Integrated Morphoelectric and Transcriptomic Classification of Cortical GABAergic Cells

Neuronal parts list and wiring diagram for a visual system

A catalogue of neuronal cell types has often been called a 'parts list' of the brain1, and regarded as a prerequisite for understanding brain function2,3. In the optic lobe of Drosophila, rules of connectivity between cell types have already proven to be essential for understanding fly vision4,5. Here we analyse the fly connectome to complete the list of cell types intrinsic to the optic lobe, as well as the rules governing their connectivity. Most new cell types contain 10 to 100 cells, and integrate information over medium distances in the visual field. Some existing type families (Tm, Li, and LPi)6-10 at least double in number of types. A new serpentine medulla (Sm) interneuron family contains more types than any other. Three families of cross-neuropil types are revealed. The consistency of types is demonstrated by analysing the distances in high-dimensional feature space, and is further validated by algorithms that select small subsets of discriminative features. We use connectivity to hypothesize about the functional roles of cell types in motion, object and colour vision. Connectivity with 'boundary types' that straddle the optic lobe and central brain is also quantified. We showcase the advantages of connectomic cell typing: complete and unbiased sampling, a rich array of features based on connectivity and reduction of the connectome to a substantially simpler wiring diagram of cell types, with immediate relevance for brain function and development.

Adaptive circuits for action and value information in rodent operant learning

Operant learning is a behavioral paradigm where animals learn to associate their actions with consequences, adapting their behavior accordingly. This review delves into the neural circuits that underpin operant learning in rodents, emphasizing the dynamic interplay between neural pathways, synaptic plasticity, and gene expression changes. We explore the cortico-basal ganglia circuits, highlighting the pivotal role of dopamine in modulating these pathways to reinforce behaviors that yield positive outcomes. We include insights from recent studies, which reveals the intricate roles of midbrain dopamine neurons in integrating action initiation and reward feedback, thereby enhancing movement-related activities in the dorsal striatum. Additionally, we discuss the molecular diversity of striatal neurons and their specific roles in reinforcement learning. The review also covers advances in transcriptome analysis techniques, such as single-cell RNA sequencing, which have provided deeper insights into the gene expression profiles associated with different neuronal populations during operant learning.

Areal specializations in the morpho-electric and transcriptomic properties of primate layer 5 extratelencephalic projection neurons

Large-scale analysis of single-cell gene expression has revealed transcriptomically defined cell subclasses present throughout the primate neocortex with gene expression profiles that differ depending upon neocortical region. Here, we test whether the interareal differences in gene expression translate to regional specializations in the physiology and morphology of infragranular glutamatergic neurons by performing Patch-seq experiments in brain slices from the temporal cortex (TCx) and motor cortex (MCx) of the macaque. We confirm that transcriptomically defined extratelencephalically projecting neurons of layer 5 (L5 ET neurons) include retrogradely labeled corticospinal neurons in the MCx and find multiple physiological properties and ion channel genes that distinguish L5 ET from non-ET neurons in both areas. Additionally, while infragranular ET and non-ET neurons retain distinct neuronal properties across multiple regions, there are regional morpho-electric and gene expression specializations in the L5 ET subclass, providing mechanistic insights into the specialized functional architecture of the primate neocortex.

Transcriptomic cell-type specificity of local cortical circuits

Complex neocortical functions rely on networks of diverse excitatory and inhibitory neurons. While local connectivity rules between major neuronal subclasses have been established, the specificity of connections at the level of transcriptomic subtypes remains unclear. We introduce single transcriptome assisted rabies tracing (START), a method combining monosynaptic rabies tracing and single-nuclei RNA sequencing to identify transcriptomic cell types, providing inputs to defined neuron populations. We employ START to transcriptomically characterize inhibitory neurons providing monosynaptic input to 5 different layer-specific excitatory cortical neuron populations in mouse primary visual cortex (V1). At the subclass level, we observe results consistent with findings from prior studies that resolve neuronal subclasses using antibody staining, transgenic mouse lines, and morphological reconstruction. With improved neuronal subtype granularity achieved with START, we demonstrate transcriptomic subtype specificity of inhibitory inputs to various excitatory neuron subclasses. These results establish local connectivity rules at the resolution of transcriptomic inhibitory cell types.

