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RNA is a central and universal mediator of genetic information underlying the diversity of cell types and cell states, which together shape tissue organization and organismal function across species and lifespans. Despite numerous advances in RNA sequencing technologies and the massive accumulation of transcriptome datasets across the life sciences

Cooperative forelimb and mouth movements during eating contribute to diet selection among vertebrates including the oromanual manipulatory skills in rodents and primates. Whereas spinal and brainstem circuits implement forelimb and orofacial actions, whether there is a specialized cortical circuit that flexibly assembles these to achieve cross-body and oromanual coordination for skilled manipulation remains unclear. Here we discover a cortical region and its cell-type-specific circuitry that orchestrates body postures and oromanual coordination for food manipulation in mice. An optogenetic screen of cortical areas and projection neuron types identified a rostral forelimb-orofacial area (RFO), wherein activation of pyramidal tract (PTFezf2) and intratelencephalic (ITPlxnD1) neurons induced concurrent posture, forelimb and orofacial eating-like movements. In a pasta-eating behavior, RFO PTFezf2and ITPlxnD1activity were closely correlated with picking up the pasta, adopting a sitting posture, oromanual manipulation, and hand-assisted biting. RFO inactivation and inhibition of RFO PTsFezf2and ITsPlxnD1impaired posture and oromanual coordination, leading to deficient pasta manipulation and biting. RFO is reciprocally connected to forelimb and orofacial sensorimotor areas as well as insular and visceral areas. Within this network, ITsPlxnD1project bilaterally to the entire network and the ventrolateral striatum and PTsFezf2project to multiple subcortical areas associated with forelimb and orofacial control. These results suggest that ITsPlxnD1select and coordinate the feeding program involving multiple body parts and PTsFezf2implement the fine details of movements. Our study reveals a neural circuit basis of hand-mouth coordination for object manipulation.

An essential step toward understanding brain function is to establish a structural framework with cellular resolution on which multi-scale datasets spanning molecules, cells, circuits and systems can be integrated and interpreted1. Here, as part of the collaborative Brain Initiative Cell Census Network (BICCN), we derive a comprehensive cell type-based anatomical description of one exemplar brain structure, the mouse primary motor cortex, upper limb area (MOp-ul). Using genetic and viral labelling, barcoded anatomy resolved by sequencing, single-neuron reconstruction, whole-brain imaging and cloud-based neuroinformatics tools, we delineated the MOp-ul in 3D and refined its sublaminar organization. We defined around two dozen projection neuron types in the MOp-ul and derived an input–output wiring diagram, which will facilitate future analyses of motor control circuitry across molecular, cellular and system levels. This work provides a roadmap towards a comprehensive cellular-resolution description of mammalian brain architecture., Multi-modal analysis is used to generate a 3D atlas of the upper limb area of the mouse primary motor cortex, providing a framework for future studies of motor control circuitry.

Diverse types of glutamatergic pyramidal neurons mediate the myriad processing streams and output channels of the cerebral cortex1,2, yet all derive from neural progenitors of the embryonic dorsal telencephalon3,4. Here we establish genetic strategies and tools for dissecting and fate-mapping subpopulations of pyramidal neurons on the basis of their developmental and molecular programs. We leverage key transcription factors and effector genes to systematically target temporal patterning programs in progenitors and differentiation programs in postmitotic neurons. We generated over a dozen temporally inducible mouse Cre and Flp knock-in driver lines to enable the combinatorial targeting of major progenitor types and projection classes. Combinatorial strategies confer viral access to subsets of pyramidal neurons defined by developmental origin, marker expression, anatomical location and projection targets. These strategies establish an experimental framework for understanding the hierarchical organization and developmental trajectory of subpopulations of pyramidal neurons that assemble cortical processing networks and output channels., A combination of genetic strategies and tools is used to define and fate-map different subtypes of glutamatergic pyramidal neurons according to their developmental and molecular programs, providing insight into the assembly of cortical processing networks.

The cellular basis of cerebral cortex functional architecture remains not well understood. A major challenge is to monitor and decipher neural network dynamics across broad cortical areas yet with projection neuron (PN)-type resolution in real time during behavior. Combining genetic targeting and wide-field imaging, we monitored activity dynamics of subcortical-projecting (PTFezf2) and intratelencephalic-projecting (ITPlxnD1) types across dorsal cortex of mice during different brain states and behaviors. ITPlxnD1 and PTFezf2 neurons showed distinct activation patterns during wakeful resting, spontaneous movements, and upon sensory stimulation. Distinct ITPlxnD1 and PTFezf2 subnetworks were dynamically tuned to different sensorimotor components of a naturalistic feeding behavior, and optogenetic inhibition of subnetwork nodes disrupted specific components of this behavior. Lastly, ITPlxnD1 and PTFezf2 projection patterns are consistent with their subnetwork activation patterns. Our results show that, in addition to the concept of columnar organization, dynamic areal and PN type-specific subnetworks are a key feature of cortical functional architecture linking microcircuit components with global brain networks.

