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22q11.2 deletion syndrome (22q11DS) is a highly penetrant and common genetic cause of neuropsychiatric disease. Here we generated induced pluripotent stem cells from 15 individuals with 22q11DS and 15 control individuals and differentiated them into three-dimensional (3D) cerebral cortical organoids. Transcriptional profiling across 100 days showed high reliability of differentiation and revealed changes in neuronal excitability-related genes. Using electrophysiology and live imaging, we identified defects in spontaneous neuronal activity and calcium signaling in both organoid- and 2D-derived cortical neurons. The calcium deficit was related to resting membrane potential changes that led to abnormal inactivation of voltage-gated calcium channels. Heterozygous loss of DGCR8 recapitulated the excitability and calcium phenotypes and its overexpression rescued these defects. Moreover, the 22q11DS calcium abnormality could also be restored by application of antipsychotics. Taken together, our study illustrates how stem cell derived models can be used to uncover and rescue cellular phenotypes associated with genetic forms of neuropsychiatric disease. A human stem cell–derived model helps to uncover neuronal phenotypes associated with genetic forms of neuropsychiatric disease.

Human brain functional networks are embedded in anatomical space and have topological properties—small-worldness, modularity, fat-tailed degree distributions—that are comparable to many other complex networks. Although a sophisticated set of measures is available to describe the topology of brain networks, the selection pressures that drive their formation remain largely unknown. Here we consider generative models for the probability of a functional connection (an edge) between two cortical regions (nodes) separated by some Euclidean distance in anatomical space. In particular, we propose a model in which the embedded topology of brain networks emerges from two competing factors: a distance penalty based on the cost of maintaining long-range connections; and a topological term that favors links between regions sharing similar input. We show that, together, these two biologically plausible factors are sufficient to capture an impressive range of topological properties of functional brain networks. Model parameters estimated in one set of functional MRI (fMRI) data on normal volunteers provided a good fit to networks estimated in a second independent sample of fMRI data. Furthermore, slightly detuned model parameters also generated a reasonable simulation of the abnormal properties of brain functional networks in people with schizophrenia. We therefore anticipate that many aspects of brain network organization, in health and disease, may be parsimoniously explained by an economical clustering rule for the probability of functional connectivity between different brain areas.

We generated cortical interneurons (cINs) from induced pluripotent stem cells derived from 14 healthy controls and 14 subjects with schizophrenia. Both healthy control cINs and schizophrenia cINs were authentic, fired spontaneously, received functional excitatory inputs from host neurons, and induced GABA-mediated inhibition in host neurons in vivo. However, schizophrenia cINs had dysregulated expression of protocadherin genes, which lie within documented schizophrenia loci. Mice lacking protocadherin-α showed defective arborization and synaptic density of prefrontal cortex cINs and behavioral abnormalities. Schizophrenia cINs similarly showed defects in synaptic density and arborization that were reversed by inhibitors of protein kinase C, a downstream kinase in the protocadherin pathway. These findings reveal an intrinsic abnormality in schizophrenia cINs in the absence of any circuit-driven pathology. They also demonstrate the utility of homogenous and functional populations of a relevant neuronal subtype for probing pathogenesis mechanisms during development.Shao et al. report that interneurons derived from iPSCs from schizophrenia patients have altered protocadherin expression and synaptic and arborization deficits. A PKC inhibitor, acting downstream of protocadherin, reversed the arborization deficit.

Humans have systematic sex differences in brain-related behavior, cognition, and pattern of mental illness risk. Many of these differences emerge during adolescence, a developmental period of intense neurostructural and endocrine change. Here, by creating \"movies\" of sexually dimorphic brain development using longitudinal in vivo structural neuroimaging, we show regionally specific sex differences in development of the cerebral cortex during adolescence. Within cortical subsystems known to underpin domains of cognitive behavioral sex difference, structural change is faster in the sex that tends to perform less well within the domain in question. By stratifying participants through molecular analysis of the androgen receptor gene, we show that possession of an allele conferring more efficient functioning of this sex steroid receptor is associated with \"masculinization\" of adolescent cortical maturation. Our findings extend models first established in rodents, and suggest that in humans too, sex and sex steroids shape brain development in a spatiotemporally specific manner, within neural systems known to underpin sexually dimorphic behaviors.

Schizophrenia is a devastating neurodevelopmental disorder whose genetic influences remain elusive. We hypothesize that individually rare structural variants contribute to the illness. Microdeletions and microduplications >100 kilobases were identified by microarray comparative genomic hybridization of genomic DNA from 150 individuals with schizophrenia and 268 ancestry-matched controls. All variants were validated by high-resolution platforms. Novel deletions and duplications of genes were present in 5% of controls versus 15% of cases and 20% of young-onset cases, both highly significant differences. The association was independently replicated in patients with childhood-onset schizophrenia as compared with their parents. Mutations in cases disrupted genes disproportionately from signaling networks controlling neurodevelopment, including neuregulin and glutamate pathways. These results suggest that multiple, individually rare mutations altering genes in neurodevelopmental pathways contribute to schizophrenia.

