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Understanding the fundamental alterations in brain functioning that lead to psychotic disorders remains a major challenge in clinical neuroscience. In particular, it is unknown whether any state-independent biomarkers can potentially predict the onset of psychosis and distinguish patients from healthy controls, regardless of paradigm. Here, using multi-paradigm fMRI data from the North American Prodrome Longitudinal Study consortium, we show that individuals at clinical high risk for psychosis display an intrinsic “trait-like” abnormality in brain architecture characterized as increased connectivity in the cerebello–thalamo–cortical circuitry, a pattern that is significantly more pronounced among converters compared with non-converters. This alteration is significantly correlated with disorganization symptoms and predictive of time to conversion to psychosis. Moreover, using an independent clinical sample, we demonstrate that this hyperconnectivity pattern is reliably detected and specifically present in patients with schizophrenia. These findings implicate cerebello–thalamo–cortical hyperconnectivity as a robust state-independent neural signature for psychosis prediction and characterization. Brain function alterations in schizophrenia and other psychotic disorders remain poorly understood. Here, the authors discover that increased neural connectivity in the cerebello-thalamo-cortical circuitry predicts psychosis in those at high risk, and is present in people with schizophrenia.

Experience-dependent plasticity is a fundamental property of the brain. It is critical for everyday function, is impaired in a range of neurological and psychiatric disorders, and frequently depends on long-term potentiation (LTP). Preclinical studies suggest that augmentingN-methyl-D-aspartate receptor (NMDAR) signaling may promote experience-dependent plasticity; however, a lack of noninvasive methods has limited our ability to test this idea in humans until recently. We examined the effects of enhancing NMDAR signaling using D-cycloserine (DCS) on a recently developed LTP EEG paradigm that uses high-frequency visual stimulation (HFvS) to induce neural potentiation in visual cortex neurons, as well as on three cognitive tasks: a weather prediction task (WPT), an information integration task (IIT), and an-back task. The WPT and IIT are learning tasks that require practice with feedback to reach optimal performance. Then-back assesses working memory. Healthy adults were randomized to receive DCS (100 mg;n= 32) or placebo (n= 33); groups were similar in IQ and demographic characteristics. Participants who received DCS showed enhanced potentiation of neural responses following repetitive HFvS, as well as enhanced performance on the WPT and IIT. Groups did not differ on then-back. Augmenting NMDAR signaling using DCS therefore enhanced activity-dependent plasticity in human adults, as demonstrated by lasting enhancement of neural potentiation following repetitive HFvS and accelerated acquisition of two learning tasks. Results highlight the utility of considering cellular mechanisms underlying distinct cognitive functions when investigating potential cognitive enhancers.

Motor dysfunction is a consistently reported but understudied aspect of schizophrenia. Postural sway area was examined in individuals with schizophrenia under four conditions with different amounts of visual and proprioceptive feedback: eyes open or closed and feet together or shoulder width apart. The nonlinear complexity of postural sway was assessed by detrended fluctuation analysis (DFA). The schizophrenia group (n = 27) exhibited greater sway area compared to controls (n = 37). Participants with schizophrenia showed increased sway area following the removal of visual input, while this pattern was absent in controls. Examination of DFA revealed decreased complexity of postural sway and abnormal changes in complexity upon removal of visual input in individuals with schizophrenia. Additionally, less complex postural sway was associated with increased symptom severity in participants with schizophrenia. Given the critical involvement of the cerebellum and related circuits in postural stability and sensorimotor integration, these results are consistent with growing evidence of motor, cerebellar, and sensory integration dysfunction in the disorder, and with theoretical models that implicate cerebellar deficits and more general disconnection of function in schizophrenia.

