Validation of the structured interview section of the penn computerized adaptive test for neurocognitive and clinical psychopathology assessment (CAT GOASSESS)

Large-scale studies and burdened clinical settings require precise, efficient measures that assess multiple domains of psychopathology. Computerized adaptive tests (CATs) can reduce administration time without compromising data quality. We examined feasibility and validity of an adaptive psychopathology measure, GOASSESS, in a clinical community-based sample (N = 315; ages 18-35) comprising three groups: healthy controls, psychosis, mood/anxiety disorders. Assessment duration was compared between the Full and CAT GOASSESS. External validity was tested by comparing how the CAT and Full versions related to demographic variables, study group, and socioeconomic status. The relationships between scale scores and criteria were statistically compared within a mixed-model framework to account for dependency between relationships. Convergent validity was assessed by comparing scores of the CAT and the Full GOASSESS using Pearson correlations. The CAT GOASSESS reduced interview duration by more than 90 % across study groups and preserved relationships to external criteria and demographic variables as the Full GOASSESS. All CAT GOASSESS scales could replace those of the Full instrument. Overall, the CAT GOASSESS showed acceptable psychometric properties and demonstrated feasibility by markedly reducing assessment time compared to the Full GOASSESS. The adaptive version could be used in large-scale studies or clinical settings for intake screening.

Accelerating Medicines Partnership® Schizophrenia (AMP® SCZ): Rationale and Study Design of the Largest Global Prospective Cohort Study of Clinical High Risk for Psychosis

This article describes the rationale, aims, and methodology of the Accelerating Medicines Partnership® Schizophrenia (AMP® SCZ). This is the largest international collaboration to date that will develop algorithms to predict trajectories and outcomes of individuals at clinical high risk (CHR) for psychosis and to advance the development and use of novel pharmacological interventions for CHR individuals. We present a description of the participating research networks and the data processing analysis and coordination center, their processes for data harmonization across 43 sites from 13 participating countries (recruitment across North America, Australia, Europe, Asia, and South America), data flow and quality assessment processes, data analyses, and the transfer of data to the National Institute of Mental Health (NIMH) Data Archive (NDA) for use by the research community. In an expected sample of approximately 2000 CHR individuals and 640 matched healthy controls, AMP SCZ will collect clinical, environmental, and cognitive data along with multimodal biomarkers, including neuroimaging, electrophysiology, fluid biospecimens, speech and facial expression samples, novel measures derived from digital health technologies including smartphone-based daily surveys, and passive sensing as well as actigraphy. The study will investigate a range of clinical outcomes over a 2-year period, including transition to psychosis, remission or persistence of CHR status, attenuated positive symptoms, persistent negative symptoms, mood and anxiety symptoms, and psychosocial functioning. The global reach of AMP SCZ and its harmonized innovative methods promise to catalyze the development of new treatments to address critical unmet clinical and public health needs in CHR individuals.

Remote assessment of the Penn computerised neurocognitive battery in individuals with 22q11.2 deletion syndrome

BACKGROUND

Neurocognitive functioning is an integral phenotype of 22q11.2 deletion syndrome relating to severity of psychopathology and outcomes. A neurocognitive battery that could be administered remotely to assess multiple cognitive domains would be especially beneficial to research on rare genetic variants, where in-person assessment can be unavailable or burdensome. The current study compares in-person and remote assessments of the Penn computerised neurocognitive battery (CNB).

METHODS

Participants (mean age = 17.82, SD = 6.94 years; 48% female) completed the CNB either in-person at a laboratory (n = 222) or remotely (n = 162).

RESULTS

Results show that accuracy of CNB performance was equivalent across the two testing locations, while slight differences in speed were detected in 3 of the 11 tasks.

CONCLUSIONS

These findings suggest that the CNB can be used in remote settings to assess multiple neurocognitive domains.

Validation of the cognitive section of the Penn computerized adaptive test for neurocognitive and clinical psychopathology assessment (CAT-CCNB)

BACKGROUND

The Penn Computerized Neurocognitive Battery is an efficient tool for assessing brain-behavior domains, and its efficiency was augmented via computerized adaptive testing (CAT). This battery requires validation in a separate sample to establish psychometric properties.

METHODS

In a mixed community/clinical sample of N = 307 18-to-35-year-olds, we tested the relationships of the CAT tests with the full-form tests. We compared discriminability among recruitment groups (psychosis, mood, control) and examined how their scores relate to demographics. CAT-Full relationships were evaluated based on a minimum inter-test correlation of 0.70 or an inter-test correlation within at least 0.10 of the full-form correlation with a previous administration of the full battery. Differences in criterion relationships were tested via mixed models.

RESULTS

Most tests (15/17) met the minimum criteria for replacing the full-form with the updated CAT version (mean r = 0.67; range = 0.53-0.80) when compared to relationships of the full-forms with previous administrations of the full-forms (mean r = 0.68; range = 0.50-0.85). Most (16/17) CAT-based relationships with diagnostics and other validity criteria were indistinguishable (interaction p > 0.05) from their full-form counterparts.

CONCLUSIONS

The updated CNB shows psychometric properties acceptable for research. The full-forms of some tests should be retained due to insufficient time savings to justify the loss in precision.

Source-based morphometry reveals structural brain pattern abnormalities in 22q11.2 deletion syndrome

22q11.2 deletion syndrome (22q11DS) is the most frequently occurring microdeletion in humans. It is associated with a significant impact on brain structure, including prominent reductions in gray matter volume (GMV), and neuropsychiatric manifestations, including cognitive impairment and psychosis. It is unclear whether GMV alterations in 22q11DS occur according to distinct structural patterns. Then, 783 participants (470 with 22q11DS: 51% females, mean age [SD] 18.2 [9.2]; and 313 typically developing [TD] controls: 46% females, mean age 18.0 [8.6]) from 13 datasets were included in the present study. We segmented structural T1-weighted brain MRI scans and extracted GMV images, which were then utilized in a novel source-based morphometry (SBM) pipeline (SS-Detect) to generate structural brain patterns (SBPs) that capture co-varying GMV. We investigated the impact of the 22q11.2 deletion, deletion size, intelligence quotient, and psychosis on the SBPs. Seventeen GMV-SBPs were derived, which provided spatial patterns of GMV covariance associated with a quantitative metric (i.e., loading score) for analysis. Patterns of topographically widespread differences in GMV covariance, including the cerebellum, discriminated individuals with 22q11DS from healthy controls. The spatial extents of the SBPs that revealed disparities between individuals with 22q11DS and controls were consistent with the findings of the univariate voxel-based morphometry analysis. Larger deletion size was associated with significantly lower GMV in frontal and occipital SBPs; however, history of psychosis did not show a strong relationship with these covariance patterns. 22q11DS is associated with distinct structural abnormalities captured by topographical GMV covariance patterns that include the cerebellum. Findings indicate that structural anomalies in 22q11DS manifest in a nonrandom manner and in distinct covarying anatomical patterns, rather than a diffuse global process. These SBP abnormalities converge with previously reported cortical surface area abnormalities, suggesting disturbances of early neurodevelopment as the most likely underlying mechanism.

Neurocognitive Profiles of 22q11.2 and 16p11.2 Deletions and Duplications

Rare recurrent copy number variants (CNVs) at chromosomal loci 22q11.2 and 16p11.2 are among the most common rare genetic disorders associated with significant risk for neuropsychiatric disorders across the lifespan. Microdeletions and duplications in these loci are associated with neurocognitive deficits, yet there are few studies comparing these groups using the same measures. We address this gap in a prospective international collaboration applying the same computerized neurocognitive assessment. The Penn Computerized Neurocognitive Battery (CNB) was administered in a multi-site study on rare genomic disorders: 22q11.2 deletion (n = 397); 22q11.2 duplication (n = 77); 16p11.2 deletion (n = 94); and 16p11.2 duplication (n = 26). Domains examined include executive functions, episodic memory, complex cognition, social cognition, and sensori-motor speed. Accuracy and speed for each neurocognitive domain were included as dependent measures in a mixed-model repeated measures analysis, with locus (22q11.2, 16p11.2) and copy number (deletion/duplication) as grouping factors and neurocognitive domain as a repeated measures factor, with age and sex as covariates. We also examined correlation with IQ and site effects. We found that 22q11.2 deletions were associated with greater deficits in overall performance accuracy than 22q11.2 duplications, while 16p11.2 duplications were associated with greater deficits than 16p11.2 deletions. Duplications at both loci were associated with reduced speed. Performance profiles differed among the groups with particularly poor performance of 16p11.2 duplication on non-verbal reasoning and social cognition. Average accuracy on the CNB was moderately correlated with Full Scale IQ. No site effects were observed. Deletions and duplications of 22q11.2 and 16p11.2 have varied effects on neurocognition indicating locus specificity, with performance profiles differing among the groups. These profile differences can help inform mechanistic substrates to heterogeneity in presentation and outcome. Future studies could aim to link performance profiles to clinical features and brain function.