SummaryVariations in size and complexity of the cerebral cortex result from differences in neuron number and composition, which are rooted in evolutionary changes in direct and indirect neurogenesis (dNG and iNG) mediated by radial glial progenitors and intermediate progenitors, respectively. How dNG and iNG differentially contribute to cortical neuronal number, diversity, and connectivity are unknown. Establishing a genetic fate-mapping method to differentially visualize dNG and iNG in mice, we found that while both dNG and iNG contribute to all cortical structures, iNG contributes the largest relative proportions to the hippocampus and neocortex compared to insular and piriform cortex, claustrum, and the pallial amygdala. Within the neocortex, whereas dNG generates all major glutamatergic projection neuron (PN) classes, iNG differentially amplifies and diversifies PNs within each class; the two neurogenic pathways generate distinct PN types and assemble fine mosaics of lineage-based cortical subnetworks. Our results establish a ground-level lineage framework for understanding cortical development and evolution by linking foundational progenitor types and neurogenic pathways to PN types.Highlights- A genetic strategy for differential visualization of direct and indirect neurogenesis in the same animal.- dNG and iNG differentially contribute to piriform cortex, basolateral amygdala, hippocampus, and neocortex- Whereas dNG generates all major PN classes, iNG differentially amplifies and diversifies PNs within each class- dNG and iNG construct distinct cortical projection subnetworks.

The cellular basis of cerebral cortex functional architecture remains not well understood. A major challenge is to monitor and decipher neural network dynamics across broad cortical areas yet with projection neuron (PN)-type resolution in real time during behavior. Combining genetic targeting and wide-field imaging, we monitored activity dynamics of subcortical-projecting (PTFezf2) and intratelencephalic-projecting (ITPlxnD1) types across dorsal cortex of mice during different brain states and behaviors. ITPlxnD1 and PTFezf2 neurons showed distinct activation patterns during wakeful resting, spontaneous movements, and upon sensory stimulation. Distinct ITPlxnD1 and PTFezf2 subnetworks were dynamically tuned to different sensorimotor components of a naturalistic feeding behavior, and optogenetic inhibition of ITsPlxnD1 and PTsFezf2 in subnetwork nodes disrupted distinct components of this behavior. Lastly, ITPlxnD1 and PTFezf2 projection patterns are consistent with their subnetwork activation patterns. Our results show that, in addition to the concept of columnar organization, dynamic areal and PN type-specific subnetworks are a key feature of cortical functional architecture linking microcircuit components with global brain networks.

The anterior insular cortex (aIC) plays a critical role in cognitive and motivational control of behavior, but the underlying neural mechanism remains elusive. Here we show that aIC neurons expressing Fezf2 (aIC(Fezf2)), which are the pyramidal tract neurons, signal motivational vigor and invigorate need-seeking behavior through projections to the brainstem nucleus tractus solitarii (NTS). aIC(Fezf2) neurons and their postsynaptic NTS neurons acquire anticipatory activity through learning, which encodes the perceived value and the vigor of actions to pursue homeostatic needs. Correspondingly, aIC→NTS circuit activity controls vigor, effort and striatal dopamine release, but only if the action is learned and the outcome is needed. Notably, aIC(Fezf2) neurons do not represent taste or valence. Moreover, aIC→NTS activity neither drives reinforcement nor influences total consumption. These results pinpoint specific functions of aIC→NTS circuit for selectively controlling motivational vigor, and suggest that motivation is subserved, in part, by aIC’s top-down regulation of dopamine signaling.

The phenotypic diversity of cortical GABAergic neurons is probably necessary for their functional versatility in shaping the spatiotemporal dynamics of neural circuit operations underlying cognition. Deciphering the logic of this diversity requires comprehensive analysis of multi-modal cell features and a framework of neuronal identity that reflects biological mechanisms and principles. Recent high-throughput single-cell analyses have generated unprecedented data sets characterizing the transcriptomes, morphology and electrophysiology of interneurons. We posit that cardinal interneuron types can be defined by their synaptic communication properties, which are encoded in key transcriptional signatures. This conceptual framework integrates multi-modal cell features, captures neuronal input–output properties fundamental to circuit operation and may advance understanding of the appropriate granularity of neuron types, towards a biologically grounded and operationally useful interneuron taxonomy.

