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Neuromorphic electronic engineering takes its inspiration from the functioning of nervous systems to build more power efficient electronic sensors and processors. Event-based neuromorphic systems are inspired by the brain's efficient data-driven communication design, which is key to its quick responses and remarkable capabilities.

Brain development is an extraordinarily complex process achieved through the spatially and temporally regulated release of key patterning factors. In vitro neurodevelopmental models seek to mimic these processes to recapitulate the steps of tissue fate acquisition and morphogenesis. Classic two-dimensional neural cultures present higher homogeneity but lower complexity compared to the brain. Brain organoids instead have more advanced cell composition, maturation and tissue architecture. They can thus be considered at the interface of in vitro and in vivo neurobiology, and further improvements in organoid techniques are continuing to narrow the gap with in vivo brain development. Here we describe these efforts to recapitulate brain development in neural organoids and focus on their applicability for disease modeling, evolutionary studies and neural network research.Chiaradia and Lancaster review applications and limitations of brain organoids, placing them in context with other technologies and describing how these methods are heavily informed by in vivo development.

Key Points When applying high-throughput molecular methods to the study of neurodevelopmental disorders, major challenges include the spatial and temporal heterogeneity of the brain, a lack of appropriate tissue available for studies and poorly defined phenotypes. Transcriptomics assays are currently the most widely used functional genomic assays in neurobiology owing to their ability to efficiently capture tissue-specific spatial and temporal heterogeneity in a high-throughput manner. Principles from transcriptomic studies will aid in evaluating additional molecular and cellular levels of regulation. We review the principles of network analysis and describe how gene networks provide a framework to organize, integrate and analyse large-scale genomic data sets in neurobiology. We review representative differential expression and gene network studies in neurodevelopmental disorders and neurodegenerative diseases and identify some next steps in data generation and integration that are necessary for progress in the field. We provide guidelines for designing, analysing and evaluating high-throughput transcriptomic studies in the brain in order to improve study quality and reproducibility. The study of the genetic basis of neurodevelopmental disorders and neurodegenerative diseases has progressed through recent large-scale association studies as well as the application of a range of high-throughput molecular methods. In this Review, the authors examine systems biology approaches and demonstrate how gene networks provide an organizing framework to integrate the analysis of large-scale genetic and molecular profiling data sets to characterize the genetic basis of phenotypes that affect the central nervous system. Genetic and genomic approaches have implicated hundreds of genetic loci in neurodevelopmental disorders and neurodegeneration, but mechanistic understanding continues to lag behind the pace of gene discovery. Understanding the role of specific genetic variants in the brain involves dissecting a functional hierarchy that encompasses molecular pathways, diverse cell types, neural circuits and, ultimately, cognition and behaviour. With a focus on transcriptomics, this Review discusses how high-throughput molecular, integrative and network approaches inform disease biology by placing human genetics in a molecular systems and neurobiological context. We provide a framework for interpreting network biology studies and leveraging big genomics data sets in neurobiology.

Key Points The neurobiology of depression features dichotomous alterations in corticolimbic brain regions. For example, the prefrontal cortex and hippocampus exhibit neuronal atrophy and synaptic dysfunction, whereas the nucleus accumbens and amygdala exhibit neuronal hypertrophy and increased synaptic activity. In subsets of depressed individuals, there is dysregulation of peripheral and central immune systems that are implicated in the neurobiology of depression. Rodents exposed to environmental and psychosocial stress recapitulate immune dysfunction observed in clinical populations. Microglia, the brain-resident macrophages, integrate neuroimmune signals and mediate neuroplasticity in physiological and pathological conditions. Neurons provide soluble and contact-dependent signals that modulate the function and activation of microglia. Typical antidepressant agents improve mood by regulating the levels of the monoamines serotonin and noradrenaline, but also partially through attenuation of immune dysregulation. Other antidepressant therapies that limit neuroimmune activation and promote anti-inflammatory pathways may provide alternative treatment options for subsets of depressed individuals. Further studies of the dynamic role of microglia in the neurobiology of depression and synapse function may reveal novel molecular pathways that can be therapeutically targeted. Central and peripheral inflammation can be induced by psychological stress and is associated with depressive symptoms, suggesting a possible role for immune dysfunction in depression. Duman and colleagues examine the neuroimmune mechanisms influencing neuronal–microglial interactions, neuronal activity and synaptic plasticity in stress and depression. Data from clinical and preclinical studies indicate that immune dysregulation, specifically of inflammatory processes, is associated with symptoms of major depressive disorder (MDD). In particular, increased levels of circulating pro-inflammatory cytokines and concomitant activation of brain-resident microglia can lead to depressive behavioural symptoms. Repeated exposure to psychological stress has a profound impact on peripheral immune responses and perturbs the function of brain microglia, which may contribute to neurobiological changes underlying MDD. Here, we review these findings and discuss ongoing studies examining neuroimmune mechanisms that influence neuronal activity as well as synaptic plasticity. Interventions targeting immune-related cellular and molecular pathways may benefit subsets of MDD patients with immune dysregulation.

