Continuous and Discrete Neuron Types of the Adult Murine Striatum

Spatial profiling of the interplay between cell type- and vision-dependent transcriptomic programs in the visual cortex

How early sensory experience during "critical periods" of postnatal life affects the organization of the mammalian neocortex at the resolution of neuronal cell types is poorly understood. We previously reported that the functional and molecular profiles of layer 2/3 (L2/3) cell types in the primary visual cortex (V1) are vision-dependent (Tan et al., Neuron, 108(4), 2020; Cheng et al., Cell, 185(2), 2022). Here, we characterize the spatial organization of L2/3 cell types with and without visual experience. Spatial transcriptomic profiling based on 500 genes recapitulates the zonation of L2/3 cell types along the pial-ventricular axis in V1. By applying multi-tasking theory (Adler et al., Cell Systems, 8, 2019), we suggest that the spatial zonation of L2/3 cell types is linked to the continuous nature of their gene expression profiles, which can be represented as a 2D manifold bounded by three archetypal cell types ("A", "B", and "C"). By comparing normally reared and dark reared L2/3 cells, we show that visual deprivation-induced transcriptomic changes comprise two independent gene programs. The first, induced specifically in the visual cortex, includes immediate-early genes and genes associated with metabolic processes. It manifests as a change in cell state that is orthogonal to cell type-specific gene expression programs. By contrast, the second program impacts L2/3 cell type identity, regulating a subset of cell type-specific genes and shifting the distribution of cells within the L2/3 manifold, with a depression of the B-type and C-type and a gain of the A-type. Through an integrated analysis of spatial transcriptomic measurements with single-nucleus RNA-seq data from our previous study, we describe how vision patterns L2/3 cortical cell types during the postnatal critical period.

Significance statement

Layer 2/3 (L2/3) glutamatergic neurons are important sites of experience-dependent plasticity and learning in the mammalian cortex. Their properties vary continuously with cortical depth and depend upon experience. Here, by applying spatial transcriptomics and different computational approaches in the mouse primary visual cortex, we show that vision regulates orthogonal gene expression programs underlying cell states and cell types. Visual deprivation not only induces an activity-dependent cell state, but also alters the composition of L2/3 cell types, which are appropriately described as a transcriptomic continuum. Our results provide insights into how experience shapes transcriptomes that may, in turn, sculpt brain wiring, function, and behavior.

Striatal cell-type-specific molecular signatures reveal therapeutic targets in a model of dystonia

Striatal dysfunction is implicated in many forms of dystonia, including idiopathic, inherited and iatrogenic dystonias. The striatum is comprised largely of GABAergic spiny projection neurons (SPNs) that are defined by their long-range efferents. Direct SPNs (dSPNs) project to the internal globus pallidus/substantia nigra reticulata whereas indirect pathway SPNs (iSPNs) project to the external pallidum; the concerted activity of both SPN subtypes modulates movement. Convergent results from genetic, imaging and physiological studies in patients suggest that abnormalities of both dSPNs and iSPNs contribute to the expression of dystonia, but the molecular adaptations underlying these abnormalities are not known. Here we provide a comprehensive analysis of SPN cell-type-specific molecular signatures in a model of DOPA-responsive dystonia (DRD mice), which is caused by gene defects that reduce dopamine neurotransmission, resulting in dystonia that is specifically associated with striatal dysfunction. Individually profiling the translatome of dSPNs and iSPNs using translating ribosome affinity purification with RNA-seq revealed hundreds of differentially translating mRNAs in each SPN subtype in DRD mice, yet there was little overlap between the dysregulated genes in dSPNs and iSPNs. Despite the paucity of shared adaptations, a disruption in glutamatergic signaling was predicted for both dSPNs and iSPNs. Indeed, we found that both AMPA and NMDA receptor-mediated currents were enhanced in dSPNs but diminished in iSPNs in DRD mice. The pattern of mRNA dysregulation was specific to dystonia as the adaptations in DRD mice were distinct from those in parkinsonian mice where the dopamine deficit occurs in adults, suggesting that the phenotypic outcome is dependent on both the timing of the dopaminergic deficit and the SPN-specific adaptions. We leveraged the unique molecular signatures of dSPNs and iSPNs in DRD mice to identify biochemical mechanisms that may be targets for therapeutics, including LRRK2 inhibition. Administration of the LRRK2 inhibitor MLi-2 ameliorated the dystonia in DRD mice suggesting a novel target for therapeutics and demonstrating that the delineation of cell-type-specific molecular signatures provides a powerful approach to revealing both CNS dysfunction and therapeutic targets in dystonia.

Molecular logic for cellular specializations that initiate the auditory parallel processing pathways

The cochlear nuclear complex (CN), the starting point for all central auditory processing, comprises a suite of neuronal cell types that are highly specialized for neural coding of acoustic signals, yet molecular logic governing cellular specializations remains unknown. By combining single-nucleus RNA sequencing and Patch-seq analysis, we reveal a set of transcriptionally distinct cell populations encompassing all previously observed types and discover multiple new subtypes with anatomical and physiological identity. The resulting comprehensive cell-type taxonomy reconciles anatomical position, morphological, physiological, and molecular criteria, enabling the determination of the molecular basis of the remarkable cellular phenotypes in the CN. In particular, CN cell-type identity is encoded in a transcriptional architecture that orchestrates functionally congruent expression across a small set of gene families to customize projection patterns, input-output synaptic communication, and biophysical features required for encoding distinct aspects of acoustic signals. This high-resolution account of cellular heterogeneity from the molecular to the circuit level illustrates molecular logic for cellular specializations and enables genetic dissection of auditory processing and hearing disorders with unprecedented specificity.

Joint inference of discrete cell types and continuous type-specific variability in single-cell datasets with MMIDAS

Reproducible definition and identification of cell types is essential to enable investigations into their biological function and to understand their relevance in the context of development, disease and evolution. Current approaches model variability in data as continuous latent factors, followed by clustering as a separate step, or immediately apply clustering on the data. We show that such approaches can suffer from qualitative mistakes in identifying cell types robustly, particularly when the number of such cell types is in the hundreds or even thousands. Here we propose an unsupervised method, Mixture Model Inference with Discrete-coupled AutoencoderS (MMIDAS), which combines a generalized mixture model with a multi-armed deep neural network to jointly infer the discrete type and continuous type-specific variability. Using four recent datasets of brain cells spanning different technologies, species and conditions, we demonstrate that MMIDAS can identify reproducible cell types and infer cell type-dependent continuous variability in both unimodal and multimodal datasets.

Striatal projection neurons coexpressing dopamine D1 and D2 receptors modulate the motor function of D1- and D2-SPNs

The role of the striatum in motor control is commonly assumed to be mediated by the two striatal efferent pathways characterized by striatal projection neurons (SPNs) expressing dopamine (DA) D1 receptors or D2 receptors (D1-SPNs and D2-SPNs, respectively), without regard to SPNs coexpressing both receptors (D1/D2-SPNs). Here we developed an approach to target these hybrid SPNs in mice and demonstrate that, although these SPNs are less abundant, they have a major role in guiding the motor function of the other two populations. D1/D2-SPNs project exclusively to the external globus pallidus and have specific electrophysiological features with distinctive integration of DA signals. Gain- and loss-of-function experiments indicate that D1/D2-SPNs potentiate the prokinetic and antikinetic functions of D1-SPNs and D2-SPNs, respectively, and restrain the integrated motor response to psychostimulants. Overall, our findings demonstrate the essential role of this population of D1/D2-coexpressing neurons in orchestrating the fine-tuning of DA regulation in thalamo-cortico-striatal loops.