ARNT2 controls prefrontal somatostatin interneurons mediating affective empathy

Empathy, crucial for social interaction, is impaired across various neuropsychiatric conditions. However, the genetic and neural underpinnings of empathy variability remain elusive. By combining forward genetic mapping with transcriptome analysis, we discover that aryl hydrocarbon receptor nuclear translocator 2 (ARNT2) is a key driver modulating observational fear, a basic form of affective empathy. Disrupted ARNT2 expression in the anterior cingulate cortex (ACC) reduces affect sharing in mice. Specifically, selective ARNT2 ablation in somatostatin (SST)-expressing interneurons leads to decreased pyramidal cell excitability, increased spontaneous firing, aberrant Ca2+ dynamics, and disrupted theta oscillations in the ACC, resulting in reduced vicarious freezing. We further demonstrate that ARNT2-expressing SST interneurons govern affective state discrimination, uncovering a potential mechanism by which ARNT2 polymorphisms associate with emotion recognition in humans. Our findings advance our understanding of the molecular mechanism controlling empathic capacity and highlight the neural substrates underlying social affective dysfunctions in psychiatric disorders.

NEURD offers automated proofreading and feature extraction for connectomics

We are now in the era of millimeter-scale electron microscopy (EM) volumes collected at nanometer resolution. Dense reconstruction of cellular compartments in these EM volumes has been enabled by recent advances in Machine Learning (ML). Automated segmentation methods produce exceptionally accurate reconstructions of cells, but post-hoc proofreading is still required to generate large connectomes free of merge and split errors. The elaborate 3-D meshes of neurons in these volumes contain detailed morphological information at multiple scales, from the diameter, shape, and branching patterns of axons and dendrites, down to the fine-scale structure of dendritic spines. However, extracting these features can require substantial effort to piece together existing tools into custom workflows. Building on existing open-source software for mesh manipulation, here we present "NEURD", a software package that decomposes meshed neurons into compact and extensively-annotated graph representations. With these feature-rich graphs, we automate a variety of tasks such as state of the art automated proofreading of merge errors, cell classification, spine detection, axon-dendritic proximities, and other annotations. These features enable many downstream analyses of neural morphology and connectivity, making these massive and complex datasets more accessible to neuroscience researchers focused on a variety of scientific questions.

Presubicular VIP expressing interneurons receive facilitating excitation from anterior thalamus

The presubiculum is part of the parahippocampal cortex and plays a fundamental role for orientation in space. Many principal neurons of the presubiculum signal head direction, and show persistent firing when the head of an animal is oriented in a specific preferred direction. GABAergic neurons of the presubiculum control the timing, sensitivity and selectivity of head directional signals from the anterior thalamic nuclei. However, the role of vasoactive intestinal peptide (VIP) expressing interneurons in the presubicular microcircuit has not yet been addressed. Here, we examined the intrinsic properties of VIP interneurons as well as their input connectivity following photostimulation of anterior thalamic axons. We show that presubicular VIP interneurons are more densely distributed in superficial than in deep layers. They are highly excitable. Three groups emerged from the unsupervised cluster analysis of their electrophysiological properties. We demonstrate a frequency dependent recruitment of VIP cells by thalamic afferences and facilitating synaptic input dynamics. Our data provide initial insight into the contribution of VIP interneurons for the integration of thalamic head direction information in the presubiculum.

Unique Transcriptomic Cell Types of the Granular Retrosplenial Cortex are Preserved Across Mice and Rats Despite Dramatic Changes in Key Marker Genes

The granular retrosplenial cortex (RSG) supports key functions ranging from memory consolidation to spatial navigation. The mouse RSG contains several cell types that are remarkably distinct from those found in other cortical regions. This includes the physiologically and transcriptomically unique low rheobase neuron that is the dominant cell-type in RSG layers 2/3 (L2/3 LR), as well as the similarly exclusive pyramidal cells that comprise much of RSG layer 5a (L5a RSG). While the functions of the RSG are extensively studied in both mice and rats, it remains unknown if the transcriptomically unique cell types of the mouse RSG are evolutionarily conserved in rats. Here, we show that mouse and rat RSG not only contain the same cell types, but key subtypes including the L2/3 LR and L5a RSG neurons are amplified in their representations in rats compared to mice. This preservation of cell types in male and female rats happens despite dramatic changes in key cell-type-specific marker genes, with the Scnn1a expression that selectively tags mouse L5a RSG neurons completely absent in rats. Important for Cre-driver line development, we identify alternative, cross-species genes that can be used to selectively target the cell types of the RSG in both mice and rats. Our results show that the unique cell types of the RSG are evolutionarily conserved across millions of years of evolution between mice and rats, but also emphasize stark species-specific differences in marker genes that need to be considered when making cell-type-specific transgenic lines of mice versus rats.

