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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.

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

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.

Despite the importance of the brain's neocortex, we still do not completely understand the diversity and functional connections of its cell types. Jiang et al. recorded, labeled, and classified over 1200 interneurons and more than 400 pyramidal neurons in the mature mouse visual cortex. Fifteen major classes of interneurons fell into three types: some connect to all neurons, some connect to other interneurons, and some form synapses with pyramidal neurons. Science , this issue p. 10.1126/science.aac9462 The connections between more than 10,000 pairs of individually classified neurons in the visual cortex of adult mice are mapped. Since the work of Ramón y Cajal in the late 19th and early 20th centuries, neuroscientists have speculated that a complete understanding of neuronal cell types and their connections is key to explaining complex brain functions. However, a complete census of the constituent cell types and their wiring diagram in mature neocortex remains elusive. By combining octuple whole-cell recordings with an optimized avidin-biotin-peroxidase staining technique, we carried out a morphological and electrophysiological census of neuronal types in layers 1, 2/3, and 5 of mature neocortex and mapped the connectivity between more than 11,000 pairs of identified neurons. We categorized 15 types of interneurons, and each exhibited a characteristic pattern of connectivity with other interneuron types and pyramidal cells. The essential connectivity structure of the neocortical microcircuit could be captured by only a few connectivity motifs.

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.

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.

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.

Two major classes of inhibitory neurons in mouse anterior cingulate cortex, somatostatin and parvalbumin interneurons, form functionally homogeneous populations that are recruited at distinct moments in time and encode unique behavioral variables in a foraging task. Neuronal diversity in the cerebral cortex The cerebral cortex contains many different classes of inhibitory interneurons, each with different anatomical and physiological properties. Recent technological developments make it possible to determine the functional impact of individual classes. This optogenetic tagging study of mice performing a reward foraging task shows that parvalbumin- and somatostatin-expressing cells, two of largest interneuron populations, respond differently during different phases of the task. These findings suggest a link between circuit-level activity of the different interneuron types in regulating the flow of information flow and the behavioural functions served by the cortical circuits. Neurons in the prefrontal cortex exhibit diverse behavioural correlates 1 , 2 , 3 , 4 , an observation that has been attributed to cell-type diversity. To link identified neuron types with network and behavioural functions, we recorded from the two largest genetically defined inhibitory interneuron classes, the perisomatically targeting parvalbumin (PV) and the dendritically targeting somatostatin (SOM) neurons 5 , 6 , 7 , 8 in anterior cingulate cortex of mice performing a reward foraging task. Here we show that PV and a subtype of SOM neurons form functionally homogeneous populations showing a double dissociation between both their inhibitory effects and behavioural correlates. Out of several events pertaining to behaviour, a subtype of SOM neurons selectively responded at reward approach, whereas PV neurons responded at reward leaving and encoded preceding stay duration. These behavioural correlates of PV and SOM neurons defined a behavioural epoch and a decision variable important for foraging (whether to stay or to leave), a crucial function attributed to the anterior cingulate cortex 9 , 10 , 11 . Furthermore, PV neurons could fire in millisecond synchrony, exerting fast and powerful inhibition on principal cell firing, whereas the inhibitory effect of SOM neurons on firing output was weak and more variable, consistent with the idea that they respectively control the outputs of, and inputs to, principal neurons 12 , 13 , 14 , 15 , 16 . These results suggest a connection between the circuit-level function of different interneuron types in regulating the flow of information and the behavioural functions served by the cortical circuits. Moreover, these observations bolster the hope that functional response diversity during behaviour can in part be explained by cell-type diversity.

Deciphering the striatal interneuron diversity is key to understanding the basal ganglia circuit and to untangling the complex neurological and psychiatric diseases affecting this brain structure. We performed snRNA-seq and spatial transcriptomics of postmortem human caudate nucleus and putamen samples to elucidate the diversity and abundance of interneuron populations and their inherent transcriptional structure in the human dorsal striatum. We propose a comprehensive taxonomy of striatal interneurons with eight main classes and fourteen subclasses, providing their full transcriptomic identity and spatial expression profile as well as additional quantitative FISH validation for specific populations. We have also delineated the correspondence of our taxonomy with previous standardized classifications and shown the main transcriptomic and class abundance differences between caudate nucleus and putamen. Notably, based on key functional genes such as ion channels and synaptic receptors, we found matching known mouse interneuron populations for the most abundant populations, the recently described PTHLH and TAC3 interneurons. Finally, we were able to integrate other published datasets with ours, supporting the generalizability of this harmonized taxonomy. Striatal interneuron diversity within the basal ganglia of human and non-human primates is not well understood. Here, authors reveal the diversity of interneurons in the human dorsal striatum based on the single-cell transcriptome, delineating unknown types and regional differences, and tracing parallels with those in mice.

Severe infections during pregnancy are one of the major risk factors for cognitive impairment in the offspring. It has been suggested that maternal inflammation leads to dysfunction of cortical GABAergic interneurons that in turn underlies cognitive impairment of the affected offspring. However, the evidence comes largely from studies of adult or mature brains and how the impairment of inhibitory circuits arises upon maternal inflammation is unknown. Here we show that maternal inflammation affects multiple steps of cortical GABAergic interneuron development, i.e., proliferation of precursor cells, migration and positioning of neuroblasts, as well as neuronal maturation. Importantly, the development of distinct subtypes of cortical GABAergic interneurons was discretely impaired as a result of maternal inflammation. This translated into a reduction in cell numbers, redistribution across cortical regions and layers, and changes in morphology and cellular properties. Furthermore, selective vulnerability of GABAergic interneuron subtypes was associated with the stage of brain development. Thus, we propose that maternally derived insults have developmental stage-dependent effects, which contribute to the complex etiology of cognitive impairment in the affected offspring.