Multi-site neuroimaging studies offer an efficient means to study brain functioning in large samples of individuals with rare conditions; however, they present new challenges given that aggregating data across sites introduces additional variability into measures of interest. Assessing the reliability of brain activation across study sites and comparing statistical methods for pooling functional data are critical to ensuring the validity of aggregating data across sites. The current study used two samples of healthy individuals to assess the feasibility and reliability of aggregating multi-site functional magnetic resonance imaging (fMRI) data from a Sternberg-style verbal working memory task. Participants were recruited as part of the North American Prodrome Longitudinal Study (NAPLS), which comprises eight fMRI scanning sites across the United States and Canada. In the first study sample (n=8), one participant from each home site traveled to each of the sites and was scanned while completing the task on two consecutive days. Reliability was examined using generalizability theory. Results indicated that blood oxygen level-dependent (BOLD) signal was reproducible across sites and was highly reliable, or generalizable, across scanning sites and testing days for core working memory ROIs (generalizability ICCs=0.81 for left dorsolateral prefrontal cortex, 0.95 for left superior parietal cortex). In the second study sample (n=154), two statistical methods for aggregating fMRI data across sites for all healthy individuals recruited as control participants in the NAPLS study were compared. Control participants were scanned on one occasion at the site from which they were recruited. Results from the image-based meta-analysis (IBMA) method and mixed effects model with site covariance method both showed robust activation in expected regions (i.e. dorsolateral prefrontal cortex, anterior cingulate cortex, supplementary motor cortex, superior parietal cortex, inferior temporal cortex, cerebellum, thalamus, basal ganglia). Quantification of the similarity of group maps from these methods confirmed a very high (96%) degree of spatial overlap in results. Thus, brain activation during working memory function was reliable across the NAPLS sites and both the IBMA and mixed effects model with site covariance methods appear to be valid approaches for aggregating data across sites. These findings indicate that multi-site functional neuroimaging can offer a reliable means to increase power and generalizability of results when investigating brain function in rare populations and support the multi-site investigation of working memory function in the NAPLS study, in particular. •We examined reliability of fMRI during a working memory task in a multi-site study.•Greater variance due to person than site factors in variance component analysis.•Reliability coefficients showed excellent reliability for person effect in primary ROIs.•Two methods for aggregating data across sites produced similar activation maps.•Implications for design and implementation of multi-site fMRI studies.

Schizophrenia is a chronic and severe mental illness which frequently leads to substantial lifelong disability. The past five years have seen major progress in our understanding of the complex genetic architecture of this disorder. Two major barriers to understanding the core biological processes that underlie schizophrenia and developing better interventions are (1) the absence of etiologically defined biomarkers and (2) the clinical and genetic heterogeneity of the disorder. Here, we review recent advances that have led to changes in our understanding of risk factors and mechanisms involved in the development of schizophrenia. In particular, mechanistic and clinically oriented approaches have now converged on a focus on disruptions in early neurodevelopment and synaptic plasticity as being critical for both understanding trajectories and intervening to change them. Translating these new findings into treatments that substantively change the lives of patients is the next major challenge for the field.

While functional neuroimaging studies typically focus on a particular paradigm to investigate network connectivity, the human brain appears to possess an intrinsic “trait” architecture that is independent of any given paradigm. We have previously proposed the use of “cross-paradigm connectivity (CPC)” to quantify shared connectivity patterns across multiple paradigms and have demonstrated the utility of such measures in clinical studies. Here, using generalizability theory and connectome fingerprinting, we examined the reliability, stability, and individual identifiability of CPC in a group of highly-sampled healthy traveling subjects who received fMRI scans with a battery of five paradigms across multiple sites and days. Compared with single-paradigm connectivity matrices, the CPC matrices showed higher reliability in connectivity diversity, lower reliability in connectivity strength, higher stability, and higher individual identification accuracy. All of these assessments increased as a function of number of paradigms included in the CPC analysis. In comparisons involving different paradigm combinations and different brain atlases, we observed significantly higher reliability, stability, and identifiability for CPC matrices constructed from task-only data (versus those from both task and rest data), and higher identifiability but lower stability for CPC matrices constructed from the Power atlas (versus those from the AAL atlas). Moreover, we showed that multi-paradigm CPC matrices likely reflect the brain’s “trait” structure that cannot be fully achieved from single-paradigm data, even with multiple runs. The present results provide evidence for the feasibility and utility of CPC in the study of functional “trait” networks and offer some methodological implications for future CPC studies.

Cognitive development after schizophrenia onset can be shaped by interventions such as cognitive remediation, yet no study to date has investigated whether patterns of early behavioral development may predict later cognitive changes following intervention. We therefore investigated the extent to which premorbid adjustment trajectories predict cognitive remediation gains in schizophrenia. In a total sample of 215 participants (170 first-episode schizophrenia participants and 45 controls), we classified premorbid functioning trajectories from childhood through late adolescence using the Cannon-Spoor Premorbid Adjustment Scale. For the 62 schizophrenia participants who underwent 6 months of computer-assisted, bottom-up cognitive remediation interventions, we identified MATRICS Consensus Cognitive Battery scores for which participants demonstrated mean changes after intervention, then evaluated whether developmental trajectories predicted these changes. Growth mixture models supported three premorbid functioning trajectories: stable-good, deteriorating, and stable-poor adjustment. Schizophrenia participants demonstrated significant cognitive remediation gains in processing speed, verbal learning, and overall cognition. Notably, participants with stable-poor trajectories demonstrated significantly greater improvements in processing speed compared to participants with deteriorating trajectories. This is the first study to our knowledge to characterize the associations between premorbid functioning trajectories and cognitive remediation gains after schizophrenia onset, indicating that 6 months of bottom-up cognitive remediation appears to be sufficient to yield a full standard deviation gain in processing speed for individuals with early, enduring functioning difficulties. Our findings highlight the connection between trajectories of premorbid and postmorbid functioning in schizophrenia and emphasize the utility of considering the lifespan developmental course in personalizing therapeutic interventions.