Alleles of the apolipoprotein E (APOE) gene modulate risk for Alzheimer's disease, with carriers of the ɛ4 allele being at increased risk and carriers of the ɛ2 allele possibly at decreased risk compared with non-carriers. Our aim was to determine whether possession of an ɛ4 allele would confer children with a neural substrate that might render them at risk for Alzheimer's disease, and whether carriers of the ɛ2 allele might have a so-called protective cortical morphology. 239 healthy children and adolescents were genotyped and had repeated neuroanatomic MRI (total 530 scans). Mixed model regression was used to determine whether the developmental trajectory of the cortex differed by genotype. Cortical thickness of the left entorhinal region was significantly thinner in ɛ4 carriers than it was in non-ɛ4 carriers (3·79 [SE 0·06] mm, range 1·54–5·24 vs 3·94 [0·03] mm, 2·37–6·11; p=0·03). There was a significant stepwise increase in cortical thickness in the left entorhinal regions, with ɛ4 carriers having the thinnest cortex and ɛ2 carriers the thickest, with ɛ3 homozygotes occupying an intermediate position (left β 0·11 [SE 0·05], p=0·02). Neuroanatomic effects seemed fixed and non-progressive, with no evidence of accelerated cortical loss in young healthy ɛ4 carriers. Alleles of the apolipoprotein E gene have distinct neuroanatomic signatures, identifiable in childhood. The thinner entorhinal cortex in individuals with the ɛ4 allele might contribute to risk of Alzheimer's disease.

We report the dynamic anatomical sequence of human cortical gray matter development between the age of 4-21 years using quantitative four-dimensional maps and time-lapse sequences. Thirteen healthy children for whom anatomic brain MRI scans were obtained every 2 years, for 8-10 years, were studied. By using models of the cortical surface and sulcal landmarks and a statistical model for gray matter density, human cortical development could be visualized across the age range in a spatiotemporally detailed time-lapse sequence. The resulting time-lapse \"movies\" reveal that (i) higher-order association cortices mature only after lower-order somatosensory and visual cortices, the functions of which they integrate, are developed, and (ii) phylogenetically older brain areas mature earlier than newer ones. Direct comparison with normal cortical development may help understanding of some neurodevelopmental disorders such as childhood-onset schizophrenia or autism.

Noninvasive brain imaging permits longitudinal studies of anatomic brain development in healthy and psychiatrically ill children. The time course for gray matter maturation varies by region and parallels earlier histological studies, indicating dynamic patterns of overproduction and regression. Developmental trajectories vary in relation to gender, intelligence, and overall functioning. Twin studies show high heritability for brain volumes, which varies with region and with age. Diagnostically specific, illness-related changes as well as outcome-associated plastic response are observed as illustrated for two pediatric populations, childhood-onset schizophrenia and attention-deficit/hyperactivity disorder, conditions which may be, in part, disorders of brain plasticity.

The advent of magnetic resonance imaging, which safely allows in vivo quantification of anatomical and physiological features of the brain, has revolutionized pediatric neuroscience. Longitudinal studies are useful for the characterization of developmental trajectories (ie, changes in imaging measures by age). Developmental trajectories (as opposed to static measures) have proven to have greater power in discriminating healthy from clinical groups and in predicting cognitive/behavioral measures, such as IQ. Here we summarize results from an ongoing longitudinal pediatric neuroimaging study that has been conducted at the Child Psychiatry Branch of the National Institute of Mental Health since 1989. Developmental trajectories of structural MRI brain measures from healthy youth are compared and contrasted with trajectories in attention-deficit/hyperactivity disorder (ADHD) and childhood-onset schizophrenia. Across ages 5-25 years, in both healthy and clinical populations, white matter volumes increase and gray matter volumes follow an inverted U trajectory, with peak size occurring at different times in different regions. At a group level, differences related to psychopathology are seen for gray and white matter volumes, rates of change, and for interconnectedness among disparate brain regions.

IntroductionArtificial intelligence and computer vision are revolutionizing the way we perceive video analysis in minimally invasive surgery. This emerging technology has increasingly been leveraged successfully for video segmentation, documentation, education, and formative assessment. New, sophisticated platforms allow pre-determined segments chosen by surgeons to be automatically presented without the need to review entire videos. This study aimed to validate and demonstrate the accuracy of the first reported AI-based computer vision algorithm that automatically recognizes surgical steps in videos of totally extraperitoneal (TEP) inguinal hernia repair.MethodsVideos of TEP procedures were manually labeled by a team of annotators trained to identify and label surgical workflow according to six major steps. For bilateral hernias, an additional change of focus step was also included. The videos were then used to train a computer vision AI algorithm. Performance accuracy was assessed in comparison to the manual annotations.ResultsA total of 619 full-length TEP videos were analyzed: 371 were used to train the model, 93 for internal validation, and the remaining 155 as a test set to evaluate algorithm accuracy. The overall accuracy for the complete procedure was 88.8%. Per-step accuracy reached the highest value for the hernia sac reduction step (94.3%) and the lowest for the preperitoneal dissection step (72.2%).ConclusionsThese results indicate that the novel AI model was able to provide fully automated video analysis with a high accuracy level. High-accuracy models leveraging AI to enable automation of surgical video analysis allow us to identify and monitor surgical performance, providing mathematical metrics that can be stored, evaluated, and compared. As such, the proposed model is capable of enabling data-driven insights to improve surgical quality and demonstrate best practices in TEP procedures.