Development and application of novel performance validity metrics for computerized neurocognitive batteries

OBJECTIVES

Data from neurocognitive assessments may not be accurate in the context of factors impacting validity, such as disengagement, unmotivated responding, or intentional underperformance. Performance validity tests (PVTs) were developed to address these phenomena and assess underperformance on neurocognitive tests. However, PVTs can be burdensome, rely on cutoff scores that reduce information, do not examine potential variations in task engagement across a battery, and are typically not well-suited to acquisition of large cognitive datasets. Here we describe the development of novel performance validity measures that could address some of these limitations by leveraging psychometric concepts using data embedded within the Penn Computerized Neurocognitive Battery (PennCNB).

METHODS

We first developed these validity measures using simulations of invalid response patterns with parameters drawn from real data. Next, we examined their application in two large, independent samples: 1) children and adolescents from the Philadelphia Neurodevelopmental Cohort (n = 9498); and 2) adult servicemembers from the Marine Resiliency Study-II (n = 1444).

RESULTS

Our performance validity metrics detected patterns of invalid responding in simulated data, even at subtle levels. Furthermore, a combination of these metrics significantly predicted previously established validity rules for these tests in both developmental and adult datasets. Moreover, most clinical diagnostic groups did not show reduced validity estimates.

CONCLUSIONS

These results provide proof-of-concept evidence for multivariate, data-driven performance validity metrics. These metrics offer a novel method for determining the performance validity for individual neurocognitive tests that is scalable, applicable across different tests, less burdensome, and dimensional. However, more research is needed into their application.

Development of Iron Status Measures during Youth: Associations with Sex, Neighborhood Socioeconomic Status, Cognitive Performance, and Brain Structure

BACKGROUND

Iron is essential to brain function, and iron deficiency during youth may adversely impact neurodevelopment. Understanding the developmental time course of iron status and its association with neurocognitive functioning is important for identifying windows for intervention.

OBJECTIVES

This study aimed to characterize developmental change in iron status and understand its association with cognitive performance and brain structure during adolescence using data from a large pediatric health network.

METHODS

This study included a cross-sectional sample of 4899 participants (2178 males; aged 8-22 y at the time of participation, M [SD] = 14.24 [3.7]) who were recruited from the Children's Hospital of Philadelphia network. Prospectively collected research data were enriched with electronic medical record data that included hematological measures related to iron status, including serum hemoglobin, ferritin, and transferrin (33,015 total samples). At the time of participation, cognitive performance was assessed using the Penn Computerized Neurocognitive Battery, and brain white matter integrity was assessed using diffusion-weighted MRI in a subset of individuals.

RESULTS

Developmental trajectories were characterized for all metrics and revealed that sex differences emerged after menarche such that females had reduced iron status relative to males [all R2partial > 0.008; all false discovery rates (FDRs) < 0.05]. Higher socioeconomic status was associated with higher hemoglobin concentrations throughout development (R2partial = 0.005; FDR < 0.001), and the association was greatest during adolescence. Higher hemoglobin concentrations were associated with better cognitive performance during adolescence (R2partial = 0.02; FDR < 0.001) and mediated the association between sex and cognition (mediation effect = -0.107; 95% CI: -0.191, -0.02). Higher hemoglobin concentration was also associated with greater brain white matter integrity in the neuroimaging subsample (R2partial = 0.06, FDR = 0.028).

CONCLUSIONS

Iron status evolves during youth and is lowest in females and individuals of low socioeconomic status during adolescence. Diminished iron status during adolescence has consequences for neurocognition, suggesting that this critical period of neurodevelopment may be an important window for intervention that has the potential to reduce health disparities in at-risk populations.

Activation of Internal Correctness Monitoring Circuitry in Youths With Psychosis Spectrum Symptoms

BACKGROUND

Self-directed performance monitoring is a critical contributor to cognitive performance and general functioning and is impacted by psychiatric symptoms and personality traits, but has been understudied in psychosis-risk states. We have shown that ventral striatum (VS) responds to correctness during cognitive tasks where no explicit feedback is required, and this intrinsic reinforcement response is reduced in schizophrenia.

METHODS

Here, we examined this phenomenon in youths (n = 796, age range 11-22 years) from the Philadelphia Neurodevelopmental Cohort (PNC) performing a working memory functional magnetic resonance imaging task. We hypothesized that VS would respond to internal correctness monitoring, while classic salience network regions, such as dorsal anterior cingulate cortex and anterior insular cortex, would reflect internal error monitoring and that these responses would increase with age. We expected that neurobehavioral measures of performance monitoring would be reduced in youths with subclinical psychosis spectrum features and would correlate with amotivation severity.

RESULTS

Supporting these hypotheses, we found correct>incorrect activation in VS and incorrect>correct activation in anterior cingulate cortex and anterior insular cortex. Furthermore, VS activation was positively correlated with age, reduced in youths with psychosis spectrum features, and inversely correlated with amotivation. However, these patterns were not significant in anterior cingulate cortex and anterior insular cortex.

CONCLUSIONS

These findings advance our understanding of the neural underpinnings of performance monitoring and its impairment in adolescents with psychosis spectrum features. Such understanding can facilitate investigation of the developmental trajectory of normative and aberrant performance monitoring; contribute to early identification of youths at elevated risk for poor academic, occupational, or psychiatric outcomes; and provide potential targets for therapeutic development.

Psychosis spectrum features, neurocognition and functioning in a longitudinal study of youth with 22q11.2 deletion syndrome

BACKGROUND

Neuropsychiatric disorders are common in 22q11.2 Deletion Syndrome (22q11DS) with about 25% of affected individuals developing schizophrenia spectrum disorders by young adulthood. Longitudinal evaluation of psychosis spectrum features and neurocognition can establish developmental trajectories and impact on functional outcome.

METHODS

157 youth with 22q11DS were assessed longitudinally for psychopathology focusing on psychosis spectrum symptoms, neurocognitive performance and global functioning. We contrasted the pattern of positive and negative psychosis spectrum symptoms and neurocognitive performance differentiating those with more prominent Psychosis Spectrum symptoms (PS+) to those without prominent psychosis symptoms (PS-).

RESULTS

We identified differences in the trajectories of psychosis symptoms and neurocognitive performance between the groups. The PS+ group showed age associated increase in symptom severity, especially negative symptoms and general nonspecific symptoms. Correspondingly, their level of functioning was worse and deteriorated more steeply than the PS- group. Neurocognitive performance was generally comparable in PS+ and PS- groups and demonstrated a similar age-related trajectory. However, worsening executive functioning distinguished the PS+ group from PS- counterparts. Notably, of the three executive function measures examined, only working memory showed a significant difference between the groups in rate of change. Finally, structural equation modeling showed that neurocognitive decline drove the clinical change.

CONCLUSIONS

Youth with 22q11DS and more prominent psychosis features show worsening of symptoms and functional decline driven by neurocognitive decline, most related to executive functions and specifically working memory. The results underscore the importance of working memory in the developmental progression of psychosis.

Construction of a computerized adaptive test (CAT-CCNB) for efficient neurocognitive and clinical psychopathology assessment

BACKGROUND

Traditional paper-and-pencil neurocognitive evaluations and semi-structured mental health interviews can take hours to administer and score. Computerized assessment has decreased that burden substantially, and contemporary psychometric tools such as item response theory and computerized adaptive testing (CAT) allow even further abbreviation.

NEW METHOD

The goal of this paper was to describe the application of CAT and related methods to the Penn Computerized Neurocognitive Battery (CNB) and a well-validated clinical assessment in order to increase efficiency in assessment and relevant domain coverage. To calibrate item banks for CAT, N = 5053 participants (63% female; mean age 45 years, range 18-80) were collected from across the United States via crowdsourcing, providing item parameters that were then linked to larger item banks and used in individual test construction. Tests not amenable to CAT were abbreviated using complementary short-form methods.

RESULTS

The final "CAT-CCNB" battery comprised 21 cognitive tests (compared to 14 in the original) and five adaptive clinical scales (compared to 16 in the original).

COMPARISON WITH EXISTING METHODS

This new battery, derived with contemporary psychometric approaches, provides further improvements over existing assessments that use collections of fixed-length tests developed for stand-alone administration. The CAT-CCNB provides an improved version of the CNB that shows promise as a maximally efficient tool for neuropsychiatric assessment.

CONCLUSIONS

We anticipate CAT-CCNB will help satisfy the clear need for broad yet efficient measurement of cognitive and clinical domains, facilitating implementation of large-scale, "big science" approaches to data collection, and potential widespread clinical implementation.

A Comprehensive Analysis of Cerebellar Volumes in the 22q11.2 Deletion Syndrome

BACKGROUND

The presence of a 22q11.2 microdeletion (22q11.2 deletion syndrome [22q11DS]) ranks among the greatest known genetic risk factors for the development of psychotic disorders. There is emerging evidence that the cerebellum is important in the pathophysiology of psychosis. However, there is currently limited information on cerebellar neuroanatomy in 22q11DS specifically.

METHODS

High-resolution 3T magnetic resonance imaging was acquired in 79 individuals with 22q11DS and 70 typically developing control subjects (N = 149). Lobar and lobule-level cerebellar volumes were estimated using validated automated segmentation algorithms, and subsequently group differences were compared. Hierarchical clustering, principal component analysis, and graph theoretical models were used to explore intercerebellar relationships. Cerebrocerebellar structural connectivity with cortical thickness was examined via linear regression models.

