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The cerebellar cortex is a well-studied brain structure with diverse roles in motor learning, coordination, cognition and autonomic regulation. However,  a complete inventory of cerebellar cell types is currently lacking. Here, using recent advances in high-throughput transcriptional profiling 1 – 3 , we molecularly define cell types across individual lobules of the adult mouse cerebellum. Purkinje neurons showed considerable regional specialization, with the greatest diversity occurring in the posterior lobules. For several types of cerebellar interneuron, the molecular variation within each type was more continuous, rather than discrete. In particular, for the unipolar brush cells—an interneuron population previously subdivided into discrete populations—the continuous variation in gene expression was associated with a graded continuum of electrophysiological properties. Notably, we found that molecular layer interneurons were composed of two molecularly and functionally distinct types. Both types show a continuum of morphological variation through the thickness of the molecular layer, but electrophysiological recordings revealed marked differences between the two types in spontaneous firing, excitability and electrical coupling. Together, these findings provide a comprehensive cellular atlas of the cerebellar cortex, and outline a methodological and conceptual framework for the integration of molecular, morphological and physiological ontologies for defining brain cell types. A comprehensive atlas of cell types and regional specializations in the mouse cerebellar cortex.

Understanding brain circuits begins with an appreciation of their component parts — the cells. Although GABAergic interneurons are a minority population within the brain, they are crucial for the control of inhibition. Determining the diversity of these interneurons has been a central goal of neurobiologists, but this amazing cell type has so far defied a generalized classification system. Interneuron complexity within the telencephalon could be simplified by viewing them as elaborations of a much more finite group of developmentally specified cardinal classes that become further specialized as they mature. Our perspective emphasizes that the ultimate goal is to dispense with classification criteria and directly define interneuron types by function.

Alzheimer’s disease is the leading cause of dementia worldwide, but the cellular pathways that underlie its pathological progression across brain regions remain poorly understood 1 – 3 . Here we report a single-cell transcriptomic atlas of six different brain regions in the aged human brain, covering 1.3 million cells from 283 post-mortem human brain samples across 48 individuals with and without Alzheimer’s disease. We identify 76 cell types, including region-specific subtypes of astrocytes and excitatory neurons and an inhibitory interneuron population unique to the thalamus and distinct from canonical inhibitory subclasses. We identify vulnerable populations of excitatory and inhibitory neurons that are depleted in specific brain regions in Alzheimer’s disease, and provide evidence that the Reelin signalling pathway is involved in modulating the vulnerability of these neurons. We develop a scalable method for discovering gene modules, which we use to identify cell-type-specific and region-specific modules that are altered in Alzheimer’s disease and to annotate transcriptomic differences associated with diverse pathological variables. We identify an astrocyte program that is associated with cognitive resilience to Alzheimer’s disease pathology, tying choline metabolism and polyamine biosynthesis in astrocytes to preserved cognitive function late in life. Together, our study develops a regional atlas of the ageing human brain and provides insights into cellular vulnerability, response and resilience to Alzheimer’s disease pathology. A regional atlas of the ageing human brain—spanning six distinct anatomical regions from individuals with and without Alzheimer’s dementia—provides insights into cellular vulnerability, response and resilience to Alzheimer’s disease pathology

Key Points A feature-based classification and agreed-upon nomenclature of GABAergic interneurons of the cerebral cortex is much needed but currently lacking. We designed a web-based interactive system that allowed 42 neuroscience experts to classify a representative sample of 320 cortical neurons and a selected set of simple morphology features based on reconstructions of their axonal arbors. The consensus on and usefulness of these features and neuron names were investigated using agreement analysis, clustering algorithms, Bayesian networks and supervised classification on the resulting data. The results quantitatively confirm the impression that different investigators use their own, mutually inconsistent classification schemes based on morphological criteria. However, the analyses also demonstrate that the community may be reaching consensus for a practical approach to the naming of certain anatomical terms that are useful for neuronal characterization and classification. State-of-the-art machine learning approaches were shown to achieve discrimination capability equivalent to or better than human performance, opening the possibility of creating an objective computer tool for automatic classification of neurons, a Neuroclassifier. The classification of cortical neurons, including interneurons, remains a thorny issue in neuroscience. This Analysis article presents and tests a possible taxonomical solution for classifying cortical GABAergic interneurons based on a web-based interactive system that allows experts to classify neurons with pre-determined morphological criteria. A systematic classification and accepted nomenclature of neuron types is much needed but is currently lacking. This article describes a possible taxonomical solution for classifying GABAergic interneurons of the cerebral cortex based on a novel, web-based interactive system that allows experts to classify neurons with pre-determined criteria. Using Bayesian analysis and clustering algorithms on the resulting data, we investigated the suitability of several anatomical terms and neuron names for cortical GABAergic interneurons. Moreover, we show that supervised classification models could automatically categorize interneurons in agreement with experts' assignments. These results demonstrate a practical and objective approach to the naming, characterization and classification of neurons based on community consensus.

