Integrated Morphoelectric and Transcriptomic Classification of Cortical GABAergic Cells

Long-Range GABAergic Projections of Cortical Origin in Brain Function

The study of long-range GABAergic projections has traditionally been focused on those with subcortical origin. In the last few years, cortical GABAergic neurons have been shown to not only mediate local inhibition, but also extend long-range axons to remote cortical and subcortical areas. In this review, we delineate the different types of long-range GABAergic neurons (LRGNs) that have been reported to arise from the hippocampus and neocortex, paying attention to the anatomical and functional circuits they form to understand their role in behavior. Although cortical LRGNs are similar to their interneuron and subcortical counterparts, they comprise distinct populations that show specific patterns of cortico-cortical and cortico-fugal connectivity. Functionally, cortical LRGNs likely induce timed disinhibition in target regions to synchronize network activity. Thus, LRGNs are emerging as a new element of cortical output, acting in concert with long-range excitatory projections to shape brain function in health and disease.

Fast and slow feedforward inhibitory circuits for cortical odor processing

Feedforward inhibitory circuits are key contributors to the complex interplay between excitation and inhibition in the brain. Little is known about the function of feedforward inhibition in the primary olfactory (piriform) cortex. Using in vivo two-photon-targeted patch clamping and calcium imaging in mice, we find that odors evoke strong excitation in two classes of interneurons – neurogliaform (NG) cells and horizontal (HZ) cells – that provide feedforward inhibition in layer 1 of the piriform cortex. NG cells fire much earlier than HZ cells following odor onset, a difference that can be attributed to the faster odor-driven excitatory synaptic drive that NG cells receive from the olfactory bulb. As a result, NG cells strongly but transiently inhibit odor-evoked excitation in layer 2 principal cells, whereas HZ cells provide more diffuse and prolonged feedforward inhibition. Our findings reveal unexpected complexity in the operation of inhibition in the piriform cortex.

Local connectivity and synaptic dynamics in mouse and human neocortex

We present a unique, extensive, and open synaptic physiology analysis platform and dataset. Through its application, we reveal principles that relate cell type to synaptic properties and intralaminar circuit organization in the mouse and human cortex. The dynamics of excitatory synapses align with the postsynaptic cell subclass, whereas inhibitory synapse dynamics partly align with presynaptic cell subclass but with considerable overlap. Synaptic properties are heterogeneous in most subclass-to-subclass connections. The two main axes of heterogeneity are strength and variability. Cell subclasses divide along the variability axis, whereas the strength axis accounts for substantial heterogeneity within the subclass. In the human cortex, excitatory-to-excitatory synaptic dynamics are distinct from those in the mouse cortex and vary with depth across layers 2 and 3.

Open Frontiers in Neural Cell Type Investigations; Lessons From Caenorhabditis elegans and Beyond, Toward a Multimodal Integration

Nervous system cells, the building blocks of circuits, have been studied with ever-progressing resolution, yet neural circuits appear still resistant to schemes of reductionist classification. Due to their sheer numbers, complexity and diversity, their systematic study requires concrete classifications that can serve reduced dimensionality, reproducibility, and information integration. Conventional hierarchical schemes transformed through the history of neuroscience by prioritizing criteria of morphology, (electro)physiological activity, molecular content, and circuit function, influenced by prevailing methodologies of the time. Since the molecular biology revolution and the recent advents in transcriptomics, molecular profiling gains ground toward the classification of neurons and glial cell types. Yet, transcriptomics entails technical challenges and more importantly uncovers unforeseen spatiotemporal heterogeneity, in complex and simpler nervous systems. Cells change states dynamically in space and time, in response to stimuli or throughout their developmental trajectory. Mapping cell type and state heterogeneity uncovers uncharted terrains in neurons and especially in glial cell biology, that remains understudied in many aspects. Examining neurons and glial cells from the perspectives of molecular neuroscience, physiology, development and evolution highlights the advantage of multifaceted classification schemes. Among the amalgam of models contributing to neuroscience research, Caenorhabditis elegans combines nervous system anatomy, lineage, connectivity and molecular content, all mapped at single-cell resolution, and can provide valuable insights for the workflow and challenges of the multimodal integration of cell type features. This review reflects on concepts and practices of neuron and glial cells classification and how research, in C. elegans and beyond, guides nervous system experimentation through integrated multidimensional schemes. It highlights underlying principles, emerging themes, and open frontiers in the study of nervous system development, regulatory logic and evolution. It proposes unified platforms to allow integrated annotation of large-scale datasets, gene-function studies, published or unpublished findings and community feedback. Neuroscience is moving fast toward interdisciplinary, high-throughput approaches for combined mapping of the morphology, physiology, connectivity, molecular function, and the integration of information in multifaceted schemes. A closer look in mapped neural circuits and understudied terrains offers insights for the best implementation of these approaches.

Transcriptomically-Guided Pharmacological Experiments in Neocortical and Hippocampal NPY-Positive GABAergic Interneurons

Cortical GABAergic interneurons have been shown to fulfil important roles by inhibiting excitatory principal neurons. Recent transcriptomic studies have confirmed seminal discoveries that used anatomic and electrophysiological methods highlighting the existence of multiple different classes of GABAergic interneurons. Although some of these studies have emphasized that inter-regional differences may exist for a given class, the extent of such differences remains unknown. To address this problem, we used single-cell Patch-RNAseq to characterize neuropeptide Y (NPY)-positive GABAergic interneurons in superficial layers of the primary auditory cortex (AC) and in distal layers of area CA3 in mice. We found that more than 300 genes are differentially expressed in NPY-positive neurons between these two brain regions. For example, the AMPA receptor (AMPAR) auxiliary subunit Shisa9/CKAMP44 and the 5HT2a receptor (5HT2aR) are significantly higher expressed in auditory NPY-positive neurons. These findings guided us to perform pharmacological experiments that revealed a role for 5HT2aRs in auditory NPY-positive neurons. Specifically, although the application of 5HT led to a depolarization of both auditory and CA3 NPY-positive neurons, the 5HT2aR antagonist ketanserin only reversed membrane potential changes in auditory NPY-positive neurons. Our study demonstrates the potential of single-cell transcriptomic studies in guiding directed pharmacological experiments.