An enhancer-AAV toolbox to target and manipulate distinct interneuron subtypes

In recent years, we and others have identified a number of enhancers that, when incorporated into rAAV vectors, can restrict the transgene expression to particular neuronal populations. Yet, viral tools to access and manipulate fine neuronal subtypes are still limited. Here, we performed systematic analysis of single cell genomic data to identify enhancer candidates for each of the cortical interneuron subtypes. We established a set of enhancer-AAV tools that are highly specific for distinct cortical interneuron populations and striatal cholinergic neurons. These enhancers, when used in the context of different effectors, can target (fluorescent proteins), observe activity (GCaMP) and manipulate (opto- or chemo-genetics) specific neuronal subtypes. We also validated our enhancer-AAV tools across species. Thus, we provide the field with a powerful set of tools to study neural circuits and functions and to develop precise and targeted therapy.

A layered microcircuit model of somatosensory cortex with three interneuron types and cell-type-specific short-term plasticity

Three major types of GABAergic interneurons, parvalbumin-, somatostatin-, and vasoactive intestinal peptide-expressing (PV, SOM, VIP) cells, play critical but distinct roles in the cortical microcircuitry. Their specific electrophysiology and connectivity shape their inhibitory functions. To study the network dynamics and signal processing specific to these cell types in the cerebral cortex, we developed a multi-layer model incorporating biologically realistic interneuron parameters from rodent somatosensory cortex. The model is fitted to in vivo data on cell-type-specific population firing rates. With a protocol of cell-type-specific stimulation, network responses when activating different neuron types are examined. The model reproduces the experimentally observed inhibitory effects of PV and SOM cells and disinhibitory effect of VIP cells on excitatory cells. We further create a version of the model incorporating cell-type-specific short-term synaptic plasticity (STP). While the ongoing activity with and without STP is similar, STP modulates the responses of Exc, SOM, and VIP cells to cell-type-specific stimulation, presumably by changing the dominant inhibitory pathways. With slight adjustments, the model also reproduces sensory responses of specific interneuron types recorded in vivo. Our model provides predictions on network dynamics involving cell-type-specific short-term plasticity and can serve to explore the computational roles of inhibitory interneurons in sensory functions.

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

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

Acute stress differently modulates interneurons excitability and synaptic plasticity in the primary motor cortex of wild-type and SOD1G93A mouse model of ALS

Primary motor cortex (M1) network stability depends on activity of inhibitory interneurons, for which susceptibility to stress was previously demonstrated in limbic regions. Hyperexcitability in M1 following changes in the excitatory/inhibitory balance is a key pathological hallmark of amyotrophic lateral sclerosis (ALS). Using electrophysiological approaches, we assessed the impact of acute restraint stress on inhibitory interneurons excitability and global synaptic plasticity in M1 of the SOD1G93A ALS mouse model at a late pre-symptomatic stage (10-12.5 weeks). Based on their firing type (continuous, discontinuous, with accommodation or not) and electrophysiological characteristics (resting potential, rheobase, firing frequency), interneurons from M1 slices were separated into four clusters, labelled from 1 to 4. Among them, only interneurons from the first cluster, presenting continuous firing with few accommodations, tended to show increased excitability in wild-type (WT) and decreased excitability in SOD1G93A animals following stress. In vivo analyses of evoked field potentials showed that stress suppressed the theta burst-induced plasticity of an excitatory component (N1) recorded in the superficial layers of M1 in WT, with no impact on an inhibitory complex (N2-P1) from the deeper layers. In SOD1G93A mice, stress did not affect N1 but suppressed the N2-P1 plasticity. These data suggest that stress can alter M1 network functioning in a different manner in WT and SOD1G93A mice, possibly through changes of inhibitory interneurons excitability and synaptic plasticity. This suggests that stress-induced activity changes in M1 may therefore influence ALS outcomes. KEY POINTS: Disruption of the excitatory/inhibitory balance in the primary motor cortex (M1) has been linked to cortical hyperexcitability development, a key pathological hallmark of amyotrophic lateral sclerosis (ALS). Psychological stress was reported to influence excitatory/inhibitory balance in limbic regions, but very little is known about its influence on the M1 functioning under physiological or pathological conditions. Our study revealed that acute stress influences the excitatory/inhibitory balance within the M1, through changes in interneurons excitability along with network plasticity. Such changes were different in pathological (SOD1G93A ALS mouse model) vs. physiological (wild-type) conditions. The results of our study help us to better understand how stress modulates the M1 and highlight the need to further characterize stress-induced motor cortex changes because it may be of importance when evaluating ALS outcomes.