Summary: Parsing diverse nerve cells into biological types is necessary for understanding neural circuit organization. Morphology is an intuitive criterion for neuronal classification and a proxy of connectivity, but morphological diversity and variability often preclude resolving the granularity of neuron types. Combining genetic labeling with high-resolution, large-volume light microscopy, we established a single neuron anatomy platform that resolves, registers, and quantifies complete neuron morphologies in the mouse brain. We discovered that cortical axo-axonic cells (AACs), a cardinal GABAergic interneuron type that controls pyramidal neuron (PyN) spiking at axon initial segments, consist of multiple subtypes distinguished by highly laminar-specific soma position and dendritic and axonal arborization patterns. Whereas the laminar arrangements of AAC dendrites reflect differential recruitment by input streams, the laminar distribution and local geometry of AAC axons enable differential innervation of PyN ensembles. This platform will facilitate genetically targeted, high-resolution, and scalable single neuron anatomy in the mouse brain. : Wang et al. combine mouse genetic labeling with high-resolution, large-volume light microscopy and establish a single-neuron anatomy platform. They show that cortical axo-axonic cells, a GABAergic interneuron type that innervates pyramidal neurons at axon initial segments, consist of multiple subtypes distinguished by laminar position and dendritic and axonal arborization. Keywords: GABAergic interneurons, axo-axonic cells, AACs, chandelier cells, ChCs, neuron subtypes, genetic single neuron anatomy, gSNA, fMOST

Ever since the seminal findings of Ramon y Cajal, dendritic and axonal morphology has been recognized as a defining feature of neuronal types. Yet our knowledge concerning the diversity of neuronal morphologies, in particular distal axonal projection patterns, is extremely limited. To systematically obtain single neuron full morphology on a brain-wide scale, we established a platform with five major components: sparse labeling, whole-brain imaging, reconstruction, registration, and classification. We achieved sparse, robust and consistent fluorescent labeling of a wide range of neuronal types by combining transgenic or viral Cre delivery with novel transgenic reporter lines. We acquired high-resolution whole-brain fluorescent images from a large set of sparsely labeled brains using fluorescence micro-optical sectioning tomography (fMOST). We developed a set of software tools for efficient large-volume image data processing, registration to the Allen Mouse Brain Common Coordinate Framework (CCF), and computer-assisted morphological reconstruction. We reconstructed and analyzed the complete morphologies of 1,708 neurons from the striatum, thalamus, cortex and claustrum. Finally, we classified these cells into multiple morphological and projection types and identified a set of region-specific organizational rules of long-range axonal projections at the single cell level. Specifically, different neuron types from different regions follow highly distinct rules in convergent or divergent projection, feedforward or feedback axon termination patterns, and between-cell homogeneity or heterogeneity. Major molecularly defined classes or types of neurons have correspondingly distinct morphological and projection patterns, however, we also identify further remarkably extensive morphological and projection diversity at more fine-grained levels within the major types that cannot presently be accounted for by preexisting transcriptomic subtypes. These insights reinforce the importance of full morphological characterization of brain cell types and suggest a plethora of ways different cell types and individual neurons may contribute to the function of their respective circuits.

An essential step toward understanding brain function is to establish a cellular-resolution structural framework upon which multi-scale and multi-modal information spanning molecules, cells, circuits and systems can be integrated and interpreted. Here, through a collaborative effort from the Brain Initiative Cell Census Network (BICCN), we derive a comprehensive cell type-based description of one brain structure - the primary motor cortex upper limb area (MOp-ul) of the mouse. Applying state-of-the-art labeling, imaging, computational, and neuroinformatics tools, we delineated the MOp-ul within the Mouse Brain 3D Common Coordinate Framework (CCF). We defined over two dozen MOp-ul projection neuron (PN) types by their anterograde targets; the spatial distribution of their somata defines 11 cortical sublayers, a significant refinement of the classic notion of cortical laminar organization. We further combine multiple complementary tracing methods (classic tract tracing, cell type-based anterograde, retrograde, and transsynaptic viral tracing, high-throughput BARseq, and complete single cell reconstruction) to systematically chart cell type-based MOp input-output streams. As PNs link distant brain regions at synapses as well as host cellular gene expression, our construction of a PN type resolution MOp-ul wiring diagram will facilitate an integrated analysis of motor control circuitry across the molecular, cellular, and systems levels. This work further provides a roadmap towards a cellular resolution description of mammalian brain architecture.

Understanding of neuronal circuitry at cellular resolution within the brain has relied on tract tracing methods which involve careful observation and interpretation by experienced neuroscientists. With recent developments in imaging and digitization, this approach is no longer feasible with the large scale (terabyte to petabyte range) images. Machine learning based techniques, using deep networks, provide an efficient alternative to the problem. However, these methods rely on very large volumes of annotated images for training and have error rates that are too high for scientific data analysis, and thus requires a significant volume of human-in-the-loop proofreading. Here we introduce a hybrid architecture combining prior structure in the form of topological data analysis methods, based on discrete Morse theory, with the best-in-class deep-net architectures for the neuronal connectivity analysis. We show significant performance gains using our hybrid architecture on detection of topological structure (e.g. connectivity of neuronal processes and local intensity maxima on axons corresponding to synaptic swellings) with precision/recall close to 90% compared with human observers. We have adapted our architecture to a high performance pipeline capable of semantic segmentation of light microscopic whole-brain image data into a hierarchy of neuronal compartments. We expect that the hybrid architecture incorporating discrete Morse techniques into deep nets will generalize to other data domains.