RESULTS

Individuals with 22q11DS had, on average, 17.3% smaller total cerebellar volumes relative to typically developing subjects (p < .0001). The lobules of the superior posterior cerebellum (e.g., VII and VIII) were particularly affected in 22q11DS. However, all cerebellar lobules were significantly smaller, even after adjusting for total brain volumes (all cerebellar lobules p < .0002). The superior posterior lobule was disproportionately associated with cortical thickness in the frontal lobes and cingulate cortex, brain regions known be affected in 22q11DS. Exploratory analyses suggested that the superior posterior lobule, particularly Crus I, may be associated with psychotic symptoms in 22q11DS.

CONCLUSIONS

The cerebellum is a critical but understudied component of the 22q11DS neuroendophenotype.

Decision value signals in the ventromedial prefrontal cortex and motivational and hedonic symptoms across mood and psychotic disorders

Deficits in motivation and pleasure are common across many psychiatric disorders, and manifest as symptoms of amotivation and anhedonia, which are prominent features of both mood and psychotic disorders. Here we provide evidence for an association between neural value signals and symptoms of amotivation and anhedonia across adults with major depression, bipolar disorder, schizophrenia, or no psychiatric diagnosis. We found that value signals in the ventromedial prefrontal cortex (vmPFC) during intertemporal decision-making were dampened in individuals with greater motivational and hedonic deficits, after accounting for primary diagnosis. This relationship remained significant while controlling for diagnosis-specific symptoms of mood and psychosis, such as depression as well as positive and negative symptoms. Our results demonstrate that dysfunction in the vmPFC during value-based decision-making is specifically linked to motivational and hedonic impairments. These findings provide a quantitative neural target for the potential development of novel treatments for amotivation and anhedonia.

Development of a probability calculator for psychosis risk in children, adolescents, and young adults

BACKGROUND

Assessment of risks of illnesses has been an important part of medicine for decades. We now have hundreds of 'risk calculators' for illnesses, including brain disorders, and these calculators are continually improving as more diverse measures are collected on larger samples.

METHODS

We first replicated an existing psychosis risk calculator and then used our own sample to develop a similar calculator for use in recruiting 'psychosis risk' enriched community samples. We assessed 632 participants age 8-21 (52% female; 48% Black) from a community sample with longitudinal data on neurocognitive, clinical, medical, and environmental variables. We used this information to predict psychosis spectrum (PS) status in the future. We selected variables based on lasso, random forest, and statistical inference relief; and predicted future PS using ridge regression, random forest, and support vector machines.

RESULTS

Cross-validated prediction diagnostics were obtained by building and testing models in randomly selected sub-samples of the data, resulting in a distribution of the diagnostics; we report the mean. The strongest predictors of later PS status were the Children's Global Assessment Scale; delusions of predicting the future or having one's thoughts/actions controlled; and the percent married in one's neighborhood. Random forest followed by ridge regression was most accurate, with a cross-validated area under the curve (AUC) of 0.67. Adjustment of the model including only six variables reached an AUC of 0.70.

CONCLUSIONS

Results support the potential application of risk calculators for screening and identification of at-risk community youth in prospective investigations of developmental trajectories of the PS.

Comparison of two cognitive screening measures in a longitudinal sample of youth at-risk for psychosis

BACKGROUND

Validated screening tools are needed to detect subtle cognitive impairment in individuals at-risk for developing psychosis. Here, the utility of the Mini-Mental Status Examination (MMSE) and Penn Computerized Neurocognitive Battery (CNB) were evaluated for detecting cognitive impairment in individuals with psychosis spectrum (PS) symptoms.

METHODS

Participants (n = 229; 54 % female) completed the MMSE and CNB at baseline and two-year follow-up. PS (n = 91) and typically developing (TD; n = 138) participants were enrolled at baseline based on the presence or absence of PS symptoms. After two years, 65 participants remained PS, 104 participants remained TD, 23 participants had Emergent (EP) subthreshold PS symptoms, and 37 participants were experiencing Other Psychopathology (OP).

RESULTS

Generally, those with PS had lower scores than TD on both the MMSE (p < 0.0001) and CNB (p < 0.0001). Additionally, OP participants performed lower on the MMSE than TD (p = 0.02). Receiver operating characteristic (ROC) analyses indicated similar area under the curve (AUCs) for the two instruments (0.67); the MMSE showed higher specificity (0.71 vs. 0.62), while the CNB showed higher sensitivity (0.66 vs 0.52). Use of the MMSE and CNB in combination provided the highest diagnostic classification.

CONCLUSION

The MMSE and CNB can be used to screen for cognitive impairment in PS. The MMSE is better at ruling out PS-related cognitive impairment while the CNB is better at ruling in PS-related cognitive impairment. Overall, our results indicate that both tests are useful in screening for cognitive impairment, particularly in combination, in a PS population.

Stability of polygenic scores across discovery genome-wide association studies

Polygenic scores (PGS) are commonly evaluated in terms of their predictive accuracy at the population level by the proportion of phenotypic variance they explain. To be useful for precision medicine applications, they also need to be evaluated at the individual level when phenotypes are not necessarily already known. We investigated the stability of PGS in European American (EUR) and African American (AFR)-ancestry individuals from the Philadelphia Neurodevelopmental Cohort and the Adolescent Brain Cognitive Development study using different discovery genome-wide association study (GWAS) results for post-traumatic stress disorder (PTSD), type 2 diabetes (T2D), and height. We found that pairs of EUR-ancestry GWAS for the same trait had genetic correlations >0.92. However, PGS calculated from pairs of same-ancestry and different-ancestry GWAS had correlations that ranged from <0.01 to 0.74. PGS stability was greater for height than for PTSD or T2D. A series of height GWAS in the UK Biobank suggested that correlation between PGS is strongly dependent on the extent of sample overlap between the discovery GWAS. Focusing on the upper end of the PGS distribution, different discovery GWAS do not consistently identify the same individuals in the upper quantiles, with the best case being 60% of individuals above the 80th percentile of PGS overlapping from one height GWAS to another. The degree of overlap decreases sharply as higher quantiles, less heritable traits, and different-ancestry GWAS are considered. PGS computed from different discovery GWAS have only modest correlation at the individual level, underscoring the need to proceed cautiously with integrating PGS into precision medicine applications.

Effect of mGluR2 positive allosteric modulation on frontostriatal working memory activation in schizophrenia

Negative symptoms and cognitive deficits contribute strongly to disability in schizophrenia, and are resistant to existing medications. Recent drug development has targeted enhanced NMDA function by increasing mGluR2/3 signaling. However, the clinical utility of such agents remains uncertain, and markers of brain circuit function are critical for clarifying mechanisms and understanding individual differences in efficacy. We conducted a double-blind, placebo-controlled, randomized cross-over (14 day washout) pilot study evaluating adjunctive use of the mGluR2 positive allosteric modulator AZD8529 (80 mg daily for 3 days), in chronic stable patients with schizophrenia (n = 26 analyzed). We focused on 3 T fMRI response in frontostriatal regions during an n-back working memory task, testing the hypothesis that AZD8529 produces fMRI changes that correlate with improvement in negative symptoms and cognition. We found that AZD8529 did not produce significant group-average effects on symptoms or cognitive accuracy. However, AZD8529 did increase n-back fMRI activation in striatum (p < 0.0001) and anterior cingulate/paracingulate (p = 0.002). Greater drug-versus-placebo effects on caudate activation significantly correlated with greater reductions in PANSS negative symptom scores (r = -0.42, p = 0.031), and exploratory correlations suggested broader effects across multiple symptom domains and regions of interest. These findings demonstrate that fMRI responses to mGluR2 positive modulation relate to individual differences in symptom reduction, and could be pursued for future biomarker development. Negative clinical results at the group level should not lead to premature termination of investigation of this mechanism, which may benefit an important subset of individuals with schizophrenia. Imaging biomarkers may reveal therapeutic mechanisms, and help guide treatment toward specific populations.

Altered functional brain dynamics in chromosome 22q11.2 deletion syndrome during facial affect processing

Chromosome 22q11.2 deletion syndrome (22q11.2DS) is a multisystem disorder associated with multiple congenital anomalies, variable medical features, and neurodevelopmental differences resulting in diverse psychiatric phenotypes, including marked deficits in facial memory and social cognition. Neuroimaging in individuals with 22q11.2DS has revealed differences relative to matched controls in BOLD fMRI activation during facial affect processing tasks. However, time-varying interactions between brain areas during facial affect processing have not yet been studied with BOLD fMRI in 22q11.2DS. We applied constrained principal component analysis to identify temporally overlapping brain activation patterns from BOLD fMRI data acquired during an emotion identification task from 58 individuals with 22q11.2DS and 58 age-, race-, and sex-matched healthy controls. Delayed frontal-motor feedback signals were diminished in individuals with 22q11.2DS, as were delayed emotional memory signals engaging amygdala, hippocampus, and entorhinal cortex. Early task-related engagement of motor and visual cortices and salience-related insular activation were relatively preserved in 22q11.2DS. Insular activation was associated with task performance within the 22q11.2DS sample. Differences in cortical surface area, but not cortical thickness, showed spatial alignment with an activation pattern associated with face processing. These findings suggest that relative to matched controls, primary visual processing and insular function are relatively intact in individuals with 22q11.22DS, while motor feedback, face processing, and emotional memory processes are more affected. Such insights may help inform potential interventional targets and enhance the specificity of neuroimaging indices of cognitive dysfunction in 22q11.2DS.