Excessive firing of dyskinesia-associated striatal direct pathway neurons is gated by dopamine and excitatory synaptic input

The striatum integrates dopaminergic and glutamatergic inputs to select preferred versus alternative actions. However, the precise mechanisms underlying this process remain unclear. One way to study action selection is to understand how it breaks down in pathological states. Here, we explored the cellular and synaptic mechanisms of levodopa-induced dyskinesia (LID), a complication of Parkinson's disease therapy characterized by involuntary movements. We used an activity-dependent tool (FosTRAP) in conjunction with a mouse model of LID to investigate functionally distinct subsets of striatal direct pathway medium spiny neurons (dMSNs). In vivo, levodopa differentially activates dyskinesia-associated (TRAPed) dMSNs compared to other dMSNs. We found this differential activation of TRAPed dMSNs is likely to be driven by higher dopamine receptor expression, dopamine-dependent excitability, and excitatory input from the motor cortex and thalamus. Together, these findings suggest how the intrinsic and synaptic properties of heterogeneous dMSN subpopulations integrate to support action selection.

Loss of primary cilia and dopaminergic neuroprotection in pathogenic LRRK2-driven and idiopathic Parkinson's disease

Activating leucine-rich repeat kinase 2 (LRRK2) mutations cause Parkinson's and phosphorylation of Rab10 by pathogenic LRRK2 blocks primary ciliogenesis in cultured cells. In the mouse brain, LRRK2 blockade of primary cilia is highly cell type specific: For example, cholinergic interneurons and astrocytes but not medium spiny neurons of the dorsal striatum lose primary cilia in LRRK2-pathway mutant mice. We show here that the cell type specificity of LRRK2-mediated cilia loss is also seen in human postmortem striatum from patients with LRRK2 pathway mutations and idiopathic Parkinson's. Single nucleus RNA sequencing shows that cilia loss in mouse cholinergic interneurons is accompanied by decreased glial-derived neurotrophic factor transcription, decreasing neuroprotection for dopamine neurons. Nevertheless, LRRK2 expression differences cannot explain the unique vulnerability of cholinergic neurons to LRRK2 kinase as much higher LRRK2 expression is seen in medium spiny neurons that have normal cilia. In parallel with decreased striatal dopaminergic neurite density, LRRK2 G2019S neurons show increased autism-linked CNTN5 adhesion protein expression; glial cells show significant loss of ferritin heavy chain. These data strongly suggest that loss of cilia in specific striatal cell types decreases neuroprotection for dopamine neurons in mice and human Parkinson's.

Regional heterogeneity in the membrane properties of mouse striatal neurons

The cytoarchitecture of the striatum is remarkably homogeneous, in contrast to the regional variation in striatal functions. Whether differences in the intrinsic membrane properties of striatal neurons contribute to regional heterogeneity has not been addressed systematically. We made recordings throughout the young adult mouse striatum under identical conditions, with synaptic input blocked, from four major striatal neuron types, namely, the two subtypes of spiny projection neurons (SPNs), cholinergic interneurons (ChIs), and fast-spiking GABAergic interneurons (FSIs), sampling at least 100 cells per cell type. Regional variation manifested across all cell types. All cell types in the nucleus accumbens (NAc) shell had higher input impedance and increased excitability. Cells in the NAc core were differentiated from the caudate-putamen (CPu) for both SPN subtypes by smaller action potentials and increased excitability. Similarity between the two SPN subtypes showed regional variation, differing more in the NAc than in the CPu. So, in the Str, both the intrinsic properties of interneurons and projection neurons are regionally heterogeneous, with the greatest difference between the NAc and CPu; greater excitability of NAc shell neurons may make the region more susceptible to activity-dependent plasticity.

The nucleus accumbens shell: a neural hub at the interface of homeostatic and hedonic feeding

Feeding behavior is a complex physiological process regulated by the interplay between homeostatic and hedonic feeding circuits. Among the neural structures involved, the nucleus accumbens (NAc) has emerged as a pivotal region at the interface of these two circuits. The NAc comprises distinct subregions and in this review, we focus mainly on the NAc shell (NAcSh). Homeostatic feeding circuits, primarily found in the hypothalamus, ensure the organism's balance in energy and nutrient requirements. These circuits monitor peripheral signals, such as insulin, leptin, and ghrelin, and modulate satiety and hunger states. The NAcSh receives input from these homeostatic circuits, integrating information regarding the organism's metabolic needs. Conversely, so-called hedonic feeding circuits involve all other non-hunger and -satiety processes, i.e., the sensory information, associative learning, reward, motivation and pleasure associated with food consumption. The NAcSh is interconnected with hedonics-related structures like the ventral tegmental area and prefrontal cortex and plays a key role in encoding hedonic information related to palatable food seeking or consumption. In sum, the NAcSh acts as a crucial hub in feeding behavior, integrating signals from both homeostatic and hedonic circuits, to facilitate behavioral output via its downstream projections. Moreover, the NAcSh's involvement extends beyond simple integration, as it directly impacts actions related to food consumption. In this review, we first focus on delineating the inputs targeting the NAcSh; we then present NAcSh output projections to downstream structures. Finally we discuss how the NAcSh regulates feeding behavior and can be seen as a neural hub integrating homeostatic and hedonic feeding signals, via a functionally diverse set of projection neuron subpopulations.

High-throughput analysis of dendrite and axonal arbors reveals transcriptomic correlates of neuroanatomy

Neuronal anatomy is central to the organization and function of brain cell types. However, anatomical variability within apparently homogeneous populations of cells can obscure such insights. Here, we report large-scale automation of neuronal morphology reconstruction and analysis on a dataset of 813 inhibitory neurons characterized using the Patch-seq method, which enables measurement of multiple properties from individual neurons, including local morphology and transcriptional signature. We demonstrate that these automated reconstructions can be used in the same manner as manual reconstructions to understand the relationship between some, but not all, cellular properties used to define cell types. We uncover gene expression correlates of laminar innervation on multiple transcriptomically defined neuronal subclasses and types. In particular, our results reveal correlates of the variability in Layer 1 (L1) axonal innervation in a transcriptomically defined subpopulation of Martinotti cells in the adult mouse neocortex.

Interneuron diversity in the human dorsal striatum

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.

Joint inference of discrete cell types and continuous type-specific variability in single-cell datasets with MMIDAS

Reproducible definition and identification of cell types is essential to enable investigations into their biological function, and understanding their relevance in the context of development, disease and evolution. Current approaches model variability in data as continuous latent factors, followed by clustering as a separate step, or immediately apply clustering on the data. We show that such approaches can suffer from qualitative mistakes in identifying cell types robustly, particularly when the number of such cell types is in the hundreds or even thousands. Here, we propose an unsupervised method, MMIDAS, which combines a generalized mixture model with a multi-armed deep neural network, to jointly infer the discrete type and continuous type-specific variability. Using four recent datasets of brain cells spanning different technologies, species, and conditions, we demonstrate that MMIDAS can identify reproducible cell types and infer cell type-dependent continuous variability in both uni-modal and multi-modal datasets.