Dendritic and axonal morphology reflects the input and output of neurons and is a defining feature of neuronal types1,2, yet our knowledge of its diversity remains limited. Here, to systematically examine complete single-neuron morphologies on a brain-wide scale, we established a pipeline encompassing sparse labelling, whole-brain imaging, reconstruction, registration and analysis. We fully reconstructed 1,741 neurons from cortex, claustrum, thalamus, striatum and other brain regions in mice. We identified 11 major projection neuron types with distinct morphological features and corresponding transcriptomic identities. Extensive projectional diversity was found within each of these major types, on the basis of which some types were clustered into more refined subtypes. This diversity follows a set of generalizable principles that govern long-range axonal projections at different levels, including molecular correspondence, divergent or convergent projection, axon termination pattern, regional specificity, topography, and individual cell variability. Although clear concordance with transcriptomic profiles is evident at the level of major projection type, fine-grained morphological diversity often does not readily correlate with transcriptomic subtypes derived from unsupervised clustering, highlighting the need for single-cell cross-modality studies. Overall, our study demonstrates the crucial need for quantitative description of complete single-cell anatomy in cell-type classification, as single-cell morphological diversity reveals a plethora of ways in which different cell types and their individual members may contribute to the configuration and function of their respective circuits., Sparse labelling and whole-brain imaging are used to reconstruct and classify brain-wide complete morphologies of 1,741 individual neurons in the mouse brain, revealing a dependence on both brain region and transcriptomic profile.

The basolateral amygdala (BLA) plays essential roles in behaviors motivated by stimuli with either positive or negative valence, but how it processes motivationally opposing information and participates in establishing valence-specific behaviors remains unclear. Here, by targeting Fezf2-expressing neurons in the BLA, we identify and characterize two functionally distinct classes in behaving mice, the negative-valence neurons and positive-valence neurons, which innately represent aversive and rewarding stimuli, respectively, and through learning acquire predictive responses that are essential for punishment avoidance or reward seeking. Notably, these two classes of neurons receive inputs from separate sets of sensory and limbic areas, and convey punishment and reward information through projections to the nucleus accumbens and olfactory tubercle, respectively, to drive negative and positive reinforcement. Thus, valence-specific BLA neurons are wired with distinctive input-output structures, forming a circuit framework that supports the roles of the BLA in encoding, learning and executing valence-specific motivated behaviors.

Single-cell transcriptomics can provide quantitative molecular signatures for large, unbiased samples of the diverse cell types in the brain1–3. With the proliferation of multi-omics datasets, a major challenge is to validate and integrate results into a biological understanding of cell-type organization. Here we generated transcriptomes and epigenomes from more than 500,000 individual cells in the mouse primary motor cortex, a structure that has an evolutionarily conserved role in locomotion. We developed computational and statistical methods to integrate multimodal data and quantitatively validate cell-type reproducibility. The resulting reference atlas—containing over 56 neuronal cell types that are highly replicable across analysis methods, sequencing technologies and modalities—is a comprehensive molecular and genomic account of the diverse neuronal and non-neuronal cell types in the mouse primary motor cortex. The atlas includes a population of excitatory neurons that resemble pyramidal cells in layer 4 in other cortical regions4. We further discovered thousands of concordant marker genes and gene regulatory elements for these cell types. Our results highlight the complex molecular regulation of cell types in the brain and will directly enable the design of reagents to target specific cell types in the mouse primary motor cortex for functional analysis., The authors describe an integrated atlas of the diverse cell types in the mouse primary motor cortex.

Single cell transcriptomics has transformed the characterization of brain cell identity by providing quantitative molecular signatures for large, unbiased samples of brain cell populations. With the proliferation of taxonomies based on individual datasets, a major challenge is to integrate and validate results toward defining biologically meaningful cell types. We used a battery of single-cell transcriptome and epigenome measurements generated by the BRAIN Initiative Cell Census Network (BICCN) to comprehensively assess the molecular signatures of cell types in the mouse primary motor cortex (MOp). We further developed computational and statistical methods to integrate these multimodal data and quantitatively validate the reproducibility of the cell types. The reference atlas, based on more than 600,000 high quality single-cell or -nucleus samples assayed by six molecular modalities, is a comprehensive molecular account of the diverse neuronal and non-neuronal cell types in MOp. Collectively, our study indicates that the mouse primary motor cortex contains over 55 neuronal cell types that are highly replicable across analysis methods, sequencing technologies, and modalities. We find many concordant multimodal markers for each cell type, as well as thousands of genes and gene regulatory elements with discrepant transcriptomic and epigenomic signatures. These data highlight the complex molecular regulation of brain cell types and will directly enable design of reagents to target specific MOp cell types for functional analysis.