Relationship of ventral striatum activation during effort discounting to clinical amotivation severity in schizophrenia

Motivational deficits play a central role in disability due to negative symptoms of schizophrenia (SZ), but limited pathophysiological understanding impedes critically needed therapeutic development. We applied an fMRI Effort Discounting Task (EDT) that quantifies motivation using a neuroeconomic decision-making approach, capturing the degree to which effort requirements produce reductions in the subjective value (SV) of monetary reward. An analyzed sample of 21 individuals with SZ and 23 group-matched controls performed the EDT during fMRI. We hypothesized that ventral striatum (VS) as well as extended brain motivation circuitry would encode SV, integrating reward and effort costs. We also hypothesized that VS hypoactivation during EDT decisions would demonstrate a dimensional relationship with clinical amotivation severity, reflecting greater suppression by effort costs. As hypothesized, VS as well as a broader cortico-limbic network were activated during the EDT and this activation correlated positively with SV. In SZ, activation to task decisions was reduced selectively in VS. Greater VS reductions correlated with more severe clinical amotivation in SZ and across all participants. However, these diagnosis and amotivation effects could not be explained by the response to parametric variation in reward, effort, or model-based SV. Our findings demonstrate that VS hypofunction in schizophrenia is manifested during effort-based decisions and reflects dimensional motivation impairment. Dysfunction of VS impacting effort-based decision-making can provide a target for biomarker development to guide novel efforts to assess and treat disabling amotivation.

Adaptation and validation of a computerized neurocognitive battery in the Xhosa of South Africa

OBJECTIVE

Large-scale studies have revolutionized biomedical research, and neurocognitive tests can help elucidate the biological basis of neuropsychiatric diseases. However, studies have predominantly been conducted in Western settings. We describe the development and validation of a computerized battery (PennCNB) with the Xhosa population of South Africa.

METHOD

Individuals with schizophrenia (n = 525) and a normative comparison group (n = 744) were balanced on age, sex, education, and region. Participants provided blood samples, were assessed psychiatrically, and were administered a PennCNB translation to isiXhosa, including measures of executive functions, episodic memory, complex cognition, social cognition, and sensorimotor speed. Feasibility was examined with test completion rates and input from administrators, and psychometric structural validity and associations with clinical and demographic characteristics were examined.

RESULTS

Tests were well tolerated by participants, as >87% had one (or fewer) test missing. Results suggested a similar factor structure to prior PennCNB studies in Western contexts, and expected age and sex effects were apparent. Furthermore, a similar profile of schizophrenia was observed, with neurocognitive deficits most pronounced for executive functions, especially attention, as well as memory, social cognition, and motor speed relative to complex cognition and sensorimotor speed.

CONCLUSIONS

Results support the feasibility of implementing a culturally adapted computerized neurocognitive battery in sub-Saharan African settings and provide evidence supporting the concurrent validity of the translated instrument. Thus, the PennCNB is implementable on a large scale in non-Western contexts, shows expected factor structure, and can detect cognitive deficits associated with neuropsychiatric disorders. Obtaining valid measures of cognition by nonspecialized proctors is especially suitable in resource-limited settings, where traditional testing is prohibitive. Future work should establish normative standards, test-retest reliability, and sensitivity to treatment. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Pitfalls in brain age analyses

Over the past decade, there has been an abundance of research on the difference between age and age predicted using brain features, which is commonly referred to as the “brain age gap.” Researchers have identified that the brain age gap, as a linear transformation of an out‐of‐sample residual, is dependent on age. As such, any group differences on the brain age gap could simply be due to group differences on age. To mitigate the brain age gap's dependence on age, it has been proposed that age be regressed out of the brain age gap. If this modified brain age gap is treated as a corrected deviation from age, model accuracy statistics such as R² will be artificially inflated to the extent that it is highly improbable that an R² value below .85 will be obtained no matter the true model accuracy. Given the limitations of proposed brain age analyses, further theoretical work is warranted to determine the best way to quantify deviation from normality.

Diminished reward responsiveness is associated with lower reward network GluCEST: an ultra-high field glutamate imaging study

Low reward responsiveness (RR) is associated with poor psychological well-being, psychiatric disorder risk, and psychotropic treatment resistance. Functional MRI studies have reported decreased activity within the brain's reward network in individuals with RR deficits, however the neurochemistry underlying network hypofunction in those with low RR remains unclear. This study employed ultra-high field glutamate chemical exchange saturation transfer (GluCEST) imaging to investigate the hypothesis that glutamatergic deficits within the reward network contribute to low RR. GluCEST images were acquired at 7.0 T from 45 participants (ages 15-29, 30 females) including 15 healthy individuals, 11 with depression, and 19 with psychosis spectrum symptoms. The GluCEST contrast, a measure sensitive to local glutamate concentration, was quantified in a meta-analytically defined reward network comprised of cortical, subcortical, and brainstem regions. Associations between brain GluCEST contrast and Behavioral Activation System Scale RR scores were assessed using multiple linear regressions. Analyses revealed that reward network GluCEST contrast was positively and selectively associated with RR, but not other clinical features. Follow-up investigations identified that this association was driven by the subcortical reward network and network areas that encode the salience of valenced stimuli. We observed no association between RR and the GluCEST contrast within non-reward cortex. This study thus provides new evidence that reward network glutamate levels contribute to individual differences in RR. Decreased reward network excitatory neurotransmission or metabolism may be mechanisms driving reward network hypofunction and RR deficits. These findings provide a framework for understanding the efficacy of glutamate-modulating psychotropics such as ketamine for treating anhedonia.

Associations between Neighborhood SES and Functional Brain Network Development

Higher socioeconomic status (SES) in childhood is associated with stronger cognitive abilities, higher academic achievement, and lower incidence of mental illness later in development. While prior work has mapped the associations between neighborhood SES and brain structure, little is known about the relationship between SES and intrinsic neural dynamics. Here, we capitalize upon a large cross-sectional community-based sample (Philadelphia Neurodevelopmental Cohort, ages 8-22 years, n = 1012) to examine associations between age, SES, and functional brain network topology. We characterize this topology using a local measure of network segregation known as the clustering coefficient and find that it accounts for a greater degree of SES-associated variance than mesoscale segregation captured by modularity. High-SES youth displayed stronger positive associations between age and clustering than low-SES youth, and this effect was most pronounced for regions in the limbic, somatomotor, and ventral attention systems. The moderating effect of SES on positive associations between age and clustering was strongest for connections of intermediate length and was consistent with a stronger negative relationship between age and local connectivity in these regions in low-SES youth. Our findings suggest that, in late childhood and adolescence, neighborhood SES is associated with variation in the development of functional network structure in the human brain.

When CAT is not an option: complementary methods of test abbreviation for neurocognitive batteries

INTRODUCTION

There is an obvious need for efficient measurement of neuropsychiatric phenomena. A proven method-computerized adaptive testing (CAT)-is not feasible for all tests, necessitating alternatives for increasing test efficiency.

METHODS

We combined/compared two methods for abbreviating rapid tests using two tests unamenable to CAT (a Continuous Performance Test [CPT] and n-back test [NBACK]). N=9,498 (mean age 14.2 years; 52% female) were administered the tests, and abbreviation was accomplished using methods answering two questions: what happens to measurement error as items are removed, and what happens to correlations with validity criteria as items are removed. The first was investigated using quasi-CAT simulation, while the second was investigated using bootstrapped confidence intervals around full-form-short-form comparisons.

RESULTS

Results for the two methods overlapped, suggesting that the CPT could be abbreviated to 57% of original and NBACK could be abbreviated to 87% of original with the max-acceptable loss of precision and min-acceptable relationships with validity criteria.

CONCLUSIONS

This method combination shows promise for use in other test types, and the divergent results for the CPT/NBACK demonstrate the methods' abilities to detect when a test should not be shortened. The methods should be used in combination because they emphasize complementary measurement qualities: precision/validity..

Altered white matter microstructure in 22q11.2 deletion syndrome: a multisite diffusion tensor imaging study

22q11.2 deletion syndrome (22q11DS)-a neurodevelopmental condition caused by a hemizygous deletion on chromosome 22-is associated with an elevated risk of psychosis and other developmental brain disorders. Prior single-site diffusion magnetic resonance imaging (dMRI) studies have reported altered white matter (WM) microstructure in 22q11DS, but small samples and variable methods have led to contradictory results. Here we present the largest study ever conducted of dMRI-derived measures of WM microstructure in 22q11DS (334 22q11.2 deletion carriers and 260 healthy age- and sex-matched controls; age range 6-52 years). Using harmonization protocols developed by the ENIGMA-DTI working group, we identified widespread reductions in mean, axial and radial diffusivities in 22q11DS, most pronounced in regions with major cortico-cortical and cortico-thalamic fibers: the corona radiata, corpus callosum, superior longitudinal fasciculus, posterior thalamic radiations, and sagittal stratum (Cohen's d's ranging from -0.9 to -1.3). Only the posterior limb of the internal capsule (IC), comprised primarily of corticofugal fibers, showed higher axial diffusivity in 22q11DS. 22q11DS patients showed higher mean fractional anisotropy (FA) in callosal and projection fibers (IC and corona radiata) relative to controls, but lower FA than controls in regions with predominantly association fibers. Psychotic illness in 22q11DS was associated with more substantial diffusivity reductions in multiple regions. Overall, these findings indicate large effects of the 22q11.2 deletion on WM microstructure, especially in major cortico-cortical connections. Taken together with findings from animal models, this pattern of abnormalities may reflect disrupted neurogenesis of projection neurons in outer cortical layers.

