validity. To improve reliable assessment of dynamic facial expression changes, we have developed automated measurements of facial emotion expressions based on information-theoretic measures of expressivity of ambiguity and distinctiveness of facial expressions. These measures were examined in matched groups of persons with schizophrenia (n=28) and healthy controls (n=26) who underwent video acquisition to assess expressivity of basic emotions (happiness, sadness, anger, fear, and disgust) in evoked conditions. Persons with schizophrenia scored higher on ambiguity, the measure of conditional entropy within the expression of a single emotion, and they scored lower on distinctiveness, the measure of mutual information across expressions of different emotions. The automated measures compared favorably with observer-based ratings. This method can be applied for delineating dynamic emotional expressivity in healthy and clinical populations.