The short-term plasticity of VIP interneurons in motor cortex

Short-term plasticity is an important feature in the brain for shaping neural dynamics and for information processing. Short-term plasticity is known to depend on many factors including brain region, cortical layer, and cell type. Here we focus on vasoactive-intestinal peptide (VIP) interneurons (INs). VIP INs play a key disinhibitory role in cortical circuits by inhibiting other IN types, including Martinotti cells (MCs) and basket cells (BCs). Despite this prominent role, short-term plasticity at synapses to and from VIP INs is not well described. In this study, we therefore characterized the short-term plasticity at inputs and outputs of genetically targeted VIP INs in mouse motor cortex. To explore inhibitory to inhibitory (I → I) short-term plasticity at layer 2/3 (L2/3) VIP IN outputs onto L5 MCs and BCs, we relied on a combination of whole-cell recording, 2-photon microscopy, and optogenetics, which revealed that VIP IN→MC/BC synapses were consistently short-term depressing. To explore excitatory (E) → I short-term plasticity at inputs to VIP INs, we used extracellular stimulation. Surprisingly, unlike VIP IN outputs, E → VIP IN synapses exhibited heterogeneous short-term dynamics, which we attributed to the target VIP IN cell rather than the input. Computational modeling furthermore linked the diversity in short-term dynamics at VIP IN inputs to a wide variability in probability of release. Taken together, our findings highlight how short-term plasticity at VIP IN inputs and outputs is specific to synapse type. We propose that the broad diversity in short-term plasticity of VIP IN inputs forms a basis to code for a broad range of contrasting signal dynamics.

Neural Network Mechanisms Underlying General Anesthesia: Cortical and Subcortical Nuclei

General anesthesia plays a significant role in modern medicine. However, the precise mechanism of general anesthesia remains unclear, posing a key scientific challenge in anesthesiology. Advances in neuroscience techniques have enabled targeted manipulation of specific neural circuits and the capture of brain-wide neural activity at high resolution. These advances hold promise for elucidating the intricate mechanisms of action of general anesthetics. This review aims to summarize our current understanding of the role of cortical and subcortical nuclei in modulating general anesthesia, providing new evidence of cortico-cortical and thalamocortical networks in relation to anesthesia and consciousness. These insights contribute to a comprehensive understanding of the neural network mechanisms underlying general anesthesia.

Scalable spatial single-cell transcriptomics and translatomics in 3D thick tissue blocks

Characterizing the transcriptional and translational gene expression patterns at the single-cell level within their three-dimensional (3D) tissue context is essential for revealing how genes shape tissue structure and function in health and disease. However, most existing spatial profiling techniques are limited to 5-20 μm thin tissue sections. Here, we developed Deep-STARmap and Deep-RIBOmap, which enable 3D in situ quantification of thousands of gene transcripts and their corresponding translation activities, respectively, within 200-μm thick tissue blocks. This is achieved through scalable probe synthesis, hydrogel embedding with efficient probe anchoring, and robust cDNA crosslinking. We first utilized Deep-STARmap in combination with multicolor fluorescent protein imaging for simultaneous molecular cell typing and 3D neuron morphology tracing in the mouse brain. We also demonstrate that 3D spatial profiling facilitates comprehensive and quantitative analysis of tumor-immune interactions in human skin cancer.