Structural and Functional Brain Parameters Related to Cognitive Performance Across Development: Replication and Extension of the Parieto-Frontal Integration Theory in a Single Sample

The parieto-frontal integration theory (PFIT) identified a fronto-parietal network of regions where individual differences in brain parameters most strongly relate to cognitive performance. PFIT was supported and extended in adult samples, but not in youths or within single-scanner well-powered multimodal studies. We performed multimodal neuroimaging in 1601 youths age 8-22 on the same 3-Tesla scanner with contemporaneous neurocognitive assessment, measuring volume, gray matter density (GMD), mean diffusivity (MD), cerebral blood flow (CBF), resting-state functional magnetic resonance imaging measures of the amplitude of low frequency fluctuations (ALFFs) and regional homogeneity (ReHo), and activation to a working memory and a social cognition task. Across age and sex groups, better performance was associated with higher volumes, greater GMD, lower MD, lower CBF, higher ALFF and ReHo, and greater activation for the working memory task in PFIT regions. However, additional cortical, striatal, limbic, and cerebellar regions showed comparable effects, hence PFIT needs expansion into an extended PFIT (ExtPFIT) network incorporating nodes that support motivation and affect. Associations of brain parameters became stronger with advancing age group from childhood to adolescence to young adulthood, effects occurring earlier in females. This ExtPFIT network is developmentally fine-tuned, optimizing abundance and integrity of neural tissue while maintaining a low resting energy state.

Alterations in white matter microstructure in individuals at persistent risk for psychosis

Abnormalities in brain white matter (WM) are reported in youth at-risk for psychosis. Yet, the neurodevelopmental time course of these abnormalities remains unclear. Thus, longitudinal diffusion-weighted imaging (DWI) was used to investigate WM abnormalities in youth at-risk for psychosis. A subset of individuals from the Philadelphia Neurodevelopmental Cohort (PNC) completed two DWI scans approximately 20 months apart. Youths were identified through structured interview as having subthreshold persistent psychosis risk symptoms (n = 46), and were compared to healthy typically developing participants (TD; n = 98). Analyses were conducted at voxelwise and regional levels. Nonlinear developmental patterns were examined using penalized splines within a generalized additive model. Compared to TD, youth with persistent psychosis risk symptoms had lower whole-brain WM fractional anisotropy (FA) and higher radial diffusivity (RD). Voxelwise analyses revealed clusters of significant WM abnormalities within the temporal and parietal lobes. Lower FA within the cingulum bundle of hippocampus and cerebrospinal tracts were the most robust deficits in individuals with persistent psychosis symptoms. These findings were consistent over two visits. Thus, it appears that WM abnormalities are present early in youth with persistent psychosis risk symptoms, however, there is little evidence to suggest that these features emerge in late adolescence or early adulthood. Future studies should seek to characterize WM abnormalities in younger individuals and follow individuals as subthreshold psychotic symptoms emerge.

Impact of childhood adversity on network reconfiguration dynamics during working memory in hypogonadal women

Many women with no history of cognitive difficulties experience executive dysfunction during menopause. Significant adversity during childhood negatively impacts executive function into adulthood and may be an indicator of women at risk of a mid-life cognitive decline. Previous studies have indicated that alterations in functional network connectivity underlie these negative effects of childhood adversity. There is growing evidence that functional brain networks are not static during executive tasks; instead, such networks reconfigure over time. Optimal dynamics are necessary for efficient executive function; while too little reconfiguration is insufficient for peak performance, too much reconfiguration (supra-optimal reconfiguration) is also maladaptive and associated with poorer performance. Here we examined the impact of adverse childhood experiences (ACEs) on network flexibility, a measure of dynamic reconfiguration, during a letter n-back task within three networks that support executive function: frontoparietal, salience, and default mode networks. Several animal and human subject studies have suggested that childhood adversity exerts lasting effects on executive function via serotonergic mechanisms. Tryptophan depletion (TD) was used to examine whether serotonin function drives ACE effects on network flexibility. We hypothesized that ACE would be associated with higher flexibility (supra-optimal flexibility) and that TD would further increase this measure. Forty women underwent functional imaging at two time points in this double-blind, placebo controlled, crossover study. Participants also completed the Penn Conditional Exclusion Test, a task assessing abstraction and mental flexibility. The effects of ACE and TD were evaluated using generalized estimating equations. ACE was associated with higher flexibility across networks (frontoparietal β = 0.00748, D = 2.79, p = 0.005; salience β = 0.00679, D = 3.02, p = 0.003; and default mode β = 0.00910, D = 3.53, p = 0.0004). While there was no interaction between ACE and TD, active TD increased network flexibility in both ACE groups in comparison to sham depletion (frontoparietal β = 0.00489, D = 2.15, p = 0.03; salience β = 0.00393, D = 1.91, p = 0.06; default mode β = 0.00334, D = 1.73, p = 0.08). These results suggest that childhood adversity has lasting impacts on dynamic reconfiguration of functional brain networks supporting executive function and that decreasing serotonin levels may exacerbate these effects.

Association of anxiety phenotypes with risk of depression and suicidal ideation in community youth

BACKGROUND

Anxiety symptoms are common in adolescence and are often considered developmentally benign. Yet for some, anxiety presents with serious comorbid nonanxiety psychopathology. Early identification of such "malignant" anxiety presentations is a major challenge. We aimed to characterize anxiety symptoms suggestive of risk for depression and suicidal ideation (SI) in community youths.

METHODS

Cross-sectional associations were evaluated in community youths (n = 7,054, mean age: 15.8) who were assessed for anxiety, depression, and SI. We employed factor and latent class analyses to identify anxiety clusters and subtypes. Longitudinal risk of anxiety was evaluated in a subset of 330 youths with longitudinal data on depression and SI (with baseline mean age of 12.3 years and follow-up mean age of 16.98 years).

OUTCOMES

Almost all (92%) adolescents reported anxiety symptoms. Data-driven approaches revealed anxiety factors and subtypes that were differentially associated with depression and SI. Cross-sectional analyses revealed that panic and generalized anxiety symptoms show the most robust associations with depression and SI. Longitudinal, multivariate analyses revealed that panic symptoms during early adolescence, not generalized anxiety symptoms, predict depression and SI for later adolescent years, particularly in males.

INTERPRETATION

Anxiety is common in youths, with certain symptom clusters/subtypes predicting risk for depression and SI. Panic symptoms in early adolescence, even below disorder threshold, predict high risk for late adolescent depression and SI.

Early language measures associated with later psychosis features in 22q11.2 deletion syndrome

The 22q11.2 deletion syndrome (22q11DS) is associated with impaired cognitive functions and increased risk for schizophrenia spectrum disorders. Speech and language deficits are prominent, with evidence of decline anteceding emergence of psychosis. There is paucity of data examining language function in children with 22q11DS with follow-up assessment of psychosis spectrum (PS) symptoms. We examined the association between early language measures, obtained clinically, and PS status, obtained on average 10.1 years later, in 166 youths with 22q11DS, with repeated language testing in 48. Participants were administered the Preschool Language Scale (receptive/expressive), and/or, for school aged children, the Clinical Evaluation of Language Fundamentals (receptive/expressive), and age appropriate IQ tests. The structured interview for prodromal syndromes (SIPS) assessed PS symptoms. We found that performance on all preschool measures showed age associated decline, and males performed more poorly on core composite (receptive/expressive) and receptive language measures. For language assessment later in childhood, poorer performance was consistently associated with subsequent PS status. Furthermore, steeper age-related decline was seen in the PS group across language measures and marginally for full-scale IQ. These findings suggest that while preschool language testing is useful in characterizing performance decline in individuals with 22q11DS, it does not robustly differentiate those with subsequent PS from those without. However, language testing in the school age population can help identify individuals with 22q11DS who are at risk for psychosis. Such data are needed for elucidating a lifespan trajectory for affected individuals and may help understand pathways to psychosis applicable to the general population.

Development of a computerised neurocognitive battery for children and adolescents with HIV in Botswana: study design and protocol for the Ntemoga study

INTRODUCTION

Neurodevelopmental delays and cognitive impairments are common in youth living with HIV. Unfortunately, in resource-limited settings, where HIV infection impacts millions of children, cognitive and neurodevelopmental disorders commonly go undetected because of a lack of appropriate assessment instruments and local expertise. Here, we present a protocol to culturally adapt and validate the Penn Computerized Neurocognitive Battery (PennCNB) and examine its validity for detecting both advanced and subtle neurodevelopmental problems among school-aged children affected by HIV in resource-limited settings.

METHODS AND ANALYSIS

This is a prospective, observational cohort study. The venue for this study is Gaborone, Botswana, a resource-limited setting with high rates of perinatal exposure to HIV and limited neurocognitive assessment tools and expertise. We aim to validate the PennCNB in this setting by culturally adapting and then administering the adapted version of the battery to 200 HIV-infected, 200 HIV-exposed uninfected and 240 HIV-unexposed uninfected children. A series of analyses will be conducted to examine the reliability and construct validity of the PennCNB in these populations.