Interneuron diversity in the rat dentate gyrus: An unbiased in vitro classification

Information processing in cortical circuits, including the hippocampus, relies on the dynamic control of neuronal activity by GABAergic interneurons (INs). INs form a heterogenous population with defined types displaying distinct morphological, molecular, and physiological characteristics. In the major input region of the hippocampus, the dentate gyrus (DG), a number of IN types have been described which provide synaptic inhibition to distinct compartments of excitatory principal cells (PrCs) and other INs. In this study, we perform an unbiased classification of GABAergic INs in the DG by combining in vitro whole-cell patch-clamp recordings, intracellular labeling, morphological analysis, and supervised cluster analysis to better define IN type diversity in this region. This analysis reveals that DG INs divide into at least 13 distinct morpho-physiological types which reflect the complexity of the local IN network and serve as a basis for further network analyses.

Synaptic connectivity to L2/3 of primary visual cortex measured by two-photon optogenetic stimulation

Understanding cortical microcircuits requires thorough measurement of physiological properties of synaptic connections formed within and between diverse subclasses of neurons. Towards this goal, we combined spatially precise optogenetic stimulation with multicellular recording to deeply characterize intralaminar and translaminar monosynaptic connections to supragranular (L2/3) neurons in the mouse visual cortex. The reliability and specificity of multiphoton optogenetic stimulation were measured across multiple Cre lines, and measurements of connectivity were verified by comparison to paired recordings and targeted patching of optically identified presynaptic cells. With a focus on translaminar pathways, excitatory and inhibitory synaptic connections from genetically defined presynaptic populations were characterized by their relative abundance, spatial profiles, strength, and short-term dynamics. Consistent with the canonical cortical microcircuit, layer 4 excitatory neurons and interneurons within L2/3 represented the most common sources of input to L2/3 pyramidal cells. More surprisingly, we also observed strong excitatory connections from layer 5 intratelencephalic neurons and potent translaminar inhibition from multiple interneuron subclasses. The hybrid approach revealed convergence to and divergence from excitatory and inhibitory neurons within and across cortical layers. Divergent excitatory connections often spanned hundreds of microns of horizontal space. In contrast, divergent inhibitory connections were more frequently measured from postsynaptic targets near each other.

Seeing the Forest and Its Trees Together: Implementing 3D Light Microscopy Pipelines for Cell Type Mapping in the Mouse Brain

The brain is composed of diverse neuronal and non-neuronal cell types with complex regional connectivity patterns that create the anatomical infrastructure underlying cognition. Remarkable advances in neuroscience techniques enable labeling and imaging of these individual cell types and their interactions throughout intact mammalian brains at a cellular resolution allowing neuroscientists to examine microscopic details in macroscopic brain circuits. Nevertheless, implementing these tools is fraught with many technical and analytical challenges with a need for high-level data analysis. Here we review key technical considerations for implementing a brain mapping pipeline using the mouse brain as a primary model system. Specifically, we provide practical details for choosing methods including cell type specific labeling, sample preparation (e.g., tissue clearing), microscopy modalities, image processing, and data analysis (e.g., image registration to standard atlases). We also highlight the need to develop better 3D atlases with standardized anatomical labels and nomenclature across species and developmental time points to extend the mapping to other species including humans and to facilitate data sharing, confederation, and integrative analysis. In summary, this review provides key elements and currently available resources to consider while developing and implementing high-resolution mapping methods.

Emerging strategies for the genetic dissection of gene functions, cell types, and neural circuits in the mammalian brain

The mammalian brain is composed of a large number of highly diverse cell types with different molecular, anatomical, and functional features. Distinct cellular identities are generated during development under the regulation of intricate genetic programs and manifested through unique combinations of gene expression. Recent advancements in our understanding of the molecular and cellular mechanisms underlying the assembly, function, and pathology of the brain circuitry depend on the invention and application of genetic strategies that engage intrinsic gene regulatory mechanisms. Here we review the strategies for gene regulation on DNA, RNA, and protein levels and their applications in cell type targeting and neural circuit dissection. We highlight newly emerged strategies and emphasize the importance of combinatorial approaches. We also discuss the potential caveats and pitfalls in current methods and suggest future prospects to improve their comprehensiveness and versatility.

A deep manifold-regularized learning model for improving phenotype prediction from multi-modal data

The phenotypes of complex biological systems are fundamentally driven by various multi-scale mechanisms. Multi-modal data, such as single cell multi-omics data, enables a deeper understanding of underlying complex mechanisms across scales for phenotypes. We developed an interpretable regularized learning model, deepManReg, to predict phenotypes from multi-modal data. First, deepManReg employs deep neural networks to learn cross-modal manifolds and then to align multi-modal features onto a common latent space. Second, deepManReg uses cross-modal manifolds as a feature graph to regularize the classifiers for improving phenotype predictions and also for prioritizing the multi-modal features and cross-modal interactions for the phenotypes. We applied deepManReg to (1) an image dataset of handwritten digits with multi-features and (2) single cell multi-modal data (Patch-seq data) including transcriptomics and electrophysiology for neuronal cells in the mouse brain. We show that deepManReg improved phenotype prediction in both datasets, and also prioritized genes and electrophysiological features for the phenotypes of neuronal cells.

A transcriptional rheostat couples past activity to future sensory responses

Animals traversing different environments encounter both stable background stimuli and novel cues, which are thought to be detected by primary sensory neurons and then distinguished by downstream brain circuits. Here, we show that each of the ∼1,000 olfactory sensory neuron (OSN) subtypes in the mouse harbors a distinct transcriptome whose content is precisely determined by interactions between its odorant receptor and the environment. This transcriptional variation is systematically organized to support sensory adaptation: expression levels of more than 70 genes relevant to transforming odors into spikes continuously vary across OSN subtypes, dynamically adjust to new environments over hours, and accurately predict acute OSN-specific odor responses. The sensory periphery therefore separates salient signals from predictable background via a transcriptional rheostat whose moment-to-moment state reflects the past and constrains the future; these findings suggest a general model in which structured transcriptional variation within a cell type reflects individual experience.