Using a combination of optogenetics, single-cell molecular profiling and paired electrophysiological recordings in the mouse visual cortex, Pfeffer and colleagues derived the connectivity matrix of three major classes of interneurons with their post-synaptic GABAergic targets. This study provides a comprehensive overview of the wiring rules of the inhibition of inhibition in the cortex. Cortical inhibitory neurons contact each other to form a network of inhibitory synaptic connections. Our knowledge of the connectivity pattern underlying this inhibitory network is, however, still incomplete. Here we describe a simple and complementary interaction scheme between three large, molecularly distinct interneuron populations in mouse visual cortex: parvalbumin-expressing interneurons strongly inhibit one another but provide little inhibition to other populations. In contrast, somatostatin-expressing interneurons avoid inhibiting one another yet strongly inhibit all other populations. Finally, vasoactive intestinal peptide–expressing interneurons preferentially inhibit somatostatin-expressing interneurons. This scheme occurs in supragranular and infragranular layers, suggesting that inhibitory networks operate similarly at the input and output of the visual cortex. Thus, as the specificity of connections between excitatory neurons forms the basis for the cortical canonical circuit, the scheme described here outlines a standard connectivity pattern among cortical inhibitory neurons.

The assembly of cortical circuits involves the generation and migration of interneurons from the ventral to the dorsal forebrain 1 , 2 – 3 , which has been challenging to study at inaccessible stages of late gestation and early postnatal human development 4 . Autism spectrum disorder and other neurodevelopmental disorders (NDDs) have been associated with abnormal cortical interneuron development 5 , but which of these NDD genes affect interneuron generation and migration, and how they mediate these effects remains unknown. We previously developed a platform to study interneuron development and migration in subpallial organoids and forebrain assembloids 6 . Here we integrate assembloids with CRISPR screening to investigate the involvement of 425 NDD genes in human interneuron development. The first screen aimed at interneuron generation revealed 13 candidate genes, including CSDE1 and SMAD4 . We subsequently conducted an interneuron migration screen in more than 1,000 forebrain assembloids that identified 33 candidate genes, including cytoskeleton-related genes and the endoplasmic reticulum-related gene LNPK . We discovered that, during interneuron migration, the endoplasmic reticulum is displaced along the leading neuronal branch before nuclear translocation. LNPK deletion interfered with this endoplasmic reticulum displacement and resulted in abnormal migration. These results highlight the power of this CRISPR-assembloid platform to systematically map NDD genes onto human development and reveal disease mechanisms. Assembloids are integrated with CRISPR screening to investigate the involvement of 425 neurodevelopmental disorder genes in human interneuron development, showing endoplasmic reticulum displacement before nuclear translocation and interference from LNPK deletion, resulting in abnormal migration.

The adult brain contains dozens of different types of interneurons that control and refine neuronal circuits. Mi et al. used single-cell transcriptomics to investigate when these subtypes emerge during interneuron development in the mouse. Transcriptomes of embryonic interneurons showed similarities to adult classes of differentiated interneurons, thus dividing the immature embryonic interneurons themselves into classes. Nearly a dozen classes of embryonic neurons could be identified soon after their last mitosis by transcriptomic similarity with known classes of adult cortical interneurons. Thus, the fate of embryonic interneurons can be read in their transcriptomes well before the neurons migrate and reach their final sites of differentiation and circuit integration. Science , this issue p. 81 Single-cell transcriptomics reveals embryonic correlates of adult interneuron classes. GABAergic interneurons (GABA, γ-aminobutyric acid) regulate neural-circuit activity in the mammalian cerebral cortex. These cortical interneurons are structurally and functionally diverse. Here, we use single-cell transcriptomics to study the origins of this diversity in the mouse. We identify distinct types of progenitor cells and newborn neurons in the ganglionic eminences, the embryonic proliferative regions that give rise to cortical interneurons. These embryonic precursors show temporally and spatially restricted transcriptional patterns that lead to different classes of interneurons in the adult cerebral cortex. Our findings suggest that shortly after the interneurons become postmitotic, their diversity is already patent in their diverse transcriptional programs, which subsequently guide further differentiation in the developing cortex.