ETHICS AND DISSEMINATION

This project received ethical approval from local and university Institutional Review Boards and involved extensive input from local stakeholders. If successful, the proposed tools will provide practical screening and streamlined, comprehensive assessments that could be implemented in resource-limited settings to identify children with cognitive deficits within programmes focused on the care and treatment of children affected by HIV. The utility of such assessments could also extend beyond children affected by HIV, increasing general access to paediatric cognitive assessments in resource-limited settings.

Large-scale mapping of cortical alterations in 22q11.2 deletion syndrome: Convergence with idiopathic psychosis and effects of deletion size

The 22q11.2 deletion (22q11DS) is a common chromosomal microdeletion and a potent risk factor for psychotic illness. Prior studies reported widespread cortical changes in 22q11DS, but were generally underpowered to characterize neuroanatomic abnormalities associated with psychosis in 22q11DS, and/or neuroanatomic effects of variability in deletion size. To address these issues, we developed the ENIGMA (Enhancing Neuro Imaging Genetics Through Meta-Analysis) 22q11.2 Working Group, representing the largest analysis of brain structural alterations in 22q11DS to date. The imaging data were collected from 10 centers worldwide, including 474 subjects with 22q11DS (age = 18.2 ± 8.6; 46.9% female) and 315 typically developing, matched controls (age = 18.0 ± 9.2; 45.9% female). Compared to controls, 22q11DS individuals showed thicker cortical gray matter overall (left/right hemispheres: Cohen's d = 0.61/0.65), but focal thickness reduction in temporal and cingulate cortex. Cortical surface area (SA), however, showed pervasive reductions in 22q11DS (left/right hemispheres: d = -1.01/-1.02). 22q11DS cases vs. controls were classified with 93.8% accuracy based on these neuroanatomic patterns. Comparison of 22q11DS-psychosis to idiopathic schizophrenia (ENIGMA-Schizophrenia Working Group) revealed significant convergence of affected brain regions, particularly in fronto-temporal cortex. Finally, cortical SA was significantly greater in 22q11DS cases with smaller 1.5 Mb deletions, relative to those with typical 3 Mb deletions. We found a robust neuroanatomic signature of 22q11DS, and the first evidence that deletion size impacts brain structure. Psychotic illness in this highly penetrant deletion was associated with similar neuroanatomic abnormalities to idiopathic schizophrenia. These consistent cross-site findings highlight the homogeneity of this single genetic etiology, and support the suitability of 22q11DS as a biological model of schizophrenia.

Gestational Age is Dimensionally Associated with Structural Brain Network Abnormalities Across Development

Prematurity is associated with diverse developmental abnormalities, yet few studies relate cognitive and neurostructural deficits to a dimensional measure of prematurity. Leveraging a large sample of children, adolescents, and young adults (age 8-22 years) studied as part of the Philadelphia Neurodevelopmental Cohort, we examined how variation in gestational age impacted cognition and brain structure later in development. Participants included 72 preterm youth born before 37 weeks' gestation and 206 youth who were born at term (37 weeks or later). Using a previously-validated factor analysis, cognitive performance was assessed in three domains: (1) executive function and complex reasoning, (2) social cognition, and (3) episodic memory. All participants completed T1-weighted neuroimaging at 3 T to measure brain volume. Structural covariance networks were delineated using non-negative matrix factorization, an advanced multivariate analysis technique. Lower gestational age was associated with both deficits in executive function and reduced volume within 11 of 26 structural covariance networks, which included orbitofrontal, temporal, and parietal cortices as well as subcortical regions including the hippocampus. Notably, the relationship between lower gestational age and executive dysfunction was accounted for in part by structural network deficits. Together, these findings emphasize the durable impact of prematurity on cognition and brain structure, which persists across development.

Mapping Subcortical Brain Alterations in 22q11.2 Deletion Syndrome: Effects of Deletion Size and Convergence With Idiopathic Neuropsychiatric Illness

OBJECTIVE

22q11.2 deletion syndrome (22q11DS) is among the strongest known genetic risk factors for schizophrenia. Previous studies have reported variable alterations in subcortical brain structures in 22q11DS. To better characterize subcortical alterations in 22q11DS, including modulating effects of clinical and genetic heterogeneity, the authors studied a large multicenter neuroimaging cohort from the ENIGMA 22q11.2 Deletion Syndrome Working Group.

METHODS

Subcortical structures were measured using harmonized protocols for gross volume and subcortical shape morphometry in 533 individuals with 22q11DS and 330 matched healthy control subjects (age range, 6-56 years; 49% female).

RESULTS

Compared with the control group, the 22q11DS group showed lower intracranial volume (ICV) and thalamus, putamen, hippocampus, and amygdala volumes and greater lateral ventricle, caudate, and accumbens volumes (Cohen's d values, -0.90 to 0.93). Shape analysis revealed complex differences in the 22q11DS group across all structures. The larger A-D deletion was associated with more extensive shape alterations compared with the smaller A-B deletion. Participants with 22q11DS with psychosis showed lower ICV and hippocampus, amygdala, and thalamus volumes (Cohen's d values, -0.91 to 0.53) compared with participants with 22q11DS without psychosis. Shape analysis revealed lower thickness and surface area across subregions of these structures. Compared with subcortical findings from other neuropsychiatric disorders studied by the ENIGMA consortium, significant convergence was observed between participants with 22q11DS with psychosis and participants with schizophrenia, bipolar disorder, major depressive disorder, and obsessive-compulsive disorder.

CONCLUSIONS

In the largest neuroimaging study of 22q11DS to date, the authors found widespread alterations to subcortical brain structures, which were affected by deletion size and psychotic illness. Findings indicate significant overlap between 22q11DS-associated psychosis, idiopathic schizophrenia, and other severe neuropsychiatric illnesses.

Temporal sequences of brain activity at rest are constrained by white matter structure and modulated by cognitive demands

A diverse set of white matter connections supports seamless transitions between cognitive states. However, it remains unclear how these connections guide the temporal progression of large-scale brain activity patterns in different cognitive states. Here, we analyze the brain's trajectories across a set of single time point activity patterns from functional magnetic resonance imaging data acquired during the resting state and an n-back working memory task. We find that specific temporal sequences of brain activity are modulated by cognitive load, associated with age, and related to task performance. Using diffusion-weighted imaging acquired from the same subjects, we apply tools from network control theory to show that linear spread of activity along white matter connections constrains the probabilities of these sequences at rest, while stimulus-driven visual inputs explain the sequences observed during the n-back task. Overall, these results elucidate the structural underpinnings of cognitively and developmentally relevant spatiotemporal brain dynamics.

Optimization of energy state transition trajectory supports the development of executive function during youth

Executive function develops during adolescence, yet it remains unknown how structural brain networks mature to facilitate activation of the fronto-parietal system, which is critical for executive function. In a sample of 946 human youths (ages 8-23y) who completed diffusion imaging, we capitalized upon recent advances in linear dynamical network control theory to calculate the energetic cost necessary to activate the fronto-parietal system through the control of multiple brain regions given existing structural network topology. We found that the energy required to activate the fronto-parietal system declined with development, and the pattern of regional energetic cost predicts unseen individuals' brain maturity. Finally, energetic requirements of the cingulate cortex were negatively correlated with executive performance, and partially mediated the development of executive performance with age. Our results reveal a mechanism by which structural networks develop during adolescence to reduce the theoretical energetic costs of transitions to activation states necessary for executive function.

Data-Driven Quantitative Susceptibility Mapping Using Loss Adaptive Dipole Inversion (LADI)

BACKGROUND

Quantitative susceptibility mapping (QSM) uses prior information to reconstruct maps, but prior information may not show pathology and introduce inconsistencies with susceptibility maps, degrade image quality and inadvertently smoothing image features.

PURPOSE

To develop a local field data-driven QSM reconstruction that does not depend on spatial edge prior information.

STUDY TYPE

Retrospective.

SUBJECTS, ANIMAL MODELS

A dataset from 2016 ISMRM QSM Challenge, 11 patients with glioblastoma, a patient with microbleeds and porcine heart.

SEQUENCE/FIELD STRENGTH

3D gradient echo sequence on 3T and 7T scanners.

ASSESSMENT

Accuracy was compared to Calculation of Susceptibility through Multiple Orientation Sampling (COSMOS), and several published techniques using region of interest (ROI) measurements, root-mean-squared error (RMSE), structural similarity index metric (SSIM), and high-frequency error norm (HFEN). Numerical ranking and semiquantitative image grading was performed by three expert observers to assess overall image quality (IQ) and image sharpness (IS).

STATISTICAL TESTS

Bland-Altman, Friedman test, and Conover multiple comparisons.