Differential Activation States of Direct Pathway Striatal Output Neurons during l-DOPA-Induced Dyskinesia Development

l-DOPA-induced dyskinesia (LID) is a debilitating motor side effect arising from chronic dopamine (DA) replacement therapy with l-DOPA for the treatment of Parkinson's disease. LID is associated with supersensitivity of striatal dopaminergic signaling and fluctuations in synaptic DA following each l-DOPA dose, shrinking the therapeutic window. The heterogeneous composition of the striatum, including subpopulations of medium spiny output neurons (MSNs), interneurons, and supporting cells, complicates the identification of cell(s) underlying LID. We used single-nucleus RNA sequencing (snRNA-seq) to establish a comprehensive striatal transcriptional profile during LID development. Male hemiparkinsonian mice were treated with vehicle or l-DOPA for 1, 5, or 10 d, and striatal nuclei were processed for snRNA-seq. Analyses indicated a limited population of DA D1 receptor-expressing MSNs (D1-MSNs) formed three subclusters in response to l-DOPA treatment and expressed cellular markers of activation. These activated D1-MSNs display similar transcriptional changes previously associated with LID; however, their prevalence and transcriptional behavior were differentially influenced by l-DOPA experience. Differentially expressed genes indicated acute upregulation of plasticity-related transcription factors and mitogen-activated protein kinase signaling, while repeated l-DOPA-induced synaptic remodeling, learning and memory, and transforming growth factor-β (TGF-β) signaling genes. Notably, repeated l-DOPA sensitized Inhba, an activin subunit of the TGF-β superfamily, in activated D1-MSNs, and its pharmacological inhibition impaired LID development, suggesting that activin signaling may play an essential role in LID. These data suggest distinct subsets of D1-MSNs become differentially l-DOPA-responsive due to aberrant induction of molecular mechanisms necessary for neuronal entrainment, similar to processes underlying hippocampal learning and memory.

The single-cell opioid responses in the context of HIV (SCORCH) consortium

Substance use disorders (SUD) and drug addiction are major threats to public health, impacting not only the millions of individuals struggling with SUD, but also surrounding families and communities. One of the seminal challenges in treating and studying addiction in human populations is the high prevalence of co-morbid conditions, including an increased risk of contracting a human immunodeficiency virus (HIV) infection. Of the ~15 million people who inject drugs globally, 17% are persons with HIV. Conversely, HIV is a risk factor for SUD because chronic pain syndromes, often encountered in persons with HIV, can lead to an increased use of opioid pain medications that in turn can increase the risk for opioid addiction. We hypothesize that SUD and HIV exert shared effects on brain cell types, including adaptations related to neuroplasticity, neurodegeneration, and neuroinflammation. Basic research is needed to refine our understanding of these affected cell types and adaptations. Studying the effects of SUD in the context of HIV at the single-cell level represents a compelling strategy to understand the reciprocal interactions among both conditions, made feasible by the availability of large, extensively-phenotyped human brain tissue collections that have been amassed by the Neuro-HIV research community. In addition, sophisticated animal models that have been developed for both conditions provide a means to precisely evaluate specific exposures and stages of disease. We propose that single-cell genomics is a uniquely powerful technology to characterize the effects of SUD and HIV in the brain, integrating data from human cohorts and animal models. We have formed the Single-Cell Opioid Responses in the Context of HIV (SCORCH) consortium to carry out this strategy.

Highly sensitive spatial transcriptomics using FISHnCHIPs of multiple co-expressed genes

High-dimensional, spatially resolved analysis of intact tissue samples promises to transform biomedical research and diagnostics, but existing spatial omics technologies are costly and labor-intensive. We present Fluorescence In Situ Hybridization of Cellular HeterogeneIty and gene expression Programs (FISHnCHIPs) for highly sensitive in situ profiling of cell types and gene expression programs. FISHnCHIPs achieves this by simultaneously imaging ~2-35 co-expressed genes (clustered into modules) that are spatially co-localized in tissues, resulting in similar spatial information as single-gene Fluorescence In Situ Hybridization (FISH), but with ~2-20-fold higher sensitivity. Using FISHnCHIPs, we image up to 53 modules from the mouse kidney and mouse brain, and demonstrate high-speed, large field-of-view profiling of a whole tissue section. FISHnCHIPs also reveals spatially restricted localizations of cancer-associated fibroblasts in a human colorectal cancer biopsy. Overall, FISHnCHIPs enables fast, robust, and scalable cell typing of tissues with normal physiology or undergoing pathogenesis.

Crym-positive striatal astrocytes gate perseverative behaviour

Astrocytes are heterogeneous glial cells of the central nervous system1-3. However, the physiological relevance of astrocyte diversity for neural circuits and behaviour remains unclear. Here we show that a specific population of astrocytes in the central striatum expresses μ-crystallin (encoded by Crym in mice and CRYM in humans) that is associated with several human diseases, including neuropsychiatric disorders4-7. In adult mice, reducing the levels of μ-crystallin in striatal astrocytes through CRISPR-Cas9-mediated knockout of Crym resulted in perseverative behaviours, increased fast synaptic excitation in medium spiny neurons and dysfunctional excitatory-inhibitory synaptic balance. Increased perseveration stemmed from the loss of astrocyte-gated control of neurotransmitter release from presynaptic terminals of orbitofrontal cortex-striatum projections. We found that perseveration could be remedied using presynaptic inhibitory chemogenetics8, and that this treatment also corrected the synaptic deficits. Together, our findings reveal converging molecular, synaptic, circuit and behavioural mechanisms by which a molecularly defined and allocated population of striatal astrocytes gates perseveration phenotypes that accompany neuropsychiatric disorders9-12. Our data show that Crym-positive striatal astrocytes have key biological functions within the central nervous system, and uncover astrocyte-neuron interaction mechanisms that could be targeted in treatments for perseveration.

TREX1 is required for microglial cholesterol homeostasis and oligodendrocyte terminal differentiation in human neural assembloids

Three Prime Repair Exonuclease 1 (TREX1) gene mutations have been associated with Aicardi-Goutières Syndrome (AGS) - a rare, severe pediatric autoimmune disorder that primarily affects the brain and has a poorly understood etiology. Microglia are brain-resident macrophages indispensable for brain development and implicated in multiple neuroinflammatory diseases. However, the role of TREX1 - a DNase that cleaves cytosolic nucleic acids, preventing viral- and autoimmune-related inflammatory responses - in microglia biology remains to be elucidated. Here, we leverage a model of human embryonic stem cell (hESC)-derived engineered microglia-like cells, bulk, and single-cell transcriptomics, optical and transmission electron microscopy, and three-month-old assembloids composed of microglia and oligodendrocyte-containing organoids to interrogate TREX1 functions in human microglia. Our analyses suggest that TREX1 influences cholesterol metabolism, leading to an active microglial morphology with increased phagocytosis in the absence of TREX1. Notably, regulating cholesterol metabolism with an HMG-CoA reductase inhibitor, FDA-approved atorvastatin, rescues these microglial phenotypes. Functionally, TREX1 in microglia is necessary for the transition from gliogenic intermediate progenitors known as pre-oligodendrocyte precursor cells (pre-OPCs) to precursors of the oligodendrocyte lineage known as OPCs, impairing oligodendrogenesis in favor of astrogliogenesis in human assembloids. Together, these results suggest routes for therapeutic intervention in pathologies such as AGS based on microglia-specific molecular and cellular mechanisms.