The striosome compartment within the dorsal striatum has been implicated in reinforcement learning and regulation of motivation, but how striosomal neurons contribute to these functions remains elusive. Here, we show that a genetically identified striosomal population, which expresses the Teashirt family zinc finger 1 (Tshz1) and belongs to the direct pathway, drives negative reinforcement and is essential for aversive learning in mice. Contrasting a "conventional" striosomal direct pathway, the Tshz1 neurons cause aversion, movement suppression, and negative reinforcement once activated, and they receive a distinct set of synaptic inputs. These neurons are predominantly excited by punishment rather than reward and represent the anticipation of punishment or the motivation for avoidance. Furthermore, inhibiting these neurons impairs punishment-based learning without affecting reward learning or movement. These results establish a major role of striosomal neurons in behaviors reinforced by punishment and moreover uncover functions of the direct pathway unaccounted for in classic models.

Human mutations in CNTNAP2 are associated with an array of neuropsychiatric and neurological syndromes, including speech and language disorders, epilepsy, and autism spectrum disorder (ASD). We examined Cntnap2’s expression and function in GABAergic cortical interneurons (CINs), where its RNA is present at highest levels in chandelier neurons, PV(+) neurons and VIP(+) neurons. In vivo functions were studied using both constitutive Cntnap2 null mice and a transplantation assay, the latter to assess cell autonomous phenotypes of medial ganglionic eminence (MGE)-derived CINs. We found that Cntnap2 constitutive null mutants had normal numbers of MGE-derived CINs, but had reduced PV(+) CINs. Transplantation assays showed that Cntnap2 cell autonomously regulated the physiology of parvalbumin (PV)(+), fast-spiking CINs; no phenotypes were observed in somatostatin(+), regular spiking, CINs. We also tested the effects of 4 human CNTNAP2 ASD missense mutations in vivo, and found that they impaired PV(+) CIN development. Together, these data reveal that reduced CNTNAP2 function impairs PV(+) CINs, a cell type with important roles in regulating cortical circuits.

SUMMARYGABAergic interneurons deploy numerous inhibitory mechanisms that regulate cortical circuit operation, but the developmental programs that generate diverse interneuron types remain not well understood. We carried out a comprehensive genetic fate mapping of the radial glial progenitors (RGs) and intermediate progenitors (IP) in the medial ganglionic eminence (MGE). We reveal thatNkx2.1+RGs are multipotent and mediate two consecutive waves of neurogenesis, each sequentially generating different sets of interneuron types that laminate the neocortex in an inside-out-inside order. The first wave is restricted to the caudal MGE, has limited neurogenic capacity, and involves mostly apical IPs. The second wave initiates throughout the MGE and features a large set of fate-restricted basal IPs that amplify and diversify interneurons. Chandelier cells are generated toward the end of each wave and laminate in an outside-in order. Therefore, separate pools of multipotent RGs deploy temporal cohorts of IPs to sequentially generate diverse interneuron types.

In mammals with binocular vision, integration of the left and right visual scene relies on information in the center visual field, which are relayed from each retina in parallel and merge in the primary visual cortex (V1) through the convergence of ipsi- and contralateral geniculocortical inputs as well as transcallosal projections between two visual cortices. The developmental assembly of this binocular circuit, especially the transcallosal pathway, remains incompletely understood. Using genetic methods in mice, we found that several days before eye-opening, retinal and callosal activities drive massive apoptosis of GABAergic chandelier cells (ChCs) in the binocular region of V1. Blockade of ChC elimination resulted in a contralateral eye-dominated V1 and deficient binocular vision. As pre-vision retinal activities convey the left-right organization of the visual field, their regulation of ChC density through the transcallosal pathway may prime a nascent binocular territory for subsequent experience-driven tuning during the post-vision critical period.

The neurodevelopmental disorder Rett syndrome is caused by mutations in the geneMecp2. Misexpression of the protein MECP2 is thought to contribute to neuropathology by causing dysregulation of plasticity. Female heterozygousMecp2mutants (Mecp2het) failed to acquire a learned maternal retrieval behavior when exposed to pups, an effect linked to disruption of parvalbumin-expressing inhibitory interneurons (PV) in the auditory cortex. Nevertheless, how dysregulated PV networks affect the neural activity dynamics that underlie auditory cortical plasticity during early maternal experience is unknown. Here we show that maternal experience in WT adult female mice (WT) triggers suppression of PV auditory responses. We also observe concomitant disinhibition of auditory responses in deep-layer pyramidal neurons that is selective for behaviorally relevant pup vocalizations. These neurons further exhibit sharpened tuning for pup vocalizations following maternal experience. All of these neuronal changes are abolished inMecp2het, suggesting that they are an essential component of maternal learning. This is further supported by our finding that genetic manipulation of GABAergic networks that restores accurate retrieval behavior inMecp2hetalso restores maternal experience-dependent plasticity of PV. Our data are consistent with a growing body of evidence that cortical networks are particularly vulnerable to mutations ofMecp2in PV neurons. Moreover, our work links, for the first time, impairedin vivocortical plasticity in awakeMecp2mutant animals to a natural, ethologically relevant behavior.SIGNIFICANCE STATEMENTRett syndrome is a genetic disorder that includes language communication problems. Nearly all Rett syndrome is caused by mutations in the gene that produces the protein MECP2, which is important for changes in brain connectivity believed to underlie learning. We previously showed that femaleMecp2mutants fail to learn a simple maternal care behavior performed in response to their pups' distress cries. This impairment appeared to critically involve inhibitory neurons in the auditory cortex called parvalbumin neurons. Here we record from these neurons before and after maternal experience, and we show that they adapt their response to pup calls during maternal learning in nonmutants, but not in mutants. This adaptation is partially restored by a manipulation that improves learning.