RESULTS

Loss adaptive dipole inversion (LADI) (β = 0.82, R² = 0.96), morphology-enabled dipole inversion (MEDI) (β = 0.91, R² = 0.97), and fast nonlinear susceptibility inversion (FANSI) (β = 0.81, R² = 0.98) had excellent correlation with COSMOS and no bias was detected (bias = 0.006 ± 0.014, P < 0.05). In glioblastoma patients, LADI showed consistently better performance (IQ_Grade = 2.6 ± 0.4, IS_Grade = 2.6 ± 0.3, IQ_Rank = 3.5 ± 0.4, IS_Rank = 3.9 ± 0.2) compared with MEDI (IQ_Grade = 2.1 ± 0.3, IS_Grade = 2 ± 0.5, IQ_Rank = 2.4 ± 0.5, IS_Rank = 2.8 ± 0.2) and FANSI (IQ_Grade = 2.2 ± 0.5, IS_Grade = 2 ± 0.4, IQ_Rank = 2.8 ± 0.3, IS_Rank = 2.1 ± 0.2). Dark artifact visible near the infarcted region in MEDI (Inf_MEDI = -0.27 ± 0.06 ppm) was better mitigated by FANSI (Inf_FANSI-TGV = -0.17 ± 0.05 ppm) and LADI (Inf_LADI = -0.18 ± 0.05 ppm).

CONCLUSION

For neuroimaging applications, LADI preserved image sharpness and fine features in glioblastoma and microbleed patients. LADI performed better at mitigating artifacts in cardiac QSM.

EVIDENCE LEVEL

4 TECHNICAL EFFICACY STAGE: 1 J. Magn. Reson. Imaging 2020;52:823-835.

Neurostructural Heterogeneity in Youths With Internalizing Symptoms

BACKGROUND

Internalizing disorders such as anxiety and depression are common psychiatric disorders that frequently begin in youth and exhibit marked heterogeneity in treatment response and clinical course. Given that symptom-based classification approaches do not align with underlying neurobiology, an alternative approach is to identify neurobiologically informed subtypes based on brain imaging data.

METHODS

We used a recently developed semisupervised machine learning method (HYDRA [heterogeneity through discriminative analysis]) to delineate patterns of neurobiological heterogeneity within youths with internalizing symptoms using structural data collected at 3T from a sample of 1141 youths.

RESULTS

Using volume and cortical thickness, cross-validation methods indicated 2 highly stable subtypes of internalizing youths (adjusted Rand index = 0.66; permutation-based false discovery rate p < .001). Subtype 1, defined by smaller brain volumes and reduced cortical thickness, was marked by impaired cognitive performance and higher levels of psychopathology than both subtype 2 and typically developing youths. Using resting-state functional magnetic resonance imaging and diffusion images not considered during clustering, we found that subtype 1 also showed reduced amplitudes of low-frequency fluctuations in frontolimbic regions at rest and reduced fractional anisotropy in several white matter tracts. In contrast, subtype 2 showed intact cognitive performance and greater volume, cortical thickness, and amplitudes during rest compared with subtype 1 and typically developing youths, despite still showing clinically significant levels of psychopathology.

CONCLUSIONS

We identified 2 subtypes of internalizing youths differentiated by abnormalities in brain structure, function, and white matter integrity, with one of the subtypes showing poorer functioning across multiple domains. Identification of biologically grounded internalizing subtypes may assist in targeting early interventions and assessing longitudinal prognosis.

Age, Sex, and Repeated Measures Effects on NASA's "Cognition" Test Battery in STEM Educated Adults

BACKGROUND: Cognition is a neurocognitive test battery created at the University of Pennsylvania and adapted by the National Aeronautics and Space Administration (NASA). It comprises 10 neurocognitive tests that examine multiple domains, and has been validated in a normative sample of STEM-educated adults and compared to NASA's WinSCAT battery.METHODS: The purpose of this study was to follow the original sample to assess Cognition and WinSCAT's test-retest reliability and age, sex, and test-retest interval effects on performance.RESULTS: Performance on both Cognition and WinSCAT decreased with age but improved with repeated administration due to practice effects, and men had higher scores than women on tasks that required vigilant attention, spatial reasoning, and risk-taking behaviors. Assessment of test-retest reliability showed intraclass coefficients for efficiency ranging from 0.417 to 0.810, reflecting the broad nature of constructs assessed by Cognition.DISCUSSION: Results largely matched predictions, with some counter-intuitive results for test-retest reliability interval.Lee G, Moore TM, Basner M, Nasrini J, Roalf DR, Ruparel K, Port AM, Dinges DF, Gur RC. Age, sex, and repeated measures effects on NASA's "Cognition" Test Battery in STEM educated adults. Aerosp Med Hum Perform. 2020; 91(1):18-25.

Evidence for Dissociable Linkage of Dimensions of Psychopathology to Brain Structure in Youths

OBJECTIVE

High comorbidity among psychiatric disorders suggests that they may share underlying neurobiological deficits. Abnormalities in cortical thickness and volume have been demonstrated in clinical samples of adults, but less is known when these structural differences emerge in youths. The purpose of this study was to examine the association between dimensions of psychopathology and brain structure.

METHODS

The authors studied 1,394 youths who underwent brain imaging as part of the Philadelphia Neurodevelopmental Cohort. Dimensions of psychopathology were constructed using a bifactor model of symptoms. Cortical thickness and volume were quantified using high-resolution 3-T MRI. Structural covariance networks were derived using nonnegative matrix factorization and analyzed using generalized additive models with penalized splines to capture both linear and nonlinear age-related effects.

RESULTS

Fear symptoms were associated with reduced cortical thickness in most networks, and overall psychopathology was associated with globally reduced gray matter volume across all networks. Structural covariance networks predicted psychopathology symptoms above and beyond demographic characteristics and cognitive performance.

CONCLUSIONS

The results suggest a dissociable relationship whereby fear is most strongly linked to reduced cortical thickness and overall psychopathology is most strongly linked to global reductions in gray matter volume. Such results have implications for understanding how abnormalities of brain development may be associated with divergent dimensions of psychopathology.

Reduced safety processing during aversive social conditioning in psychosis and clinical risk

Social impairment occurs across the psychosis spectrum, but its pathophysiology remains poorly understood. Here we tested the hypothesis that reduced differential responses (aversive vs. neutral) in neural circuitry underpinning aversive conditioning of social stimuli characterizes the psychosis spectrum. Participants age 10-30 included a healthy control group (HC, analyzed n = 36) and a psychosis spectrum group (PSY, n = 71), including 49 at clinical risk for psychosis and 22 with a frank psychotic disorder. 3T fMRI utilized a passive aversive conditioning paradigm, with neutral faces as conditioned stimuli (CS) and a scream as the unconditioned stimulus. fMRI conditioning was indexed as the activation difference between aversive and neutral trials. Analysis focused on amygdala, ventromedial prefrontal cortex, and anterior insula, regions previously implicated in aversive and social-emotional processing. Ventromedial prefrontal cortex activated more to neutral than aversive CS; this "safety effect" was driven by HC and reduced in PSY, and correlated with subjective emotional ratings following conditioning. Insula showed the expected aversive conditioning effect, and although no group differences were found, its activation in PSY correlated with anxiety severity. Unexpectedly, amygdala did not show aversive conditioning; its activation trended greater for neutral than aversive CS, and did not differ significantly based on group or symptom severity. We conclude that abnormalities in social aversive conditioning are present across the psychosis spectrum including clinical risk, linked to a failure of safety processing. Aversive and safety learning provide translational paradigms yielding insight into pathophysiology of psychosis risk, and providing potential targets for therapeutic and preventative interventions.

Accelerated cortical thinning within structural brain networks is associated with irritability in youth

Irritability is an important dimension of psychopathology that spans multiple clinical diagnostic categories, yet its relationship to patterns of brain development remains sparsely explored. Here, we examined how transdiagnostic symptoms of irritability relate to the development of structural brain networks. All participants (n = 137, 83 females) completed structural brain imaging with 3 Tesla MRI at two timepoints (mean age at follow-up: 21.1 years, mean inter-scan interval: 5.2 years). Irritability at follow-up was assessed using the Affective Reactivity Index, and cortical thickness was quantified using Advanced Normalization Tools software. Structural covariance networks were delineated using non-negative matrix factorization, a multivariate analysis technique. Both cross-sectional and longitudinal associations with irritability at follow-up were evaluated using generalized additive models with penalized splines. The False Discovery Rate (q < 0.05) was used to correct for multiple comparisons. Cross-sectional analysis of follow-up data revealed that 11 of the 24 covariance networks were associated with irritability, with higher levels of irritability being associated with thinner cortex. Longitudinal analyses further revealed that accelerated cortical thinning within nine networks was related to irritability at follow-up. Effects were particularly prominent in brain regions implicated in emotion regulation, including the orbitofrontal, lateral temporal, and medial temporal cortex. Collectively, these findings suggest that irritability is associated with widespread reductions in cortical thickness and accelerated cortical thinning, particularly within the frontal and temporal cortex. Aberrant structural maturation of regions important for emotional regulation may in part underlie symptoms of irritability.

Burden of Environmental Adversity Associated With Psychopathology, Maturation, and Brain Behavior Parameters in Youths

IMPORTANCE

Low socioeconomic status (L-SES) and the experience of traumatic stressful events (TSEs) are environmental factors implicated in behavioral deficits, abnormalities in brain development, and accelerated maturation. However, the relative contribution of these environmental factors is understudied.

OBJECTIVE

To compare the association of L-SES and TSEs with psychopathology, puberty, neurocognition, and multimodal neuroimaging parameters in brain maturation.