Transcriptional regulation of neuronal identity

Neuronal diversity is an intrinsic feature of the nervous system. Transcription factors (TFs) are key regulators in the establishment of different neuronal identities; how are the actions of different TFs coordinated to orchestrate this diversity? Are there common features shared among the different neuron types of an organism or even among different animal groups? In this review, we provide a brief overview on common traits emerging on the transcriptional regulation of neuron type diversification with a special focus on the comparison between mouse and Caenorhabditis elegans model systems. In the first part, we describe general concepts on neuronal identity and transcriptional regulation of gene expression. In the second part of the review, TFs are classified in different categories according to their key roles at specific steps along the protracted process of neuronal specification and differentiation. The same TF categories can be identified both in mammals and nematodes. Importantly, TFs are very pleiotropic: Depending on the neuron type or the time in development, the same TF can fulfil functions belonging to different categories. Finally, we describe the key role of transcriptional repression at all steps controlling neuronal diversity and propose that acquisition of neuronal identities could be considered a metastable process.

Cortical interneurons in autism

The mechanistic underpinnings of autism remain a subject of debate and controversy. Why do individuals with autism share an overlapping set of atypical behaviors and symptoms, despite having different genetic and environmental risk factors? A major challenge in developing new therapies for autism has been the inability to identify convergent neural phenotypes that could explain the common set of symptoms that result in the diagnosis. Although no striking macroscopic neuropathological changes have been identified in autism, there is growing evidence that inhibitory interneurons (INs) play an important role in its neural basis. In this Review, we evaluate and interpret this evidence, focusing on recent findings showing reduced density and activity of the parvalbumin class of INs. We discuss the need for additional studies that investigate how genes and the environment interact to change the developmental trajectory of INs, permanently altering their numbers, connectivity and circuit engagement.

Inhibition in the auditory cortex

The auditory system provides us with extremely rich and precise information about the outside world. Once a sound reaches our ears, the acoustic information it carries travels from the cochlea all the way to the auditory cortex, where its complexity and nuances are integrated. In the auditory cortex, functional circuits are formed by subpopulations of intermingled excitatory and inhibitory cells. In this review, we discuss recent evidence of the specific contributions of inhibitory neurons in sound processing and integration. We first examine intrinsic properties of three main classes of inhibitory interneurons in the auditory cortex. Then, we describe how inhibition shapes the responsiveness of the auditory cortex to sound. Finally, we discuss how inhibitory interneurons contribute to the sensation and perception of sounds. Altogether, this review points out the crucial role of cortical inhibitory interneurons in integrating information about the context, history, or meaning of a sound. It also highlights open questions to be addressed for increasing our understanding of the staggering complexity leading to the subtlest auditory perception.

Manifold learning analysis suggests strategies to align single-cell multimodal data of neuronal electrophysiology and transcriptomics

Recent single-cell multimodal data reveal multi-scale characteristics of single cells, such as transcriptomics, morphology, and electrophysiology. However, integrating and analyzing such multimodal data to deeper understand functional genomics and gene regulation in various cellular characteristics remains elusive. To address this, we applied and benchmarked multiple machine learning methods to align gene expression and electrophysiological data of single neuronal cells in the mouse brain from the Brain Initiative. We found that nonlinear manifold learning outperforms other methods. After manifold alignment, the cells form clusters highly corresponding to transcriptomic and morphological cell types, suggesting a strong nonlinear relationship between gene expression and electrophysiology at the cell-type level. Also, the electrophysiological features are highly predictable by gene expression on the latent space from manifold alignment. The aligned cells further show continuous changes of electrophysiological features, implying cross-cluster gene expression transitions. Functional enrichment and gene regulatory network analyses for those cell clusters revealed potential genome functions and molecular mechanisms from gene expression to neuronal electrophysiology.

Explorers of the cells: Toward cross-platform knowledge integration to evaluate neuronal function

In this issue of Neuron, Petersen et al. (2021) introduce CellExplorer, an open-source tool to integrate neurophysiological metrics of neuronal activity from circuits to behavior. Together with other neuroinformatic resources, it may facilitate community-based multidisciplinary characterization of brain cell types.

The Epigenome in Neurodevelopmental Disorders

Neurodevelopmental diseases (NDDs), such as autism spectrum disorders, epilepsy, and schizophrenia, are characterized by diverse facets of neurological and psychiatric symptoms, differing in etiology, onset and severity. Such symptoms include mental delay, cognitive and language impairments, or restrictions to adaptive and social behavior. Nevertheless, all have in common that critical milestones of brain development are disrupted, leading to functional deficits of the central nervous system and clinical manifestation in child- or adulthood. To approach how the different development-associated neuropathologies can occur and which risk factors or critical processes are involved in provoking higher susceptibility for such diseases, a detailed understanding of the mechanisms underlying proper brain formation is required. NDDs rely on deficits in neuronal identity, proportion or function, whereby a defective development of the cerebral cortex, the seat of higher cognitive functions, is implicated in numerous disorders. Such deficits can be provoked by genetic and environmental factors during corticogenesis. Thereby, epigenetic mechanisms can act as an interface between external stimuli and the genome, since they are known to be responsive to external stimuli also in cortical neurons. In line with that, DNA methylation, histone modifications/variants, ATP-dependent chromatin remodeling, as well as regulatory non-coding RNAs regulate diverse aspects of neuronal development, and alterations in epigenomic marks have been associated with NDDs of varying phenotypes. Here, we provide an overview of essential steps of mammalian corticogenesis, and discuss the role of epigenetic mechanisms assumed to contribute to pathophysiological aspects of NDDs, when being disrupted.

mGlu1 potentiation enhances prelimbic somatostatin interneuron activity to rescue schizophrenia-like physiological and cognitive deficits

Evidence for prefrontal cortical (PFC) GABAergic dysfunction is one of the most consistent findings in schizophrenia and may contribute to cognitive deficits. Recent studies suggest that the mGlu1 subtype of metabotropic glutamate receptor regulates cortical inhibition; however, understanding the mechanisms through which mGlu1 positive allosteric modulators (PAMs) regulate PFC microcircuit function and cognition is essential for advancing these potential therapeutics toward the clinic. We report a series of electrophysiology, optogenetic, pharmacological magnetic resonance imaging, and animal behavior studies demonstrating that activation of mGlu1 receptors increases inhibitory transmission in the prelimbic PFC by selective excitation of somatostatin-expressing interneurons (SST-INs). An mGlu1 PAM reverses cortical hyperactivity and concomitant cognitive deficits induced by N-methyl-d-aspartate (NMDA) receptor antagonists. Using in vivo optogenetics, we show that prelimbic SST-INs are necessary for mGlu1 PAM efficacy. Collectively, these findings suggest that mGlu1 PAMs could reverse cortical GABAergic deficits and exhibit efficacy in treating cognitive dysfunction in schizophrenia.