Probing naturally-occurring, reciprocal genomic copy number variations (CNVs) may help us understand mechanisms that underlie deviations from typical brain development. Cross-sectional studies have identified prominent reductions in cortical surface area (SA) and increased cortical thickness (CT) in 22q11.2 deletion carriers (22qDel), with the opposite pattern in duplication carriers (22qDup), but the longitudinal trajectories of these anomalies—and their relationship to clinical symptomatology—are unknown. Here, we examined neuroanatomic changes within a longitudinal cohort of 261 22q11.2 CNV carriers and demographically-matched typically developing (TD) controls (84 22qDel, 34 22qDup, and 143 TD; mean age 18.35, ±10.67 years; 50.47% female). A total of 431 magnetic resonance imaging scans (164 22qDel, 59 22qDup, and 208 TD control scans; mean interscan interval = 20.27 months) were examined. Longitudinal FreeSurfer analysis pipelines were used to parcellate the cortex and calculate average CT and SA for each region. First, general additive mixed models (GAMMs) were used to identify regions with between-group differences in developmental trajectories. Secondly, we investigated whether these trajectories were associated with clinical outcomes. Developmental trajectories of CT were more protracted in 22qDel relative to TD and 22qDup. 22qDup failed to show normative age-related SA decreases. 22qDel individuals with psychosis spectrum symptoms showed two distinct periods of altered CT trajectories relative to 22qDel without psychotic symptoms. In contrast, 22q11.2 CNV carriers with autism spectrum diagnoses showed early alterations in SA trajectories. Collectively, these results provide new insights into altered neurodevelopment in 22q11.2 CNV carriers, which may shed light on neural mechanisms underlying distinct clinical outcomes.

Subtle behavioral and cognitive symptoms precede schizophrenia (SCZ) and appear in individuals with elevated risk based on polygenic risk scores (SCZ-PRS) and family history of psychosis (SCZ-FH). However, most SCZ-PRS studies focus on European ancestry youth, limiting generalizability. Furthermore, it remains unclear whether SCZ-FH reflects common-variant polygenic risk or broader SCZ liability. Using baseline data from the Adolescent Brain Cognitive Development (ABCD) study, we investigated associations of SCZ-FH and SCZ-PRS with cognitive, behavioral, and emotional measures from NIH-Toolbox, Child Behavior Checklist (CBCL), and Kiddie Schedule for Affective Disorders and Schizophrenia (KSADS) for 9,636 children (mean age = 9.92 yrs, 47.4% female), specifically, 5,636 European, 2,093 African, and 1,477 Admixed American ancestry individuals. SCZ-FH was associated with SCZ-PRS (  = 0.05, FDR-  = 0.02) and subthreshold psychotic symptoms (  = 0.46, FDR-  = 0.01) in European youth, higher CBCL scores ( range = 0.36-0.6, FDR-  < 0.001), and higher odds of multiple internalizing and externalizing disorders (OR = 1.10-1.22, FDR-  < 0.001) across ancestries. SCZ-PRS was associated with lower cognition across ancestries (  = -0.43, FDR-  = 0.02), higher CBCL total problems, anxious/depressed, rule-breaking and aggressive behaviors in European youth ( range = 0.16-0.33, FDR-  < 0.04), and depressive disorders in Admixed American youth (OR = 1.37, FDR-  = 0.02). Results remained consistent when SCZ-PRS and SCZ-FH were jointly modeled. Some SCZ-FH associations weakened when income-to-needs was accounted for, suggesting that SCZ-FH may capture both genetic and environmental influences. SCZ-FH showed associations with broad psychopathology, while SCZ-PRS was associated with cognition and specific symptoms in European youth. Findings highlight their complementary role in SCZ risk assessment and the need to improve PRS utility across ancestries.

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.