In mammalian primary visual cortex (V1), integration of the left and right visual scene into a binocular percept derives from convergent ipsi- and contralateral geniculocortical inputs and trans-callosal projections between the two hemispheres. However, the underlying developmental mechanisms remain incompletely understood. Using genetic methods in mice we found that during the days before eye-opening, retinal and callosal activity drives massive apoptosis of GABAergic chandelier cells (ChCs) in the binocular region of V1. Blockade of ChC elimination resulted in a contralateral-dominated V1 and deficient binocular vision. As activity patterns within and between retinas prior to vision convey organization of the visual field, their regulation of ChC density through the trans-callosal pathway may prime a nascent binocular territory for subsequent experience-driven tuning during the post-vision critical period.One Sentence SummaryPrior to eye opening the developing retina primes the visual cortex for binocular vision by adjusting the density of a cortical inhibitory neuron type.

Dendritic and axonal morphology is a defining feature of neuronal types and their connectivity. Yet our knowledge concerning the diversity of neuronal morphology is extremely limited. To systematically obtain single neuron full morphology on a brain-wide scale in mice, we established a pipeline that encompasses five major components: sparse labeling, whole-brain imaging, reconstruction, registration, and classification. We achieved sparse, robust and consistent fluorescent labeling by combining transgenic or viral Cre delivery with novel transgenic reporter lines, and generated whole-brain fluorescent imaging datasets containing tens of thousands of reconstructable neurons. We developed software tools for large-volume image data processing and computer-assisted morphological reconstruction. For a proof-of-principle, we reconstructed the full morphologies of 96 neurons from the claustrum and cortex that belong to a single transcriptomically-defined subclass, and classified them into multiple morphological types, suggesting that they work in a targeted and coordinated manner to process cortical information over a large region.

Single-cell RNA sequencing (RNA-seq) is now a widely implemented tool for assaying gene expression. Commercially available single-cell RNA-sequencing platforms process all input cells indiscriminately. Sometimes, fluorescence-activated cell sorting (FACS) is used upstream to isolate a specifically labeled population of interest. A limitation of FACS is the need for high numbers of input cells with significantly labeled fractions, which is impractical for collecting and profiling rare or sparsely labeled neuron populations from the mouse brain. Here, we describe a method for manually collecting sparse fluorescently labeled single neurons from freshly dissociated mouse brain tissue. This process allows for capturing single-labeled neurons with high purity and subsequent integration with an in vitro transcription-based amplification protocol that preserves endogenous transcript ratios. We describe a double linear amplification method that uses unique molecule identifiers (UMIs) to generate individual mRNA counts. Two rounds of amplification results in a high degree of gene detection per single cell.

Single-cell RNA sequencing (RNA-seq) is now a widely implemented tool for assaying gene expression. Commercially available single-cell RNA-sequencing platforms process all input cells indiscriminately. Sometimes, fluorescence-activated cell sorting (FACS) is used upstream to isolate a specifically labeled population of interest. A limitation of FACS is the need for high numbers of input cells with significantly labeled fractions, which is impractical for collecting and profiling rare or sparsely labeled neuron populations from the mouse brain. Here, we describe a method for manually collecting sparse fluorescently labeled single neurons from freshly dissociated mouse brain tissue. This process allows for capturing single-labeled neurons with high purity and subsequent integration with an in vitro transcription-based amplification protocol that preserves endogenous transcript ratios. We describe a double linear amplification method that uses unique molecule identifiers (UMIs) to generate individual mRNA counts. Two rounds of amplification results in a high degree of gene detection per single cell.

Understanding neural circuits requires deciphering the interactions of myriad cell types defined by anatomy, spatial organization, gene expression, and functional properties. Resolving these cell types requires both single neuron resolution and high-throughput, a combination that is challenging to achieve with conventional anatomical methods. Here we introduce BARseq, a method for mapping the projections of thousands of spatially resolved neurons by combining the high throughput of DNA sequencing with the high spatial resolution of microscopy. We used BARseq to determine the projections of 1309 neurons in mouse auditory cortex to 11 targets. We observed 264 distinct projection patterns. Hierarchical clustering confirmed the major classical classes of projection neurons, segregated across cortical laminae. Further analysis revealed 25 subclasses, largely intermingled across laminae. Unlike cell types defined by gene expression, projection subclasses beyond the major classes were rarely enriched in specific laminae, raising the possibility that the organization of projection patterns in mature neurons is orthogonal to that of gene expression. In this way, downstream brain areas could receive information from multiple cell types through parallel pathways. By sequencing in situ, BARseq has the potential to bridge anatomical, transcriptomic, functional, and other approaches at single neuron resolution with high throughput, and thereby offer unprecedented insight of the structure and function of a neural circuit.