Integrating single-cell transcriptomics with cellular phenotypes: cell morphology, Ca2+ imaging and electrophysiology

I review recent technological advancements in coupling single-cell transcriptomics with cellular phenotypes including morphology, calcium signaling, and electrophysiology. Single-cell RNA sequencing (scRNAseq) has revolutionized cell type classifications by capturing the transcriptional diversity of cells. A new wave of methods to integrate scRNAseq and biophysical measurements is facilitating the linkage of transcriptomic data to cellular function, which provides physiological insight into cellular states. I briefly discuss critical factors of these phenotypical characterizations such as timescales, information content, and analytical tools. Dedicated sections focus on the integration with cell morphology, calcium imaging, and electrophysiology (patch-seq), emphasizing their complementary roles. I discuss their application in elucidating cellular states, refining cell type classifications, and uncovering functional differences in cell subtypes. To illustrate the practical applications and benefits of these methods, I highlight their use in tissues with excitable cell-types such as the brain, pancreatic islets, and the retina. The potential of combining functional phenotyping with spatial transcriptomics for a detailed mapping of cell phenotypes in situ is explored. Finally, I discuss open questions and future perspectives, emphasizing the need for a shift towards broader accessibility through increased throughput.

Single nuclei transcriptomics in human and non-human primate striatum in opioid use disorder

In brain, the striatum is a heterogenous region involved in reward and goal-directed behaviors. Striatal dysfunction is linked to psychiatric disorders, including opioid use disorder (OUD). Striatal subregions are divided based on neuroanatomy, each with unique roles in OUD. In OUD, the dorsal striatum is involved in altered reward processing, formation of habits, and development of negative affect during withdrawal. Using single nuclei RNA-sequencing, we identified both canonical (e.g., dopamine receptor subtype) and less abundant cell populations (e.g., interneurons) in human dorsal striatum. Pathways related to neurodegeneration, interferon response, and DNA damage were significantly enriched in striatal neurons of individuals with OUD. DNA damage markers were also elevated in striatal neurons of opioid-exposed rhesus macaques. Sex-specific molecular differences in glial cell subtypes associated with chronic stress were found in OUD, particularly female individuals. Together, we describe different cell types in human dorsal striatum and identify cell type-specific alterations in OUD.

Loss of primary cilia and dopaminergic neuroprotection in pathogenic LRRK2-driven and idiopathic Parkinson's disease

Activating LRRK2 mutations cause Parkinson's disease. Previously, we showed that cholinergic interneurons and astrocytes but not medium spiny neurons of the dorsal striatum lose primary cilia in LRRK2 mutant mice. Single nucleus RNA sequencing shows that cilia loss in cholinergic interneurons correlates with higher LRRK2 expression and decreased glial derived neurotrophic factor transcription. Nevertheless, much higher LRRK2 expression is seen in medium spiny neurons that have normal cilia in mice and humans. In parallel with decreased striatal dopaminergic neurite density, LRRK2 G2019S neurons show increased autism-linked CNTN5 adhesion protein expression; glial cells show significant loss of ferritin heavy chain. Human striatal tissue from LRRK2 pathway mutation carriers and idiopathic Parkinson's disease show similar cilia loss in cholinergic interneurons and astrocytes and overall loss of such neurons. These data strongly suggest that loss of cilia in specific striatal cell types decreases neuroprotection for dopamine neurons in mice and human Parkinson's disease.

Neural heterogeneity controls computations in spiking neural networks

The brain is composed of complex networks of interacting neurons that express considerable heterogeneity in their physiology and spiking characteristics. How does this neural heterogeneity influence macroscopic neural dynamics, and how might it contribute to neural computation? In this work, we use a mean-field model to investigate computation in heterogeneous neural networks, by studying how the heterogeneity of cell spiking thresholds affects three key computational functions of a neural population: the gating, encoding, and decoding of neural signals. Our results suggest that heterogeneity serves different computational functions in different cell types. In inhibitory interneurons, varying the degree of spike threshold heterogeneity allows them to gate the propagation of neural signals in a reciprocally coupled excitatory population. Whereas homogeneous interneurons impose synchronized dynamics that narrow the dynamic repertoire of the excitatory neurons, heterogeneous interneurons act as an inhibitory offset while preserving excitatory neuron function. Spike threshold heterogeneity also controls the entrainment properties of neural networks to periodic input, thus affecting the temporal gating of synaptic inputs. Among excitatory neurons, heterogeneity increases the dimensionality of neural dynamics, improving the network's capacity to perform decoding tasks. Conversely, homogeneous networks suffer in their capacity for function generation, but excel at encoding signals via multistable dynamic regimes. Drawing from these findings, we propose intra-cell-type heterogeneity as a mechanism for sculpting the computational properties of local circuits of excitatory and inhibitory spiking neurons, permitting the same canonical microcircuit to be tuned for diverse computational tasks.

Neuronal types in the mouse amygdala and their transcriptional response to fear conditioning

The amygdala is a brain region primarily associated with emotional response. The use of genetic markers and single-cell transcriptomics can provide insights into behavior-associated cell state changes. Here we present a detailed cell-type taxonomy of the adult mouse amygdala during fear learning and memory consolidation. We perform single-cell RNA sequencing on naïve and fear-conditioned mice, identify 130 neuronal cell types and validate their spatial distributions. A subset of all neuronal types is transcriptionally responsive to fear learning and memory retrieval. The activated engram cells upregulate activity-response genes and coordinate the expression of genes associated with neurite outgrowth, synaptic signaling, plasticity and development. We identify known and previously undescribed candidate genes responsive to fear learning. Our molecular atlas may be used to generate hypotheses to unveil the neuron types and neural circuits regulating the emotional component of learning and memory.

Molecularly defined and spatially resolved cell atlas of the whole mouse brain

In mammalian brains, millions to billions of cells form complex interaction networks to enable a wide range of functions. The enormous diversity and intricate organization of cells have impeded our understanding of the molecular and cellular basis of brain function. Recent advances in spatially resolved single-cell transcriptomics have enabled systematic mapping of the spatial organization of molecularly defined cell types in complex tissues1-3, including several brain regions (for example, refs. 1-11). However, a comprehensive cell atlas of the whole brain is still missing. Here we imaged a panel of more than 1,100 genes in approximately 10 million cells across the entire adult mouse brains using multiplexed error-robust fluorescence in situ hybridization12 and performed spatially resolved, single-cell expression profiling at the whole-transcriptome scale by integrating multiplexed error-robust fluorescence in situ hybridization and single-cell RNA sequencing data. Using this approach, we generated a comprehensive cell atlas of more than 5,000 transcriptionally distinct cell clusters, belonging to more than 300 major cell types, in the whole mouse brain with high molecular and spatial resolution. Registration of this atlas to the mouse brain common coordinate framework allowed systematic quantifications of the cell-type composition and organization in individual brain regions. We further identified spatial modules characterized by distinct cell-type compositions and spatial gradients featuring gradual changes of cells. Finally, this high-resolution spatial map of cells, each with a transcriptome-wide expression profile, allowed us to infer cell-type-specific interactions between hundreds of cell-type pairs and predict molecular (ligand-receptor) basis and functional implications of these cell-cell interactions. These results provide rich insights into the molecular and cellular architecture of the brain and a foundation for functional investigations of neural circuits and their dysfunction in health and disease.