Toward Understanding the Diverse Roles of Perisomatic Interneurons in Epilepsy

Epileptic seizures are associated with excessive neuronal spiking. Perisomatic γ-aminobutyric acid (GABA)ergic interneurons specifically innervate the subcellular domains of postsynaptic excitatory cells that are critical for spike generation. With a revolution in transcriptomics-based cell taxonomy driving the development of novel transgenic mouse lines, selectively monitoring and modulating previously elusive interneuron types is becoming increasingly feasible. Emerging evidence suggests that the three types of hippocampal perisomatic interneurons, axo-axonic cells, along with parvalbumin- and cholecystokinin-expressing basket cells, each follow unique activity patterns in vivo, suggesting distinctive roles in regulating epileptic networks.

Tau reduction affects excitatory and inhibitory neurons differently, reduces excitation/inhibition ratios, and counteracts network hypersynchrony

The protein tau has been implicated in many brain disorders. In animal models, tau reduction suppresses epileptogenesis of diverse causes and ameliorates synaptic and behavioral abnormalities in various conditions associated with excessive excitation-inhibition (E/I) ratios. However, the underlying mechanisms are unknown. Global genetic ablation of tau in mice reduces the action potential (AP) firing and E/I ratio of pyramidal cells in acute cortical slices without affecting the excitability of these cells. Tau ablation reduces the excitatory inputs to inhibitory neurons, increases the excitability of these cells, and structurally alters their axon initial segments (AISs). In primary neuronal cultures subjected to prolonged overstimulation, tau ablation diminishes the homeostatic response of AISs in inhibitory neurons, promotes inhibition, and suppresses hypersynchrony. Together, these differential alterations in excitatory and inhibitory neurons help explain how tau reduction prevents network hypersynchrony and counteracts brain disorders causing abnormally increased E/I ratios.

Layer 6A Pyramidal Cell Subtypes Form Synaptic Microcircuits with Distinct Functional and Structural Properties

Neocortical layer 6 plays a crucial role in sensorimotor co-ordination and integration through functionally segregated circuits linking intracortical and subcortical areas. We performed whole-cell recordings combined with morphological reconstructions to identify morpho-electric types of layer 6A pyramidal cells (PCs) in rat barrel cortex. Cortico-thalamic (CT), cortico-cortical (CC), and cortico-claustral (CCla) PCs were classified based on their distinct morphologies and have been shown to exhibit different electrophysiological properties. We demonstrate that these three types of layer 6A PCs innervate neighboring excitatory neurons with distinct synaptic properties: CT PCs establish weak facilitating synapses onto other L6A PCs; CC PCs form synapses of moderate efficacy, while synapses made by putative CCla PCs display the highest release probability and a marked short-term depression. For excitatory-inhibitory synaptic connections in layer 6, both the presynaptic PC type and the postsynaptic interneuron type govern the dynamic properties of the respective synaptic connections. We have identified a functional division of local layer 6A excitatory microcircuits which may be responsible for the differential temporal engagement of layer 6 feed-forward and feedback networks. Our results provide a basis for further investigations on the long-range CC, CT, and CCla pathways.

From Cell Types to an Integrated Understanding of Brain Evolution: The Case of the Cerebral Cortex

With the discovery of the incredible diversity of neurons, Cajal and coworkers laid the foundation of modern neuroscience. Neuron types are not only structural units of nervous systems but also evolutionary units, because their identities are encoded in the genome. With the advent of high-throughput cellular transcriptomics, neuronal identities can be characterized and compared systematically across species. The comparison of neurons in mammals, reptiles, and birds indicates that the mammalian cerebral cortex is a mosaic of deeply conserved and recently evolved neuron types. Using the cerebral cortex as a case study, this review illustrates how comparing neuron types across species is key to reconciling observations on neural development, neuroanatomy, circuit wiring, and physiology for an integrated understanding of brain evolution.

Comparative cellular analysis of motor cortex in human, marmoset and mouse

The primary motor cortex (M1) is essential for voluntary fine-motor control and is functionally conserved across mammals1. Here, using high-throughput transcriptomic and epigenomic profiling of more than 450,000 single nuclei in humans, marmoset monkeys and mice, we demonstrate a broadly conserved cellular makeup of this region, with similarities that mirror evolutionary distance and are consistent between the transcriptome and epigenome. The core conserved molecular identities of neuronal and non-neuronal cell types allow us to generate a cross-species consensus classification of cell types, and to infer conserved properties of cell types across species. Despite the overall conservation, however, many species-dependent specializations are apparent, including differences in cell-type proportions, gene expression, DNA methylation and chromatin state. Few cell-type marker genes are conserved across species, revealing a short list of candidate genes and regulatory mechanisms that are responsible for conserved features of homologous cell types, such as the GABAergic chandelier cells. This consensus transcriptomic classification allows us to use patch-seq (a combination of whole-cell patch-clamp recordings, RNA sequencing and morphological characterization) to identify corticospinal Betz cells from layer 5 in non-human primates and humans, and to characterize their highly specialized physiology and anatomy. These findings highlight the robust molecular underpinnings of cell-type diversity in M1 across mammals, and point to the genes and regulatory pathways responsible for the functional identity of cell types and their species-specific adaptations.

Interneuron Dysfunction and Inhibitory Deficits in Autism and Fragile X Syndrome

The alteration of excitatory–inhibitory (E–I) balance has been implicated in various neurological and psychiatric diseases, including autism spectrum disorder (ASD). Fragile X syndrome (FXS) is a single-gene disorder that is the most common known cause of ASD. Understanding the molecular and physiological features of FXS is thought to enhance our knowledge of the pathophysiology of ASD. Accumulated evidence implicates deficits in the inhibitory circuits in FXS that tips E–I balance toward excitation. Deficits in interneurons, the main source of an inhibitory neurotransmitter, gamma-aminobutyric acid (GABA), have been reported in FXS, including a reduced number of cells, reduction in intrinsic cellular excitability, or weaker synaptic connectivity. Manipulating the interneuron activity ameliorated the symptoms in the FXS mouse model, which makes it reasonable to conceptualize FXS as an interneuronopathy. While it is still poorly understood how the developmental profiles of the inhibitory circuit go awry in FXS, recent works have uncovered several developmental alterations in the functional properties of interneurons. Correcting disrupted E–I balance by potentiating the inhibitory circuit by targeting interneurons may have a therapeutic potential in FXS. I will review the recent evidence about the inhibitory alterations and interneuron dysfunction in ASD and FXS and will discuss the future directions of this field.