Understanding brain circuit organization and function requires systematic dissection of its cellular components. With vast cell number and diversity, mammalian nervous systems present a daunting challenge for achieving specific and comprehensive cell type access-prerequisite to circuit analysis. Genetic approaches in the mouse have relied on germline engineering to access marker-defined cell populations. Combinatorial strategies that engage marker intersection, anatomy and projection pattern (e.g. antero-grade and retro-grade viral vectors), and developmental lineage substantially increase the specificity of cell type targeting. While increasing number of mouse cell types are becoming experimentally accessible, comprehensive coverage requires larger coordinated efforts with strategic infrastructural and fiscal planning. CRISPR-based genome editing may enable cell type access in other species, but issues of time, cost and ethics remain, especially for primates. Novel approaches that bypass the germline, such as somatic cell engineering and cell surface-based gene delivery, may reduce the barrier of genetic access to mammalian cell types.

SUMMARYThe circuitry of the striatum is characterized by two organizational plans: the division into striosome and matrix compartments, thought to mediate evaluation and action, and the direct and indirect pathways, thought to promote or suppress behavior. The developmental origins of and relationships between these organizations are unknown, leaving a conceptual gap in understanding the cortico-basal ganglia system. Through genetic fate mapping, we demonstrate that striosome-matrix compartmentalization arises from a lineage program embedded in lateral ganglionic eminence radial glial progenitors mediating neurogenesis through two distinct types of intermediate progenitors (IPs). The early phase of this program produces striosomal spiny projection neurons (SPNs) through fate-restricted apical IPs (aIPSs) with limited capacity; the late phase produces matrix SPNs through fate-restricted basal IPs (bIPMs) with expanded capacity. Remarkably, direct and indirect pathway SPNs arise within both aIPSand bIPMpools, suggesting that striosome-matrix architecture is the fundamental organizational plan of basal ganglia circuitry organization.

Selective processing of behaviorally relevant sensory inputs against irrelevant ones is a fundamental cognitive function whose impairment has been implicated in major psychiatric disorders. It is known that the thalamic reticular nucleus (TRN) gates sensory information en route to the cortex, but the underlying mechanisms remain unclear. Here we show in mice that deficiency of the Erbb4 gene in somatostatin-expressing TRN neurons markedly alters behaviors that are dependent on sensory selection. Whereas the performance of the Erbb4-deficient mice in identifying targets from distractors was improved, their ability to switch attention between conflicting sensory cues was impaired. These behavioral changes were mediated by an enhanced cortical drive onto the TRN that promotes the TRN-mediated cortical feedback inhibition of thalamic neurons. Our results uncover a previously unknown role of ErbB4 in regulating cortico-TRN-thalamic circuit function. We propose that ErbB4 sets the sensitivity of the TRN to cortical inputs at levels that can support sensory selection while allowing behavioral flexibility.

Single-cell RNA-sequencing (scRNA-seq) technology provides a new avenue to discover and characterize cell types; however, the experiment-specific technical biases and analytic variability inherent to current pipelines may undermine its replicability. Meta-analysis is further hampered by the use of ad hoc naming conventions. Here we demonstrate our replication framework, MetaNeighbor, that quantifies the degree to which cell types replicate across datasets, and enables rapid identification of clusters with high similarity. We first measure the replicability of neuronal identity, comparing results across eight technically and biologically diverse datasets to define best practices for more complex assessments. We then apply this to novel interneuron subtypes, finding that 24/45 subtypes have evidence of replication, which enables the identification of robust candidate marker genes. Across tasks we find that large sets of variably expressed genes can identify replicable cell types with high accuracy, suggesting a general route forward for large-scale evaluation of scRNA-seq data., Single cell RNA-sequencing analysis poses challenges in replication due to technical biases and analytic variability among bioinformatics pipelines. Here, Crow et al develop MetaNeighbor for measuring cell-type replication across datasets, and use it to identify marker genes for neuron subtypes with evidence of replication.