Spiny projection neurons exhibit transcriptional signatures within subregions of the dorsal striatum

The dorsal striatum is organized into functional territories defined by corticostriatal inputs onto both direct and indirect spiny projection neurons (SPNs), the major cell types within the striatum. In addition to circuit connectivity, striatal domains are likely defined by the spatially determined transcriptomes of SPNs themselves. To identify cell-type-specific spatiomolecular signatures of direct and indirect SPNs within dorsomedial, dorsolateral, and ventrolateral dorsal striatum, we used RNA profiling in situ hybridization with probes to >98% of protein coding genes. We demonstrate that the molecular identity of SPNs is mediated by hundreds of differentially expressed genes across territories of the striatum, revealing extraordinary heterogeneity in the expression of genes that mediate synaptic function in both direct and indirect SPNs. This deep insight into the complex spatiomolecular organization of the striatum provides a foundation for understanding both normal striatal function and for dissecting region-specific dysfunction in disorders of the striatum.

Integrative multi-dimensional characterization of striatal projection neuron heterogeneity in adult brain

Striatal projection neurons (SPNs) are traditionally segregated into two subpopulations expressing dopamine (DA) D1-like or D2-like receptors. However, this dichotomy is challenged by recent evidence. Functional and expression studies raise important questions: do SPNs co-express different DA receptors, and do these differences reflect unique striatal spatial distributions and expression profiles? Using RNAscope in mouse striatum, we report heterogenous SPN subpopulations distributed across dorsal-ventral and rostral-caudal axes. SPN subpopulations co-express multiple DA receptors, including D1 and D2 (D1/2R) and D1 and D3. Our integrative approach using single-nuclei multi-omics analyses provides a simple consensus to describe SPNs across diverse datasets, connecting it to complementary spatial mapping. Combining RNAscope and multi-omics shows D1/2R SPNs further separate into distinct subtypes according to spatial organization and conserved marker genes. Each SPN cell type contributes uniquely to genetic risk for neuropsychiatric diseases. Our results bridge anatomy and transcriptomics to offer new understandings of striatal neuron heterogeneity.

Δ9-Tetrahydrocannabinol does not upregulate an aversive dopamine receptor mechanism in adolescent brain unlike in adults

Earlier age of cannabis usage poses higher risk of Cannabis Use Disorder and adverse consequences, such as addiction, anxiety, dysphoria, psychosis, largely attributed to its principal psychoactive component, Δ9-tetrahydrocannabinol (THC) and altered dopaminergic function. As dopamine D1-D2 receptor heteromer activation causes anxiety and anhedonia, this signaling complex was postulated to contribute to THC-induced affective symptoms. To investigate this, we administered THC repeatedly to adolescent monkeys and adolescent or adult rats. Drug-naïve adolescent rat had lower striatal densities of D1-D2 heteromer compared to adult rat. Repeated administration of THC to adolescent rat or adolescent monkey did not alter D1-D2 heteromer expression in nucleus accumbens or dorsal striatum but upregulated it in adult rat. Behaviourally, THC-treated adult, but not adolescent rat manifested anxiety and anhedonia-like behaviour, with elevated composite negative emotionality scores that correlated with striatal D1-D2 density. THC modified downstream markers of D1-D2 activation in adult, but not adolescent striatum. THC administered with cannabidiol did not alter D1-D2 expression. In adult rat, co-administration of CB1 receptor (CB1R) inverse agonist with THC attenuated D1-D2 upregulation, implicating cannabinoids in the regulation of striatal D1-D2 heteromer expression. THC exposure revealed an adaptable age-specific, anxiogenic, anti-reward mechanism operant in adult striatum but deficient in adolescent rat and monkey striatum that may confer increased sensitivity to THC reward in adolescence while limiting its negative effects, thus promoting continued use and increasing vulnerability to long-term adverse cannabis effects.

SMDB: a Spatial Multimodal Data Browser

Understanding the relationship between fine-scale spatial organization and biological function necessitates a tool that effectively combines spatial positions, morphological information, and spatial transcriptomics (ST) data. We introduce the Spatial Multimodal Data Browser (SMDB, https://www.biosino.org/smdb), a robust visualization web service for interactively exploring ST data. By integrating multimodal data, such as hematoxylin and eosin (H&E) images, gene expression-based molecular clusters, and more, SMDB facilitates the analysis of tissue composition through the dissociation of two-dimensional (2D) sections and the identification of gene expression-profiled boundaries. In a digital three-dimensional (3D) space, SMDB allows researchers to reconstruct morphology visualizations based on manually filtered spots or expand anatomical structures using high-resolution molecular subtypes. To enhance user experience, it offers customizable workspaces for interactive exploration of ST spots in tissues, providing features like smooth zooming, panning, 360-degree rotation in 3D and adjustable spot scaling. SMDB is particularly valuable in neuroscience and spatial histology studies, as it incorporates Allen's mouse brain anatomy atlas for reference in morphological research. This powerful tool provides a comprehensive and efficient solution for examining the intricate relationships between spatial morphology, and biological function in various tissues.

A single-cell trajectory atlas of striatal development

The striatum integrates dense neuromodulatory inputs from many brain regions to coordinate complex behaviors. This integration relies on the coordinated responses from distinct striatal cell types. While previous studies have characterized the cellular and molecular composition of the striatum using single-cell RNA-sequencing at distinct developmental timepoints, the molecular changes spanning embryonic through postnatal development at the single-cell level have not been examined. Here, we combine published mouse striatal single-cell datasets from both embryonic and postnatal timepoints to analyze the developmental trajectory patterns and transcription factor regulatory networks within striatal cell types. Using this integrated dataset, we found that dopamine receptor-1 expressing spiny projection neurons have an extended period of transcriptional dynamics and greater transcriptional complexity over postnatal development compared to dopamine receptor-2 expressing neurons. Moreover, we found the transcription factor, FOXP1, exerts indirect changes to oligodendrocytes. These data can be accessed and further analyzed through an interactive website ( https://mouse-striatal-dev.cells.ucsc.edu ).

Interneuron diversity in the human dorsal striatum

Deciphering the striatal interneuron diversity is key to understanding the basal ganglia circuit and to untangle the complex neurological and psychiatric diseases affecting this brain structure. We performed snRNA-seq of postmortem human caudate nucleus and putamen samples to elucidate the diversity and abundance of interneuron populations and their transcriptional structure in the human dorsal striatum. We propose a new taxonomy of striatal interneurons with eight main classes and fourteen subclasses and provide their specific markers and some quantitative FISH validation, particularly for a novel PTHLH-expressing population. For the most abundant populations, PTHLH and TAC3, we found matching known mouse interneuron populations based on key functional genes such as ion channels and synaptic receptors. Remarkably, human TAC3 and mouse Th populations share important similarities including the expression of the neuropeptide tachykinin 3. Finally, we were able to integrate other published datasets supporting the generalizability of this new harmonized taxonomy.