Embryonic DNA damage resulting from DNA repair deficiencies or exposure to ionizing radiation during early neurogenesis can lead to neurodevelopmental disorders, including microcephaly. This has been linked to an excessive DNA damage response in dorsal neural progenitor cells (NPCs), resulting in p53-dependent apoptosis and premature neuronal differentiation which culminates in depletion of the NPC pool. However, the effect of DNA damage on ventral forebrain NPCs, the origin of interneurons, remains unclear. In this study, we investigated the sequelae of irradiation of mouse fetuses at an early timepoint of forebrain neurogenesis. We focused on the neocortex (NCX) and medial ganglionic eminence (MGE), key regions for developing dorsal and ventral NPCs, respectively. Although both regions showed a typical p53-mediated DNA damage response consisting of cell cycle arrest, DNA repair and apoptosis, NCX cells displayed prolonged cell cycle arrest, while MGE cells exhibited more sustained apoptosis. Moreover, irradiation reduced the migration speed of interneurons in acute living brain slices and MGE explants, the latter indicating a cell-intrinsic component in the defect. RNA sequencing and protein analyses revealed disruptions in actin and microtubule cytoskeletal-related cellular machinery, particularly in MGE cells. Despite massive acute apoptosis and an obvious interneuron migration defect, prenatally irradiated animals did not show increased sensitivity to pentylenetetrazole-induced seizures, nor was there a reduction in cortical interneurons in young adult mice. This suggests a high plasticity of the developing brain to acute insults during early neurogenesis. Overall, our findings indicate that embryonic DNA damage induces region-specific responses, potentially linked to neurodevelopmental disorders.

Major depressive disorder emerges from the complex interactions of biological systems that span genes and molecules through cells, networks, and behavior. Establishing how neurobiological processes coalesce to contribute to depression requires a multiscale approach, encompassing measures of brain structure and function as well as genetic and cell-specific transcriptional data. Here, we examine anatomical (cortical thickness) and functional (functional variability, global brain connectivity) correlates of depression and negative affect across three population-imaging datasets: UK Biobank, Brain Genomics Superstruct Project, and Enhancing Neuro- Imaging through Meta Analysis (ENIGMA; combined n ≥ 23,723). Integrative analyses incorporate measures of cortical gene expression, postmortem patient transcriptional data, depression genome-wide association study (GWAS), and single-cell gene transcription. Neuroimaging correlates of depression and negative affect were consistent across three independent datasets. Linking ex vivo gene down-regulation with in vivo neuroimaging, we find that transcriptional correlates of depression imaging phenotypes track gene down-regulation in postmortem cortical samples of patients with depression. Integrated analysis of single-cell and Allen Human Brain Atlas expression data reveal somatostatin interneurons and astrocytes to be consistent cell associates of depression, through both in vivo imaging and ex vivo cortical gene dysregulation. Providing converging evidence for these observations, GWAS-derived polygenic risk for depression was enriched for genes expressed in interneurons, but not glia. Underscoring the translational potential of multiscale approaches, the transcriptional correlates of depression-linked brain function and structure were enriched for disorder-relevant molecular pathways. These findings bridge levels to connect specific genes, cell classes, and biological pathways to in vivo imaging correlates of depression.

In vertebrates, motor control relies on cholinergic neurons in the spinal cord that have been extensively studied over the past hundred years, yet the full heterogeneity of these neurons and their different functional roles in the adult remain to be defined. Here, we develop a targeted single nuclear RNA sequencing approach and use it to identify an array of cholinergic interneurons, visceral and skeletal motor neurons. Our data expose markers for distinguishing these classes of cholinergic neurons and their rich diversity. Specifically, visceral motor neurons, which provide autonomic control, can be divided into more than a dozen transcriptomic classes with anatomically restricted localization along the spinal cord. The complexity of the skeletal motor neurons is also reflected in our analysis with alpha, gamma, and a third subtype, possibly corresponding to the elusive beta motor neurons, clearly distinguished. In combination, our data provide a comprehensive transcriptomic description of this important population of neurons that control many aspects of physiology and movement and encompass the cellular substrates for debilitating degenerative disorders. The full heterogeneity and different functional roles of cholinergic neurons in the adult spinal cord remain to be defined. Here the authors develop a targeted single nuclear RNA sequencing approach and use it to identify an array of cholinergic interneurons, as well as visceral and skeletal motor neurons.