DESIGN, SETTING, AND PARTICIPANTS

The Philadelphia Neurodevelopmental Cohort is a community-based study examining psychopathology, neurocognition, and neuroimaging among participants recruited through the Children's Hospital of Philadelphia pediatric network. Participants are youths aged 8 to 21 years at enrollment with stable health and fluency in English. The sample of 9498 participants was racially (5298 European ancestry [55.8%], 3124 African ancestry [32.9%], and 1076 other [11.4%]) and economically diverse. A randomly selected subsample (n = 1601) underwent multimodal neuroimaging. Data were collected from November 5, 2009, through December 30, 2011, and analyzed from February 1 through November 7, 2018.

MAIN OUTCOMES AND MEASURES

The following domains were examined: (1) clinical, including psychopathology, assessed with a structured interview based on the Schedule for Affective Disorders and Schizophrenia for School-Age Children, and puberty, assessed with the Tanner scale; (2) neurocognition, assessed by the Penn Computerized Neurocognitive Battery; and (3) multimodal magnetic resonance imaging parameters of brain structure and function.

RESULTS

A total of 9498 participants were included in the analysis (4906 [51.7%] female; mean [SD] age, 14.2 [3.7] years). Clinically, L-SES and TSEs were associated with greater severity of psychiatric symptoms across the psychopathology domains of anxiety/depression, fear, externalizing behavior, and the psychosis spectrum. Low SES showed small effect sizes (highest for externalizing behavior, 0.306 SD; 95% CI, 0.269 to 0.342), whereas TSEs had large effect sizes, with the highest in females for anxiety/depression (1.228 SD; 95% CI, 1.156 to 1.300) and in males for the psychosis spectrum (1.099 SD; 95% CI, 1.032 to 1.166). Both were associated with early puberty. Cognitively, L-SES had moderate effect sizes on poorer performance, the greatest being on complex cognition (-0.500 SD 95% CI, -0.536 to -0.464), whereas TSEs were associated with slightly better memory (0.129 SD; 95% CI, 0.084 to 0.174) and poorer complex reasoning (-0.109 SD; 95% CI, -0.154 to -0.064). Environmental factors had common and distinct associations with brain structure and function. Structurally, both were associated with lower volume, but L-SES had correspondingly lower gray matter density, whereas TSEs were associated with higher gray matter density. Functionally, both were associated with lower regional cerebral blood flow and coherence and with accelerated brain maturation.

CONCLUSIONS AND RELEVANCE

Low SES and TSEs are associated with common and unique differences in symptoms, neurocognition, and structural and functional brain parameters. Both environmental factors are associated with earlier completion of puberty by physical features and brain parameters. These findings appear to underscore the need for identifying and preventing adverse environmental conditions associated with neurodevelopment.

Development and public release of the Penn Reading Assessment Computerized Adaptive Test (PRA-CAT) for premorbid IQ

An important component of neuropsychological testing is assessment of premorbid intelligence to estimate a patient's ability independent of neurological impairment. A common test of premorbid IQ-namely, the Reading section of the Wide Range Achievement Test (WRAT)-has been shown to have high measurement error in the high ability range, is unnecessarily long (55 items), and is proprietary. We describe the development of an alternative, nonproprietary, computerized adaptive test for premorbid IQ, the Penn Reading Assessment (PRA-CAT). PRA-CAT items were calibrated using a 1-parameter item response theory model in a large community sample (N = 9,498), Ages 8 to 21, and the resulting parameters were used to simulate computerized adaptive testing sessions. Simulations demonstrated that the PRA-CAT achieves low measurement error (0.25; equivalent to Cronbach's alpha = .94) and acceptable measurement error (0.40; Cronbach's alpha = .84) after only 18 and 6 items, respectively (on average). Correlation of WRAT and PRA-CAT scores with numerous clinical, cognitive, demographic, and neuroimaging criteria suggests that validity of PRA-CAT score interpretation is comparable (and sometimes superior) with the WRAT. The fully functioning PRA-CAT for public use (including item parameter estimates reported here) has been built using the open-source program Concerto, and can be installed by anyone on a local computer or on the "cloud." Given the length and proprietary nature of the WRAT, the PRA-CAT shows promise as a potential alternative (and with minimal or no cost). Further validation in the context of neurological injury is needed. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Robust spatial extent inference with a semiparametric bootstrap joint inference procedure

Spatial extent inference (SEI) is widely used across neuroimaging modalities to adjust for multiple comparisons when studying brain-phenotype associations that inform our understanding of disease. Recent studies have shown that Gaussian random field (GRF)-based tools can have inflated family-wise error rates (FWERs). This has led to substantial controversy as to which processing choices are necessary to control the FWER using GRF-based SEI. The failure of GRF-based methods is due to unrealistic assumptions about the spatial covariance function of the imaging data. A permutation procedure is the most robust SEI tool because it estimates the spatial covariance function from the imaging data. However, the permutation procedure can fail because its assumption of exchangeability is violated in many imaging modalities. Here, we propose the (semi-) parametric bootstrap joint (PBJ; sPBJ) testing procedures that are designed for SEI of multilevel imaging data. The sPBJ procedure uses a robust estimate of the spatial covariance function, which yields consistent estimates of standard errors, even if the covariance model is misspecified. We use the methods to study the association between performance and executive functioning in a working memory functional magnetic resonance imaging study. The sPBJ has similar or greater power to the PBJ and permutation procedures while maintaining the nominal type 1 error rate in reasonable sample sizes. We provide an R package to perform inference using the PBJ and sPBJ procedures.

Faster family-wise error control for neuroimaging with a parametric bootstrap

In neuroimaging, hundreds to hundreds of thousands of tests are performed across a set of brain regions or all locations in an image. Recent studies have shown that the most common family-wise error (FWE) controlling procedures in imaging, which rely on classical mathematical inequalities or Gaussian random field theory, yield FWE rates (FWER) that are far from the nominal level. Depending on the approach used, the FWER can be exceedingly small or grossly inflated. Given the widespread use of neuroimaging as a tool for understanding neurological and psychiatric disorders, it is imperative that reliable multiple testing procedures are available. To our knowledge, only permutation joint testing procedures have been shown to reliably control the FWER at the nominal level. However, these procedures are computationally intensive due to the increasingly available large sample sizes and dimensionality of the images, and analyses can take days to complete. Here, we develop a parametric bootstrap joint testing procedure. The parametric bootstrap procedure works directly with the test statistics, which leads to much faster estimation of adjusted p-values than resampling-based procedures while reliably controlling the FWER in sample sizes available in many neuroimaging studies. We demonstrate that the procedure controls the FWER in finite samples using simulations, and present region- and voxel-wise analyses to test for sex differences in developmental trajectories of cerebral blood flow.

Sex differences in estimated brain metabolism in relation to body growth through adolescence

The human brain consumes a disproportionate amount of the body's overall metabolic resources, and evidence suggests that brain and body may compete for substrate during development. Using perfusion MRI from a large cross-sectional cohort, we examined developmental changes of MRI-derived estimates of brain metabolism, in relation to weight change. Nonlinear models demonstrated that, in childhood, changes in body weight were inversely related to developmental age-related changes in brain metabolism. This inverse relationship persisted through early adolescence, after which body and brain metabolism began to decline. Females achieved maximum body growth approximately two years earlier than males, with a correspondingly earlier stabilization of brain metabolism to adult levels. These findings confirm prior findings with positron emission tomography performed in a much smaller cohort, demonstrate that relative brain metabolism can be inferred from noninvasive MRI data, and extend observations on the associations between body growth and brain metabolism to sex differences through adolescence.

Common and dissociable regional cerebral blood flow differences associate with dimensions of psychopathology across categorical diagnoses

The high comorbidity among neuropsychiatric disorders suggests a possible common neurobiological phenotype. Resting-state regional cerebral blood flow (CBF) can be measured noninvasively with magnetic resonance imaging (MRI) and abnormalities in regional CBF are present in many neuropsychiatric disorders. Regional CBF may also provide a useful biological marker across different types of psychopathology. To investigate CBF changes common across psychiatric disorders, we capitalized upon a sample of 1042 youths (ages 11-23 years) who completed cross-sectional imaging as part of the Philadelphia Neurodevelopmental Cohort. CBF at rest was quantified on a voxelwise basis using arterial spin labeled perfusion MRI at 3T. A dimensional measure of psychopathology was constructed using a bifactor model of item-level data from a psychiatric screening interview, which delineated four factors (fear, anxious-misery, psychosis and behavioral symptoms) plus a general factor: overall psychopathology. Overall psychopathology was associated with elevated perfusion in several regions including the right dorsal anterior cingulate cortex (ACC) and left rostral ACC. Furthermore, several clusters were associated with specific dimensions of psychopathology. Psychosis symptoms were related to reduced perfusion in the left frontal operculum and insula, whereas fear symptoms were associated with less perfusion in the right occipital/fusiform gyrus and left subgenual ACC. Follow-up functional connectivity analyses using resting-state functional MRI collected in the same participants revealed that overall psychopathology was associated with decreased connectivity between the dorsal ACC and bilateral caudate. Together, the results of this study demonstrate common and dissociable CBF abnormalities across neuropsychiatric disorders in youth.