Predictive and robust gene selection for spatial transcriptomics

A prominent trend in single-cell transcriptomics is providing spatial context alongside a characterization of each cell's molecular state. This typically requires targeting an a priori selection of genes, often covering less than 1% of the genome, and a key question is how to optimally determine the small gene panel. We address this challenge by introducing a flexible deep learning framework, PERSIST, to identify informative gene targets for spatial transcriptomics studies by leveraging reference scRNA-seq data. Using datasets spanning different brain regions, species, and scRNA-seq technologies, we show that PERSIST reliably identifies panels that provide more accurate prediction of the genome-wide expression profile, thereby capturing more information with fewer genes. PERSIST can be adapted to specific biological goals, and we demonstrate that PERSIST's binarization of gene expression levels enables models trained on scRNA-seq data to generalize with to spatial transcriptomics data, despite the complex shift between these technologies.

PQBP1 regulates striatum development through balancing striatal progenitor proliferation and differentiation

The balance between cell proliferation and differentiation is essential for maintaining the neural progenitor pool and brain development. Although the mechanisms underlying cell proliferation and differentiation at the transcriptional level have been studied intensively, post-transcriptional regulation of cell proliferation and differentiation remains largely unclear. Here, we show that deletion of the alternative splicing regulator PQBP1 in striatal progenitors results in defective striatal development due to impaired neurogenesis of spiny projection neurons (SPNs). Pqbp1-deficient striatal progenitors exhibit declined proliferation and increased differentiation, resulting in a reduced striatal progenitor pool. We further reveal that PQBP1 associates with components in splicing machinery. The alternative splicing profiles identify that PQBP1 promotes the exon 9 inclusion of Numb, a variant that mediates progenitor proliferation. These findings identify PQBP1 as a regulator in balancing striatal progenitor proliferation and differentiation and provide alternative insights into the pathogenic mechanisms underlying Renpenning syndrome.

A molecularly defined and spatially resolved cell atlas of the whole mouse brain

In mammalian brains, tens of millions to billions of cells form complex interaction networks to enable a wide range of functions. The enormous diversity and intricate organization of cells in the brain have so far hindered our understanding of the molecular and cellular basis of its functions. Recent advances in spatially resolved single-cell transcriptomics have allowed systematic mapping of the spatial organization of molecularly defined cell types in complex tissues1-3. However, these approaches have only been applied to a few brain regions1-11 and a comprehensive cell atlas of the whole brain is still missing. Here, we imaged a panel of >1,100 genes in ~8 million cells across the entire adult mouse brain using multiplexed error-robust fluorescence in situ hybridization (MERFISH)12 and performed spatially resolved, single-cell expression profiling at the whole-transcriptome scale by integrating MERFISH and single-cell RNA-sequencing (scRNA-seq) data. Using this approach, we generated a comprehensive cell atlas of >5,000 transcriptionally distinct cell clusters, belonging to ~300 major cell types, in the whole mouse brain with high molecular and spatial resolution. Registration of the MERFISH images to the common coordinate framework (CCF) of the mouse brain further allowed systematic quantifications of the cell composition and organization in individual brain regions defined in the CCF. We further identified spatial modules characterized by distinct cell-type compositions and spatial gradients featuring gradual changes in the gene-expression profiles of cells. Finally, this high-resolution spatial map of cells, with a transcriptome-wide expression profile associated with each cell, allowed us to infer cell-type-specific interactions between several hundred pairs of molecularly defined cell types and predict potential molecular (ligand-receptor) basis and functional implications of these cell-cell interactions. These results provide rich insights into the molecular and cellular architecture of the brain and a valuable resource for future functional investigations of neural circuits and their dysfunction in diseases.

A high-resolution transcriptomic and spatial atlas of cell types in the whole mouse brain

The mammalian brain is composed of millions to billions of cells that are organized into numerous cell types with specific spatial distribution patterns and structural and functional properties. An essential step towards understanding brain function is to obtain a parts list, i.e., a catalog of cell types, of the brain. Here, we report a comprehensive and high-resolution transcriptomic and spatial cell type atlas for the whole adult mouse brain. The cell type atlas was created based on the combination of two single-cell-level, whole-brain-scale datasets: a single-cell RNA-sequencing (scRNA-seq) dataset of ~7 million cells profiled, and a spatially resolved transcriptomic dataset of ~4.3 million cells using MERFISH. The atlas is hierarchically organized into five nested levels of classification: 7 divisions, 32 classes, 306 subclasses, 1,045 supertypes and 5,200 clusters. We systematically analyzed the neuronal, non-neuronal, and immature neuronal cell types across the brain and identified a high degree of correspondence between transcriptomic identity and spatial specificity for each cell type. The results reveal unique features of cell type organization in different brain regions, in particular, a dichotomy between the dorsal and ventral parts of the brain: the dorsal part contains relatively fewer yet highly divergent neuronal types, whereas the ventral part contains more numerous neuronal types that are more closely related to each other. We also systematically characterized cell-type specific expression of neurotransmitters, neuropeptides, and transcription factors. The study uncovered extraordinary diversity and heterogeneity in neurotransmitter and neuropeptide expression and co-expression patterns in different cell types across the brain, suggesting they mediate a myriad of modes of intercellular communications. Finally, we found that transcription factors are major determinants of cell type classification in the adult mouse brain and identified a combinatorial transcription factor code that defines cell types across all parts of the brain. The whole-mouse-brain transcriptomic and spatial cell type atlas establishes a benchmark reference atlas and a foundational resource for deep and integrative investigations of cell type and circuit function, development, and evolution of the mammalian brain.

Scalable in situ single-cell profiling by electrophoretic capture of mRNA using EEL FISH

Methods to spatially profile the transcriptome are dominated by a trade-off between resolution and throughput. Here we develop a method named Enhanced ELectric Fluorescence in situ Hybridization (EEL FISH) that can rapidly process large tissue samples without compromising spatial resolution. By electrophoretically transferring RNA from a tissue section onto a capture surface, EEL speeds up data acquisition by reducing the amount of imaging needed, while ensuring that RNA molecules move straight down toward the surface, preserving single-cell resolution. We apply EEL on eight entire sagittal sections of the mouse brain and measure the expression patterns of up to 440 genes to reveal complex tissue organization. Moreover, EEL can be used to study challenging human samples by removing autofluorescent lipofuscin, enabling the spatial transcriptome of the human visual cortex to be visualized. We provide full hardware specifications, all protocols and complete software for instrument control, image processing, data analysis and visualization.

Accurate inference of genome-wide spatial expression with iSpatial

Spatially resolved transcriptomic analyses can reveal molecular insights underlying tissue structure and context-dependent cell-cell or cell-environment interaction. Because of the current technical limitation, obtaining genome-wide spatial transcriptome at single-cell resolution is challenging. Here, we developed a new algorithm named iSpatial to derive the spatial pattern of the entire transcriptome by integrating spatial transcriptomic and single-cell RNA-seq datasets. Compared to other existing methods, iSpatial has higher accuracy in predicting gene expression and spatial distribution. Furthermore, it reduces false-positive and false-negative signals in the original datasets. By testing iSpatial with multiple spatial transcriptomic datasets, we demonstrate its wide applicability to datasets from different tissues and by different techniques. Thus, we provide a computational approach to reveal spatial organization of the entire transcriptome at single-cell resolution. With numerous high-quality datasets available in the public domain, iSpatial provides a unique way to understand the structure and function of complex tissues and disease processes.