Morphological diversity of single neurons in molecularly defined cell types

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.

Single-Cell Transcriptome Profiling of Thyroid Hormone Effectors in the Human Fetal Neocortex: Expression of SLCO1C1, DIO2, and THRB in Specific Cell Types

Background: Thyroid hormones are crucial for brain development, acting through the thyroid hormone nuclear receptors (TR)α1 and β to control gene expression. Triiodothyronine (T3), the receptor-ligand, is transported into the brain from the blood by the monocarboxylate transporter 8 (MCT8). Another source of brain T3 is from the local deiodination of thyroxine (T4) by type 2 deiodinase (DIO2). While these mechanisms are very similar in mice and humans, important species-specific differences confound our understanding of disease using mouse models. To fill this knowledge gap on thyroid hormone action in the human fetal brain, we analyzed the expression of transporters, DIO2, and TRs, which we call thyroid hormone effectors, at single-cell resolution. Methods: We analyzed publicly available single-cell transcriptome data sets of isolated cerebral cortex neural cells from three different studies, with expression data from 393 to almost 40,000 cells. We generated Uniform Manifold Approximation and Projection scatterplots and cell clusters to identify differentially expressed genes between clusters, and correlated their gene signatures with the expression of thyroid effectors. Results: The radial glia, mainly the outer radial glia, and astrocytes coexpress SLCO1C1 and DIO2, indicating close cooperation between the T4 transporter OATP1C1 and DIO2 in local T3 formation. Strikingly, THRB was mainly present in two classes of interneurons: a majority expressing CALB2/calretinin, from the caudal ganglionic eminence, and in somatostatin-expressing interneurons from the medial ganglionic eminence. By contrast, many cell types express SLC16A2 and THRA. Conclusions:SLCO1C1 and DIO2 coexpression in the outer radial glia, the universal stem cell of the cerebral cortex, highlights the likely importance of brain-generated T3 in neurogenesis. The unique expression of THRB in discrete subsets of interneurons is a novel finding whose pathophysiological meaning deserves further investigation.

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.

A multimodal cell census and atlas of the mammalian primary motor cortex

Here we report the generation of a multimodal cell census and atlas of the mammalian primary motor cortex as the initial product of the BRAIN Initiative Cell Census Network (BICCN). This was achieved by coordinated large-scale analyses of single-cell transcriptomes, chromatin accessibility, DNA methylomes, spatially resolved single-cell transcriptomes, morphological and electrophysiological properties and cellular resolution input-output mapping, integrated through cross-modal computational analysis. Our results advance the collective knowledge and understanding of brain cell-type organization^1-5. First, our study reveals a unified molecular genetic landscape of cortical cell types that integrates their transcriptome, open chromatin and DNA methylation maps. Second, cross-species analysis achieves a consensus taxonomy of transcriptomic types and their hierarchical organization that is conserved from mouse to marmoset and human. Third, in situ single-cell transcriptomics provides a spatially resolved cell-type atlas of the motor cortex. Fourth, cross-modal analysis provides compelling evidence for the transcriptomic, epigenomic and gene regulatory basis of neuronal phenotypes such as their physiological and anatomical properties, demonstrating the biological validity and genomic underpinning of neuron types. We further present an extensive genetic toolset for targeting glutamatergic neuron types towards linking their molecular and developmental identity to their circuit function. Together, our results establish a unifying and mechanistic framework of neuronal cell-type organization that integrates multi-layered molecular genetic and spatial information with multi-faceted phenotypic properties.

A multimodal cell census and atlas of the mammalian primary motor cortex

Here we report the generation of a multimodal cell census and atlas of the mammalian primary motor cortex as the initial product of the BRAIN Initiative Cell Census Network (BICCN). This was achieved by coordinated large-scale analyses of single-cell transcriptomes, chromatin accessibility, DNA methylomes, spatially resolved single-cell transcriptomes, morphological and electrophysiological properties and cellular resolution input-output mapping, integrated through cross-modal computational analysis. Our results advance the collective knowledge and understanding of brain cell-type organization1-5. First, our study reveals a unified molecular genetic landscape of cortical cell types that integrates their transcriptome, open chromatin and DNA methylation maps. Second, cross-species analysis achieves a consensus taxonomy of transcriptomic types and their hierarchical organization that is conserved from mouse to marmoset and human. Third, in situ single-cell transcriptomics provides a spatially resolved cell-type atlas of the motor cortex. Fourth, cross-modal analysis provides compelling evidence for the transcriptomic, epigenomic and gene regulatory basis of neuronal phenotypes such as their physiological and anatomical properties, demonstrating the biological validity and genomic underpinning of neuron types. We further present an extensive genetic toolset for targeting glutamatergic neuron types towards linking their molecular and developmental identity to their circuit function. Together, our results establish a unifying and mechanistic framework of neuronal cell-type organization that integrates multi-layered molecular genetic and spatial information with multi-faceted phenotypic properties.

Human neocortical expansion involves glutamatergic neuron diversification

The neocortex is disproportionately expanded in human compared with mouse1,2, both in its total volume relative to subcortical structures and in the proportion occupied by supragranular layers composed of neurons that selectively make connections within the neocortex and with other telencephalic structures. Single-cell transcriptomic analyses of human and mouse neocortex show an increased diversity of glutamatergic neuron types in supragranular layers in human neocortex and pronounced gradients as a function of cortical depth3. Here, to probe the functional and anatomical correlates of this transcriptomic diversity, we developed a robust platform combining patch clamp recording, biocytin staining and single-cell RNA-sequencing (Patch-seq) to examine neurosurgically resected human tissues. We demonstrate a strong correspondence between morphological, physiological and transcriptomic phenotypes of five human glutamatergic supragranular neuron types. These were enriched in but not restricted to layers, with one type varying continuously in all phenotypes across layers 2 and 3. The deep portion of layer 3 contained highly distinctive cell types, two of which express a neurofilament protein that labels long-range projection neurons in primates that are selectively depleted in Alzheimer's disease4,5. Together, these results demonstrate the explanatory power of transcriptomic cell-type classification, provide a structural underpinning for increased complexity of cortical function in humans, and implicate discrete transcriptomic neuron types as selectively vulnerable in disease.