Background Childhood maltreatment has been associated with significant impairment in social, emotional and behavioural functioning later in life. Nevertheless, some individuals who have experienced childhood maltreatment function better than expected given their circumstances. Main body Here, we provide an integrated understanding of the complex, interrelated mechanisms that facilitate such individual resilient functioning after childhood maltreatment. We aim to show that resilient functioning is not facilitated by any single ‘resilience biomarker’. Rather, resilient functioning after childhood maltreatment is a product of complex processes and influences across multiple levels, ranging from ‘bottom-up’ polygenetic influences, to ‘top-down’ supportive social influences. We highlight the complex nature of resilient functioning and suggest how future studies could embrace a complexity theory approach and investigate multiple levels of biological organisation and their temporal dynamics in a longitudinal or prospective manner. This would involve using methods and tools that allow the characterisation of resilient functioning trajectories, attractor states and multidimensional/multilevel assessments of functioning. Such an approach necessitates large, longitudinal studies on the neurobiological mechanisms of resilient functioning after childhood maltreatment that cut across and integrate multiple levels of explanation (i.e. genetics, endocrine and immune systems, brain structure and function, cognition and environmental factors) and their temporal interconnections. Conclusion We conclude that a turn towards complexity is likely to foster collaboration and integration across fields. It is a promising avenue which may guide future studies aimed to promote resilience in those who have experienced childhood maltreatment.

This report coordinates assessments of five types of behavioral responses in new mothers to their own infants’ cries with neurobiological responses in new mothers to their own infants’ cries and in experienced mothers and inexperienced nonmothers to infant cries and other emotional and control sounds. We found that 684 new primipara mothers in 11 countries (Argentina, Belgium, Brazil, Cameroon, France, Kenya, Israel, Italy, Japan, South Korea, and the United States) preferentially responded to their infants’ vocalizing distress by picking up and holding and by talking to their infants, as opposed to displaying affection, distracting, or nurturing. Complementary functional magnetic resonance imaging (fMRI) analyses of brain responses to their own infants’ cries in 43 new primipara US mothers revealed enhanced activity in concordant brain territories linked to the intention to move and to speak, to process auditory stimulation, and to caregive [supplementary motor area (SMA), inferior frontal regions, superior temporal regions, midbrain, and striatum]. Further, fMRI brain responses to infant cries in 50 Chinese and Italian mothers replicated, extended, and, through parcellation, refined the results. Brains of inexperienced nonmothers activated differently. Culturally common responses to own infant cry coupled with corresponding fMRI findings to own infant and to generic infant cries identified specific, common, and automatic caregiving reactions in mothers to infant vocal expressions of distress and point to their putative neurobiological bases. Candidate behaviors embedded in the nervous systems of human caregivers lie at the intersection of evolutionary biology and developmental cultural psychology.

Alternatives to traditional categorical diagnoses have been proposed to improve the validity and utility of psychiatric nosology. This paper continues the companion review of an alternative model, the psychosis superspectrum of the Hierarchical Taxonomy of Psychopathology (HiTOP). The superspectrum model aims to describe psychosis-related psychopathology according to data on distributions and associations among signs and symptoms. The superspectrum includes psychoticism and detachment spectra as well as narrow subdimensions within them. Auxiliary domains of cognitive deficit and functional impairment complete the psychopathology profile. The current paper reviews evidence on this model from neurobiology, treatment response, clinical utility, and measure development. Neurobiology research suggests that psychopathology included in the superspectrum shows similar patterns of neural alterations. Treatment response often mirrors the hierarchy of the superspectrum with some treatments being efficacious for psychoticism, others for detachment, and others for a specific subdimension. Compared to traditional diagnostic systems, the quantitative nosology shows an approximately 2-fold increase in reliability, explanatory power, and prognostic accuracy. Clinicians consistently report that the quantitative nosology has more utility than traditional diagnoses, but studies of patients with frank psychosis are currently lacking. Validated measures are available to implement the superspectrum model in practice. The dimensional conceptualization of psychosis-related psychopathology has implications for research, clinical practice, and public health programs. For example, it encourages use of the cohort study design (rather than case-control), transdiagnostic treatment strategies, and selective prevention based on subclinical symptoms. These approaches are already used in the field, and the superspectrum provides further impetus and guidance for their implementation. Existing knowledge on this model is substantial, but significant gaps remain. We identify outstanding questions and propose testable hypotheses to guide further research. Overall, we predict that the more informative, reliable, and valid characterization of psychopathology offered by the superspectrum model will facilitate progress in research and clinical care.