Cell types as species: Exploring a metaphor

The concept of "cell type," though fundamental to cell biology, is controversial. Cells have historically been classified into types based on morphology, physiology, or location. More recently, single cell transcriptomic studies have revealed fine-scale differences among cells with similar gross phenotypes. Transcriptomic snapshots of cells at various stages of differentiation, and of cells under different physiological conditions, have shown that in many cases variation is more continuous than discrete, raising questions about the relationship between cell type and cell state. Some researchers have rejected the notion of fixed types altogether. Throughout the history of discussions on cell type, cell biologists have compared the problem of defining cell type with the interminable and often contentious debate over the definition of arguably the most important concept in systematics and evolutionary biology, "species." In the last decades, systematics, like cell biology, has been transformed by the increasing availability of molecular data, and the fine-grained resolution of genetic relationships have generated new ideas about how that variation should be classified. There are numerous parallels between the two fields that make exploration of the "cell types as species" metaphor timely. These parallels begin with philosophy, with discussion of both cell types and species as being either individuals, groups, or something in between (e.g., homeostatic property clusters). In each field there are various different types of lineages that form trees or networks that can (and in some cases do) provide criteria for grouping. Developing and refining models for evolutionary divergence of species and for cell type differentiation are parallel goals of the two fields. The goal of this essay is to highlight such parallels with the hope of inspiring biologists in both fields to look for new solutions to similar problems outside of their own field.

A molecularly defined D1 medium spiny neuron subtype negatively regulates cocaine addiction

The striatum plays a critical role in regulating addiction-related behaviors. The conventional dichotomy model suggests that striatal D1/D2 medium spiny neurons (MSNs) positively/negatively regulate addiction-related behaviors. However, this model does not account for the neuronal heterogeneity and functional diversity of the striatum, and whether MSN subtypes beyond the pan-D1/D2 populations play distinct roles in drug addiction remains unknown. We characterized the role of a tachykinin 2-expressing D1 MSN subtype (Tac2+), present in both rodent and primate striatum, using cocaine addiction mouse models. We found that acute cocaine administration reduces Tac2 neuronal activity, and cocaine conditioning alters neuronal response related to cocaine reward contextual associations. In addition, activation/inhibition of Tac2+ neurons attenuates/promotes cocaine-induced conditioned place preference and cocaine intravenous self-administration. Furthermore, stimulation of the NAc-to-lateral hypothalamic projection of Tac2+ neurons suppresses cocaine reward behavior. Our study reveals an unconventional negative regulatory function of D1 MSNs in drug addiction that operates in a subtype- and projection-specific manner.

What is a cell type and how to define it?

Cell types are the basic functional units of an organism. Cell types exhibit diverse phenotypic properties at multiple levels, making them challenging to define, categorize, and understand. This review provides an overview of the basic principles of cell types rooted in evolution and development and discusses approaches to characterize and classify cell types and investigate how they contribute to the organism's function, using the mammalian brain as a primary example. I propose a roadmap toward a conceptual framework and knowledge base of cell types that will enable a deeper understanding of the dynamic changes of cellular function under healthy and diseased conditions.

Morphological pseudotime ordering and fate mapping reveal diversification of cerebellar inhibitory interneurons

Understanding how diverse neurons are assembled into circuits requires a framework for describing cell types and their developmental trajectories. Here we combine genetic fate-mapping, pseudotemporal profiling of morphogenesis, and dual morphology and RNA labeling to resolve the diversification of mouse cerebellar inhibitory interneurons. Molecular layer interneurons (MLIs) derive from a common progenitor population but comprise diverse dendritic-, somatic-, and axon initial segment-targeting interneurons. Using quantitative morphology from 79 mature MLIs, we identify two discrete morphological types and presence of extensive within-class heterogeneity. Pseudotime trajectory inference using 732 developmental morphologies indicate the emergence of distinct MLI types during migration, before reaching their final positions. By comparing MLI identities from morphological and transcriptomic signatures, we demonstrate the dissociation between these modalities and that subtype divergence can be resolved from axonal morphogenesis prior to marker gene expression. Our study illustrates the utility of applying single-cell methods to quantify morphology for defining neuronal diversification.

Dlx1/2-dependent expression of Meis2 promotes neuronal fate determination in the mammalian striatum

The striatum is a central regulator of behavior and motor function through the actions of D1 and D2 medium-sized spiny neurons (MSNs), which arise from a common lateral ganglionic eminence (LGE) progenitor. The molecular mechanisms of cell fate specification of these two neuronal subtypes are incompletely understood. Here, we found that deletion of murine Meis2, which is highly expressed in the LGE and derivatives, led to a large reduction in striatal MSNs due to a block in their differentiation. Meis2 directly binds to the Zfp503 and Six3 promoters and is required for their expression and specification of D1 and D2 MSNs, respectively. Finally, Meis2 expression is regulated by Dlx1/2 at least partially through the enhancer hs599 in the LGE subventricular zone. Overall, our findings define a pathway in the LGE whereby Dlx1/2 drives expression of Meis2, which subsequently promotes the fate determination of striatal D1 and D2 MSNs via Zfp503 and Six3.

Transcriptional and anatomical diversity of medium spiny neurons in the primate striatum

Medium spiny neurons (MSNs) constitute the vast majority of striatal neurons and the principal interface between dopamine reward signals and functionally diverse cortico-basal ganglia circuits. Information processing in these circuits is dependent on distinct MSN types: cell types that are traditionally defined according to their projection targets or dopamine receptor expression. Single-cell transcriptional studies have revealed greater MSN heterogeneity than predicted by traditional circuit models, but the transcriptional landscape in the primate striatum remains unknown. Here, we set out to establish molecular definitions for MSN subtypes in Rhesus monkeys and to explore the relationships between transcriptionally defined subtypes and anatomical subdivisions of the striatum. Our results suggest at least nine MSN subtypes, including dorsal striatum subtypes associated with striosome and matrix compartments, ventral striatum subtypes associated with the nucleus accumbens shell and olfactory tubercle, and an MSN-like cell type restricted to μ-opioid receptor rich islands in the ventral striatum. Although each subtype was demarcated by discontinuities in gene expression, continuous variation within subtypes defined gradients corresponding to anatomical locations and, potentially, functional specializations. These results lay the foundation for achieving cell-type-specific transgenesis in the primate striatum and provide a blueprint for investigating circuit-specific information processing.

Decoding molecular and cellular heterogeneity of mouse nucleus accumbens

The nucleus accumbens (NAc) plays an important role in regulating multiple behaviors, and its dysfunction has been linked to many neural disorders. However, the molecular, cellular and anatomic heterogeneity underlying its functional diversity remains incompletely understood. In this study, we generated a cell census of the mouse NAc using single-cell RNA sequencing and multiplexed error-robust fluorescence in situ hybridization, revealing a high level of cell heterogeneity in this brain region. Here we show that the transcriptional and spatial diversity of neuron subtypes underlie the NAc's anatomic and functional heterogeneity. These findings explain how the seemingly simple neuronal composition of the NAc achieves its highly heterogenous structure and diverse functions. Collectively, our study generates a spatially resolved cell taxonomy for understanding the structure and function of the NAc, which demonstrates the importance of combining molecular and spatial information in revealing the fundamental features of the nervous system.