Comprehensive characterization of oscillatory signatures in a model circuit with PV- and SOM-expressing interneurons

Neural circuits contain a wide variety of interneuron types, which differ in their biophysical properties and connectivity patterns. The two most common interneuron types, parvalbumin-expressing and somatostatin-expressing cells, have been shown to be differentially involved in many cognitive functions. These cell types also show different relationships with the power and phase of oscillations in local field potentials. The mechanisms that underlie the emergence of different oscillatory rhythms in neural circuits with more than one interneuron subtype, and the roles specific interneurons play in those mechanisms, are not fully understood. Here, we present a comprehensive analysis of all possible circuit motifs and input regimes that can be achieved in circuits comprised of excitatory cells, PV-like fast-spiking interneurons and SOM-like low-threshold spiking interneurons. We identify 18 unique motifs and simulate their dynamics over a range of input strengths. Using several characteristics, such as oscillation frequency, firing rates, phase of firing and burst fraction, we cluster the resulting circuit dynamics across motifs in order to identify patterns of activity and compare these patterns to behaviors that were generated in circuits with one interneuron type. In addition to the well-known PING and ING gamma oscillations and an asynchronous state, our analysis identified three oscillatory behaviors that were generated by the three-cell-type motifs only: theta-nested gamma oscillations, stable beta oscillations and theta-locked bursting behavior, which have also been observed in experiments. Our characterization provides a map to interpret experimental activity patterns and suggests pharmacological manipulations or optogenetics approaches to validate these conclusions.

Identification of neural oscillations and epileptiform changes in human brain organoids

Brain organoids represent a powerful tool for studying human neurological diseases, particularly those that affect brain growth and structure. However, many diseases manifest with clear evidence of physiological and network abnormality in the absence of anatomical changes, raising the question of whether organoids possess sufficient neural network complexity to model these conditions. Here, we explore the network-level functions of brain organoids using calcium sensor imaging and extracellular recording approaches that together reveal the existence of complex network dynamics reminiscent of intact brain preparations. We demonstrate highly abnormal and epileptiform-like activity in organoids derived from induced pluripotent stem cells from individuals with Rett syndrome, accompanied by transcriptomic differences revealed by single-cell analyses. We also rescue key physiological activities with an unconventional neuroregulatory drug, pifithrin-α. Together, these findings provide an essential foundation for the utilization of brain organoids to study intact and disordered human brain network formation and illustrate their utility in therapeutic discovery.

Mechanisms Underlying Target Selectivity for Cell Types and Subcellular Domains in Developing Neocortical Circuits

The cerebral cortex contains numerous neuronal cell types, distinguished by their molecular identity as well as their electrophysiological and morphological properties. Cortical function is reliant on stereotyped patterns of synaptic connectivity and synaptic function among these neuron types, but how these patterns are established during development remains poorly understood. Selective targeting not only of different cell types but also of distinct postsynaptic neuronal domains occurs in many brain circuits and is directed by multiple mechanisms. These mechanisms include the regulation of axonal and dendritic guidance and fine-scale morphogenesis of pre- and postsynaptic processes, lineage relationships, activity dependent mechanisms and intercellular molecular determinants such as transmembrane and secreted molecules, many of which have also been implicated in neurodevelopmental disorders. However, many studies of synaptic targeting have focused on circuits in which neuronal processes target different lamina, such that cell-type-biased connectivity may be confounded with mechanisms of laminar specificity. In the cerebral cortex, each cortical layer contains cell bodies and processes from intermingled neuronal cell types, an arrangement that presents a challenge for the development of target-selective synapse formation. Here, we address progress and future directions in the study of cell-type-biased synaptic targeting in the cerebral cortex. We highlight challenges to identifying developmental mechanisms generating stereotyped patterns of intracortical connectivity, recent developments in uncovering the determinants of synaptic target selection during cortical synapse formation, and current gaps in the understanding of cortical synapse specificity.

Signature morpho-electric, transcriptomic, and dendritic properties of human layer 5 neocortical pyramidal neurons

In the neocortex, subcerebral axonal projections originate largely from layer 5 (L5) extratelencephalic-projecting (ET) neurons. The unique morpho-electric properties of these neurons have been mainly described in rodents, where retrograde tracers or transgenic lines can label them. Similar labeling strategies are infeasible in the human neocortex, rendering the translational relevance of findings in rodents unclear. We leveraged the recent discovery of a transcriptomically defined L5 ET neuron type to study the properties of human L5 ET neurons in neocortical brain slices derived from neurosurgeries. Patch-seq recordings, where transcriptome, physiology, and morphology were assayed from the same cell, revealed many conserved morpho-electric properties of human and rodent L5 ET neurons. Divergent properties were often subtler than differences between L5 cell types within these two species. These data suggest a conserved function of L5 ET neurons in the neocortical hierarchy but also highlight phenotypic divergence possibly related to functional specialization of human neocortex.

Development, Diversity, and Death of MGE-Derived Cortical Interneurons

In the mammalian brain, cortical interneurons (INs) are a highly diverse group of cells. A key neurophysiological question concerns how each class of INs contributes to cortical circuit function and whether specific roles can be attributed to a selective cell type. To address this question, researchers are integrating knowledge derived from transcriptomic, histological, electrophysiological, developmental, and functional experiments to extensively characterise the different classes of INs. Our hope is that such knowledge permits the selective targeting of cell types for therapeutic endeavours. This review will focus on two of the main types of INs, namely the parvalbumin (PV⁺) or somatostatin (SOM⁺)-containing cells, and summarise the research to date on these classes.