Single cell RNA-sequencing technology (scRNA-seq) provides a new avenue to discover and characterize cell types, but the experiment-specific technical biases and analytic variability inherent to current pipelines may undermine the replicability of these studies. Meta-analysis of rapidly accumulating data is further hampered by the use of ad hoc naming conventions. Here we demonstrate our replication framework, MetaNeighbor, that allows researchers to quantify the degree to which cell types replicate across datasets, and to rapidly identify clusters with high similarity for further testing. We first measure the replicability of neuronal identity by comparing more than 13 thousand individual scRNA-seq transcriptomes, sampling with high specificity from within the data to define a range of robust practices. We then assess cross-dataset evidence for novel cortical interneuron subtypes identified by scRNA-seq and find that 24/45 cortical interneuron subtypes have evidence of replication in at least one other study. Identifying these putative replicates allows us to re-analyze the data for differential expression and provide lists of robust candidate marker genes. Across tasks we find that large sets of variably expressed genes can identify replicable cell types and subtypes with high accuracy, suggesting a general route forward for large-scale evaluation of scRNA-seq data.

The neocortex comprises multiple information processing streams mediated by subsets of glutamatergic pyramidal cells (PCs) that receive diverse inputs and project to distinct targets. How GABAergic interneurons regulate the segregation and communication among intermingled PC subsets that contribute to separate brain networks remains unclear. Here we demonstrate that a subset of GABAergic chandelier cells (ChCs) in the prelimbic cortex (PL), which innervate PCs at spike initiation site, selectively control PCs projecting to the basolateral amygdala (BLAPC) compared to those projecting to contralateral cortex (ccPC). These ChCs in turn receive preferential input from local and contralateralCCPCs as opposed toBLAPCs and BLA neurons (the PL-BLA network). Accordingly, optogenetic activation of ChCs rapidly suppressesBLAPCs and BLA activity in freely behaving mice. Thus, the exquisite connectivity of ChCs not only mediates directional inhibition between local PC ensembles but may also shape communication hierarchies between global networks.

Neurodevelopmental disorders are marked by inappropriate synaptic connectivity early in life, but how disruption of experience-dependent plasticity contributes to cognitive and behavioural decline in adulthood is unclear. Here we show that pup gathering behaviour and associated auditory cortical plasticity are impaired in female Mecp2het mice, a model of Rett syndrome. In response to learned maternal experience, Mecp2het females exhibited transient changes to cortical inhibitory networks typically associated with limited plasticity. Averting these changes in Mecp2het through genetic or pharmacological manipulations targeting the GABAergic network restored gathering behaviour. We propose that pup gathering learning triggers a transient epoch of inhibitory plasticity in auditory cortex that is dysregulated in Mecp2het. In this window of heightened sensitivity to sensory and social cues, Mecp2 mutations suppress adult plasticity independently from their effects on early development., Rett syndrome is associated with impaired synaptic connectivity beginning in early development. Here the authors show in female mice heterozygous for Mecp2, a model of Rett syndrome, that during adulthood, auditory cortex plasticity associated with a learned maternal behaviour is also impaired.

SummaryThe brain’s response to sensory input is strikingly modulated by behavioral state. Notably, the visual response of mouse primary visual cortex (V1) is enhanced by locomotion, a tractable and accessible example of a time-locked change in cortical state. The neural circuits that transmit behavioral state to sensory cortex to produce this modulation are unknown. In vivo calcium imaging of behaving animals revealed that locomotion activates vasoactive intestinal peptide (VIP)-positive neurons in mouse V1 independent of visual stimulation and largely through nicotinic inputs from basal forebrain. Optogenetic activation of VIP neurons increased V1 visual responses in stationary awake mice, artificially mimicking the effect of locomotion, and photolytic damage of VIP neurons abolished the enhancement of V1 responses by locomotion. These findings establish a cortical circuit for the enhancement of visual response by locomotion and provide a potential common circuit for the modulation of sensory processing by behavioral state.

The precision of skilled movement depends on sensory feedback and its refinement by local inhibitory microcircuits. One specialized set of spinal GABAergic interneurons forms axo-axonic contacts with the central terminals of sensory afferents, exerting presynaptic inhibitory control over sensory-motor transmission. The inability to achieve selective access to the GABAergic neurons responsible for this unorthodox inhibitory mechanism has left unresolved the contribution of presynaptic inhibition to motor behaviour. We used Gad2 as a genetic entry point to manipulate the interneurons that contact sensory terminals, and show that activation of these interneurons in mice elicits the defining physiological characteristics of presynaptic inhibition. Selective genetic ablation of Gad2-expressing interneurons severely perturbs goal-directed reaching movements, uncovering a pronounced and stereotypic forelimb motor oscillation, the core features of which are captured by modelling the consequences of sensory feedback at high gain. Our findings define the neural substrate of a genetically hardwired gain control system crucial for the smooth execution of movement.

We are on the verge of a fundamental leap toward understanding the human brain, and the implications for health and society are profound. Large-scale brain projects have been launched or are being planned in multiple continents and countries ( 1 – 4 ). In June, about 50 leading scientists from the United States, Europe, Japan, Korea, and China gathered in Suzhou, China (organized by Cold Spring Harbor Asia) to discuss the opportunities and challenges in brain research ( 5 ). The benefits of international coordination and collaboration were recognized, and the discussions laid a foundation for future meetings aimed at fleshing out details related to specific goals.