From Progenitors to Progeny: Shaping Striatal Circuit Development and Function

Understanding how neurons of the striatum are formed and integrate into complex synaptic circuits is essential to provide insight into striatal function in health and disease. In this review, we summarize our current understanding of the development of striatal neurons and associated circuits with a focus on their embryonic origin. Specifically, we address the role of distinct types of embryonic progenitors, found in the proliferative zones of the ganglionic eminences in the ventral telencephalon, in the generation of diverse striatal interneurons and projection neurons. Indeed, recent evidence would suggest that embryonic progenitor origin dictates key characteristics of postnatal cells, including their neurochemical content, their location within striatum, and their long-range synaptic inputs. We also integrate recent observations regarding embryonic progenitors in cortical and other regions and discuss how this might inform future research on the ganglionic eminences. Last, we examine how embryonic progenitor dysfunction can alter striatal formation, as exemplified in Huntington's disease and autism spectrum disorder, and how increased understanding of embryonic progenitors can have significant implications for future research directions and the development of improved therapeutic options.SIGNIFICANCE STATEMENT This review highlights recently defined novel roles for embryonic progenitor cells in shaping the functional properties of both projection neurons and interneurons of the striatum. It outlines the developmental mechanisms that guide neuronal development from progenitors in the embryonic ganglionic eminences to progeny in the striatum. Where questions remain open, we integrate observations from cortex and other regions to present possible avenues for future research. Last, we provide a progenitor-centric perspective onto both Huntington's disease and autism spectrum disorder. We suggest that future investigations and manipulations of embryonic progenitor cells in both research and clinical settings will likely require careful consideration of their great intrinsic diversity and neurogenic potential.

A transcriptomic atlas of mouse cerebellar cortex comprehensively defines cell types

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.

Graded heterogeneity of metabotropic signaling underlies a continuum of cell-intrinsic temporal responses in unipolar brush cells

Many neuron types consist of populations with continuously varying molecular properties. Here, we show a continuum of postsynaptic molecular properties in three types of neurons and assess the functional correlates in cerebellar unipolar brush cells (UBCs). While UBCs are generally thought to form discrete functional subtypes, with mossy fiber (MF) activation increasing firing in ON-UBCs and suppressing firing in OFF-UBCs, recent work also points to a heterogeneity of response profiles. Indeed, we find a continuum of response profiles that reflect the graded and inversely correlated expression of excitatory mGluR1 and inhibitory mGluR2/3 pathways. MFs coactivate mGluR2/3 and mGluR1 in many UBCs, leading to sequential inhibition-excitation because mGluR2/3-currents are faster. Additionally, we show that DAG-kinase controls mGluR1 response duration, and that graded DAG kinase levels correlate with systematic variation of response duration over two orders of magnitude. These results demonstrate that continuous variations in metabotropic signaling can generate a stable cell-autonomous basis for temporal integration and learning over multiple time scales.

Single-nucleus transcriptome analysis reveals cell-type-specific molecular signatures across reward circuitry in the human brain

Single-cell gene expression technologies are powerful tools to study cell types in the human brain, but efforts have largely focused on cortical brain regions. We therefore created a single-nucleus RNA-sequencing resource of 70,615 high-quality nuclei to generate a molecular taxonomy of cell types across five human brain regions that serve as key nodes of the human brain reward circuitry: nucleus accumbens, amygdala, subgenual anterior cingulate cortex, hippocampus, and dorsolateral prefrontal cortex. We first identified novel subpopulations of interneurons and medium spiny neurons (MSNs) in the nucleus accumbens and further characterized robust GABAergic inhibitory cell populations in the amygdala. Joint analyses across the 107 reported cell classes revealed cell-type substructure and unique patterns of transcriptomic dynamics. We identified discrete subpopulations of D1- and D2-expressing MSNs in the nucleus accumbens to which we mapped cell-type-specific enrichment for genetic risk associated with both psychiatric disease and addiction.

Unbiased identification of novel transcription factors in striatal compartmentation and striosome maturation

Many diseases are linked to dysregulation of the striatum. Striatal function depends on neuronal compartmentation into striosomes and matrix. Striatal projection neurons are GABAergic medium spiny neurons (MSNs), subtyped by selective expression of receptors, neuropeptides, and other gene families. Neurogenesis of the striosome and matrix occurs in separate waves, but the factors regulating compartmentation and neuronal differentiation are largely unidentified. We performed RNA- and ATAC-seq on sorted striosome and matrix cells at postnatal day 3, using the Nr4a1-EGFP striosome reporter mouse. Focusing on the striosome, we validated the localization and/or role of Irx1, Foxf2, Olig2, and Stat1/2 in the developing striosome and the in vivo enhancer function of a striosome-specific open chromatin region 4.4 Kb downstream of Olig2. These data provide novel tools to dissect and manipulate the networks regulating MSN compartmentation and differentiation, including in human iPSC-derived striatal neurons for disease modeling and drug discovery.

Parallel and hierarchical neural mechanisms for adaptive and predictive behavioral control

Our brain can be recognized as a network of largely hierarchically organized neural circuits that operate to control specific functions, but when acting in parallel, enable the performance of complex and simultaneous behaviors. Indeed, many of our daily actions require concurrent information processing in sensorimotor, associative, and limbic circuits that are dynamically and hierarchically modulated by sensory information and previous learning. This organization of information processing in biological organisms has served as a major inspiration for artificial intelligence and has helped to create in silico systems capable of matching or even outperforming humans in several specific tasks, including visual recognition and strategy-based games. However, the development of human-like robots that are able to move as quickly as humans and respond flexibly in various situations remains a major challenge and indicates an area where further use of parallel and hierarchical architectures may hold promise. In this article we review several important neural and behavioral mechanisms organizing hierarchical and predictive processing for the acquisition and realization of flexible behavioral control. Then, inspired by the organizational features of brain circuits, we introduce a multi-timescale parallel and hierarchical learning framework for the realization of versatile and agile movement in humanoid robots.

Phenotypic variation of transcriptomic cell types in mouse motor cortex

Cortical neurons exhibit extreme diversity in gene expression as well as in morphological and electrophysiological properties1,2. Most existing neural taxonomies are based on either transcriptomic3,4 or morpho-electric5,6 criteria, as it has been technically challenging to study both aspects of neuronal diversity in the same set of cells7. Here we used Patch-seq8 to combine patch-clamp recording, biocytin staining, and single-cell RNA sequencing of more than 1,300 neurons in adult mouse primary motor cortex, providing a morpho-electric annotation of almost all transcriptomically defined neural cell types. We found that, although broad families of transcriptomic types (those expressing Vip, Pvalb, Sst and so on) had distinct and essentially non-overlapping morpho-electric phenotypes, individual transcriptomic types within the same family were not well separated in the morpho-electric space. Instead, there was a continuum of variability in morphology and electrophysiology, with neighbouring transcriptomic cell types showing similar morpho-electric features, often without clear boundaries between them. Our results suggest that neuronal types in the neocortex do not always form discrete entities. Instead, neurons form a hierarchy that consists of distinct non-overlapping branches at the level of families, but can form continuous and correlated transcriptomic and morpho-electrical landscapes within families.