Adaptive Mechanisms of Somatostatin-Positive Interneurons after Traumatic Brain Injury through a Switch of α Subunits in L-Type Voltage-Gated Calcium Channels

Unilateral traumatic brain injury (TBI) causes cortical dysfunctions spreading to the primarily undamaged hemisphere. This phenomenon, called transhemispheric diaschisis, is mediated by an imbalance of glutamatergic versus GABAergic neurotransmission. This study investigated the role of GABAergic, somatostatin-positive (SST) interneurons in the contralateral hemisphere 72 h after unilateral TBI. The brain injury was induced to the primary motor/somatosensory cortex of glutamate decarboxylase 67-green fluorescent protein (GAD67-GFP) knock-in mice at postnatal days 19-21 under anesthesia in vivo. Single GFP+ interneurons of the undamaged, contralateral cortex were isolated by fluorescence-activated cell sorting and analyzed by mass spectrometry. TBI caused a switch of 2 α subunits of pore-forming L-type voltage-gated calcium channels (VGCC) in GABAergic interneurons, an increased expression of CaV1.3, and simultaneous ablation of CaV1.2. This switch was associated with 1) increased excitability of single SST interneurons in patch-clamp recordings and (2) a recovery from early network hyperactivity in the contralateral hemisphere in microelectrode array recordings of acute slices. The electrophysiological changes were sensitive to pharmacological blockade of CaV1.3 (isradipine, 100 nM). These data identify a switch of 2 α subunits of VGCCs in SST interneurons early after TBI as a mechanism to counterbalance post-traumatic hyperexcitability.

Scaled, high fidelity electrophysiological, morphological, and transcriptomic cell characterization

The Patch-seq approach is a powerful variation of the patch-clamp technique that allows for the combined electrophysiological, morphological, and transcriptomic characterization of individual neurons. To generate Patch-seq datasets at scale, we identified and refined key factors that contribute to the efficient collection of high-quality data. We developed patch-clamp electrophysiology software with analysis functions specifically designed to automate acquisition with online quality control. We recognized the importance of extracting the nucleus for transcriptomic success and maximizing membrane integrity during nucleus extraction for morphology success. The protocol is generalizable to different species and brain regions, as demonstrated by capturing multimodal data from human and macaque brain slices. The protocol, analysis and acquisition software are compiled at https://githubcom/AllenInstitute/patchseqtools. This resource can be used by individual labs to generate data across diverse mammalian species and that is compatible with large publicly available Patch-seq datasets.

Non-linear dimensionality reduction on extracellular waveforms reveals cell type diversity in premotor cortex

Cortical circuits are thought to contain a large number of cell types that coordinate to produce behavior. Current in vivo methods rely on clustering of specified features of extracellular waveforms to identify putative cell types, but these capture only a small amount of variation. Here, we develop a new method (WaveMAP) that combines non-linear dimensionality reduction with graph clustering to identify putative cell types. We apply WaveMAP to extracellular waveforms recorded from dorsal premotor cortex of macaque monkeys performing a decision-making task. Using WaveMAP, we robustly establish eight waveform clusters and show that these clusters recapitulate previously identified narrow- and broad-spiking types while revealing previously unknown diversity within these subtypes. The eight clusters exhibited distinct laminar distributions, characteristic firing rate patterns, and decision-related dynamics. Such insights were weaker when using feature-based approaches. WaveMAP therefore provides a more nuanced understanding of the dynamics of cell types in cortical circuits.

Long-term stability of cortical ensembles

Neuronal ensembles, coactive groups of neurons found in spontaneous and evoked cortical activity, are causally related to memories and perception, but it is still unknown how stable or flexible they are over time. We used two-photon multiplane calcium imaging to track over weeks the activity of the same pyramidal neurons in layer 2/3 of the visual cortex from awake mice and recorded their spontaneous and visually evoked responses. Less than half of the neurons remained active across any two imaging sessions. These stable neurons formed ensembles that lasted weeks, but some ensembles were also transient and appeared only in one single session. Stable ensembles preserved most of their neurons for up to 46 days, our longest imaged period, and these 'core' cells had stronger functional connectivity. Our results demonstrate that neuronal ensembles can last for weeks and could, in principle, serve as a substrate for long-lasting representation of perceptual states or memories.

Electrophysiological and Transcriptomic Features Reveal a Circular Taxonomy of Cortical Neurons

The complete understanding of the mammalian brain requires exact knowledge of the function of each neuron subpopulation composing its parts. To achieve this goal, an exhaustive, precise, reproducible, and robust neuronal taxonomy should be defined. In this paper, a new circular taxonomy based on transcriptomic features and novel electrophysiological features is proposed. The approach is validated by analysing more than 1850 electrophysiological signals of different mouse visual cortex neurons proceeding from the Allen Cell Types database. The study is conducted on two different levels: neurons and their cell-type aggregation into Cre lines. At the neuronal level, electrophysiological features have been extracted with a promising model that has already proved its worth in neuronal dynamics. At the Cre line level, electrophysiological and transcriptomic features are joined on cell types with available genetic information. A taxonomy with a circular order is revealed by a simple transformation of the first two principal components that allow the characterization of the different Cre lines. Moreover, the proposed methodology locates other Cre lines in the taxonomy that do not have transcriptomic features available. Finally, the taxonomy is validated by Machine Learning methods which are able to discriminate the different neuron types with the proposed electrophysiological features.

Generating and Using Transcriptomically Based Retinal Cell Atlases

It has been known for over a century that the basic organization of the retina is conserved across vertebrates. It has been equally clear that retinal cells can be classified into numerous types, but only recently have methods been devised to explore this diversity in unbiased, scalable, and comprehensive ways. Advances in high-throughput single-cell RNA-sequencing (scRNA-seq) have played a pivotal role in this effort. In this article, we outline the experimental and computational components of scRNA-seq and review studies that have used them to generate retinal atlases of cell types in several vertebrate species. These atlases have enabled studies of retinal development, responses of retinal cells to injury, expression patterns of genes implicated in retinal disease, and the evolution of cell types. Recently, the inquiry has expanded to include the entire eye and visual centers in the brain. These studies have enhanced our understanding of retinal function and dysfunction and provided tools and insights for exploring neural diversity throughout the brain. Expected final online publication date for the Annual Review of Vision Science, Volume 7 is September 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Electrophysiological Properties of Neurons: Current-Clamp Recordings in Mouse Brain Slices and Firing-Pattern Analysis

Characterization of an electrically active cell, such as a neuron, demands measurement of its electrical properties. Due to differences in gene activation, location, innervation patterns, and functions, the millions of neurons in the mammalian brain are tremendously diverse in their membrane characteristics and abilities to generate action potentials. These features can be measured with a patch-clamp technique in whole-cell current-clamp configuration followed by detailed post-hoc analysis of firing patterns. This analysis can be time-consuming, and different laboratories have their own methods to perform it, either manually or with custom-written scripts. Here, we describe in detail a protocol for firing-pattern registration in neurons of the ventral tegmental area (VTA) as an example and introduce a software for its fast and convenient analysis. With the help of this article, other research groups can easily apply this method and generate unified types of data that are comparable between brain regions and various studies. Graphic abstract: Workflow of the Protocol.

Progress towards a cellularly resolved mouse mesoconnectome is empowered by data fusion and new neuroanatomy techniques

Over the past decade there has been a rapid improvement in techniques for obtaining large-scale cellular level data related to the mouse brain connectome. However, a detailed mapping of cell-type-specific projection patterns is lacking, which would, for instance, allow us to study the role of circuit motifs in cognitive processes. In this work, we review advanced neuroanatomical and data fusion techniques within the context of a proposed Multimodal Connectomic Integration Framework for augmenting the cellularly resolved mouse mesoconnectome. First, we emphasize the importance of registering data modalities to a common reference atlas. We then review a number of novel experimental techniques that can provide data for characterizing cell-types in the mouse brain. Furthermore, we examine a number of data integration strategies, which involve fine-grained cell-type classification, spatial inference of cell densities, latent variable models for the mesoconnectome and multi-modal factorisation. Finally, we discuss a number of use cases which depend on connectome augmentation techniques, such as model simulations of functional connectivity and generating mechanistic hypotheses for animal disease models.

High-frequency burst spiking in layer 5 thick-tufted pyramids of rat primary somatosensory cortex encodes exploratory touch

Diversity of cell-types that collectively shape the cortical microcircuit ensures the necessary computational richness to orchestrate a wide variety of behaviors. The information content embedded in spiking activity of identified cell-types remain unclear to a large extent. Here, we recorded spike responses upon whisker touch of anatomically identified excitatory cell-types in primary somatosensory cortex in naive, untrained rats. We find major differences across layers and cell-types. The temporal structure of spontaneous spiking contains high-frequency bursts (≥100 Hz) in all morphological cell-types but a significant increase upon whisker touch is restricted to layer L5 thick-tufted pyramids (L5tts) and thus provides a distinct neurophysiological signature. We find that whisker touch can also be decoded from L5tt bursting, but not from other cell-types. We observed high-frequency bursts in L5tts projecting to different subcortical regions, including thalamus, midbrain and brainstem. We conclude that bursts in L5tts allow accurate coding and decoding of exploratory whisker touch.

In order to investigate the information encoded by spiking activity in different neuronal cell types in the primary somatosensory cortex, de Kock et al performed electrophysiological recordings in untrained rats. They demonstrated that an increase in high-frequency burst spiking in thick tufted pyramids in layer 5 of the cortex allow accurate encoding of exploratory whisker touch.

A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation

The isocortex and hippocampal formation (HPF) in the mammalian brain play critical roles in perception, cognition, emotion, and learning. We profiled ∼1.3 million cells covering the entire adult mouse isocortex and HPF and derived a transcriptomic cell-type taxonomy revealing a comprehensive repertoire of glutamatergic and GABAergic neuron types. Contrary to the traditional view of HPF as having a simpler cellular organization, we discover a complete set of glutamatergic types in HPF homologous to all major subclasses found in the six-layered isocortex, suggesting that HPF and the isocortex share a common circuit organization. We also identify large-scale continuous and graded variations of cell types along isocortical depth, across the isocortical sheet, and in multiple dimensions in hippocampus and subiculum. Overall, our study establishes a molecular architecture of the mammalian isocortex and hippocampal formation and begins to shed light on its underlying relationship with the development, evolution, connectivity, and function of these two brain structures.

Oligodendrocyte Secreted Factors Shape Hippocampal GABAergic Neuron Transcriptome and Physiology

Oligodendrocytes form myelin for central nervous system axons and release factors which signal to neurons during myelination. Here, we ask how oligodendroglial factors influence hippocampal GABAergic neuron physiology. In mixed hippocampal cultures, GABAergic neurons fired action potentials (APs) of short duration and received high frequencies of excitatory synaptic events. In purified neuronal cultures without glial cells, GABAergic neuron excitability increased and the frequency of synaptic events decreased. These effects were largely reversed by adding oligodendrocyte conditioned medium (OCM). We compared the transcriptomic signature with the electrophysiological phenotype of single neurons in these three culture conditions. Genes expressed by single pyramidal or GABAergic neurons largely conformed to expected cell-type specific patterns. Multiple genes of GABAergic neurons were significantly downregulated by the transition from mixed cultures containing glial cells to purified neuronal cultures. Levels of these genes were restored by the addition of OCM to purified cultures. Clustering genes with similar changes in expression between different culture conditions revealed processes affected by oligodendroglial factors. Enriched genes are linked to roles in synapse assembly, AP generation, and transmembrane ion transport, including of zinc. These results provide new insight into the molecular targets by which oligodendrocytes influence neuron excitability and synaptic function.

Cortical disinhibitory circuits: cell types, connectivity and function

The concept of a dynamic excitation/inhibition balance tuned by circuit disinhibition, which can shape information flow during complex behavioral tasks, has arisen as an important and conserved information-processing motif. In cortical circuits, different subtypes of GABAergic inhibitory interneurons are connected to each other, offering an anatomical foundation for disinhibitory processes. Moreover, a subpopulation of GABAergic cells that express vasoactive intestinal polypeptide (VIP) preferentially innervates inhibitory interneurons, highlighting their central role in disinhibitory modulation. We discuss inhibitory neuron subtypes involved in disinhibition, with a focus on local circuits and long-range synaptic connections that drive disinhibitory function. We highlight multiple layers of disinhibition across cortical circuits that regulate behavior and serve to maintain an excitation/inhibition balance.

NMDA receptor function in inhibitory neurons

N-methyl-d-aspartate receptors (NMDARs) are present in the majority of brain circuits and play a key role in synaptic information transfer and synaptic plasticity. A key element of many brain circuits are inhibitory GABAergic interneurons that in themselves show diverse and cell-type-specific NMDAR expression and function. Indeed, NMDARs located on interneurons control cellular excitation in a synapse-type specific manner which leads to divergent dendritic integration properties amongst the plethora of interneuron subtypes known to exist. In this review, we explore the documented diversity of NMDAR subunit expression in identified subpopulations of interneurons and assess the NMDAR subtype-specific control of their function. We also highlight where knowledge still needs to be obtained, if a full appreciation is to be gained of roles played by NMDARs in controlling GABAergic modulation of synaptic and circuit function. This article is part of the 'Special Issue on Glutamate Receptors - NMDA receptors'.