Neurotensin-specific corticothalamic circuit regulates innate response conflict

Animals must simultaneously select and balance multiple action contingencies in ambiguous situations: for instance, evading danger during feeding. This has rarely been examined in the context of information selection; despite corticothalamic pathways that mediate sensory attention being relatively well characterized, neural mechanisms filtering conflicting actions remain unclear. Here, we develop a new loom/feed test to observe conflict between naturally induced fear and feeding and identify a novel anterior cingulate cortex (ACC) output to the ventral anterior and ventral lateral thalamus (VA/VL) that adjusts selectivity between these innate actions. Using micro-endoscopy and fiber photometry, we reveal that activity in corticofugal outputs was lowered during unbalanced/singularly occupied periods, as were the resulting decreased thalamic initiation-related signals for less-favored actions, suggesting that the integration of ACC-thalamic firing may directly regulate the output of behavior choices. Accordingly, the optoinhibition of ACC-VA/VL circuits induced high bias toward feeding at the expense of defense. To identify upstream "commander" cortical cells gating this output, we established dual-order tracing (DOT)-translating ribosome affinity purification (TRAP)-a scheme to label upstream neurons with transcriptome analysis-and found a novel population of neurotensin-positive interneurons (ACCNts). The photoexcitation of ACCNts cells indeed caused similarly hyper-selective behaviors. Collectively, this new "corticofugal action filter" scheme suggests that communication in multi-step cingulate circuits may critically influence the summation of motor signals in thalamic outputs, regulating bias between innate action types.

Pyramidal neurons proportionately alter the identity and survival of specific cortical interneuron subtypes

The mammalian cerebral cortex comprises a complex neuronal network that maintains a delicate balance between excitatory neurons and inhibitory interneurons. Previous studies, including our own research, have shown that specific interneuron subtypes are closely associated with particular pyramidal neuron types, forming stereotyped local inhibitory microcircuits. However, the developmental processes that establish these precise networks are not well understood. Here we show that pyramidal neuron types are instrumental in driving the terminal differentiation and maintaining the survival of specific associated interneuron subtypes. In a wild-type cortex, the relative abundance of different interneuron subtypes aligns precisely with the pyramidal neuron types to which they synaptically target. In Fezf2 mutant cortex, characterized by the absence of layer 5 pyramidal tract neurons and an expansion of layer 6 intratelencephalic neurons, we observed a corresponding decrease in associated layer 5b interneurons and an increase in layer 6 subtypes. Interestingly, these shifts in composition are achieved through mechanisms specific to different interneuron types. While SST interneurons adjust their abundance to the change in pyramidal neuron prevalence through the regulation of programmed cell death, parvalbumin interneurons alter their identity. These findings illustrate two key strategies by which the dynamic interplay between pyramidal neurons and interneurons allows local microcircuits to be sculpted precisely. These insights underscore the precise roles of extrinsic signals from pyramidal cells in the establishment of interneuron diversity and their subsequent integration into local cortical microcircuits.

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

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

Genetic approaches to elucidating cortical and hippocampal GABAergic interneuron diversity

GABAergic interneurons (INs) in the mammalian forebrain represent a diverse population of cells that provide specialized forms of local inhibition to regulate neural circuit activity. Over the last few decades, the development of a palette of genetic tools along with the generation of single-cell transcriptomic data has begun to reveal the molecular basis of IN diversity, thereby providing deep insights into how different IN subtypes function in the forebrain. In this review, we outline the emerging picture of cortical and hippocampal IN speciation as defined by transcriptomics and developmental origin and summarize the genetic strategies that have been utilized to target specific IN subtypes, along with the technical considerations inherent to each approach. Collectively, these methods have greatly facilitated our understanding of how IN subtypes regulate forebrain circuitry via cell type and compartment-specific inhibition and thus have illuminated a path toward potential therapeutic interventions for a variety of neurocognitive disorders.

Pyramidal neurons proportionately alter the identity and survival of specific cortical interneuron subtypes

The mammalian cerebral cortex comprises a complex neuronal network that maintains a delicate balance between excitatory neurons and inhibitory interneurons. Previous studies, including our own research, have shown that specific interneuron subtypes are closely associated with particular pyramidal neuron types, forming stereotyped local inhibitory microcircuits. However, the developmental processes that establish these precise networks are not well understood. Here we show that pyramidal neuron types are instrumental in driving the terminal differentiation and maintaining the survival of specific associated interneuron subtypes. In a wild-type cortex, the relative abundance of different interneuron subtypes aligns precisely with the pyramidal neuron types to which they synaptically target. In Fezf2 mutant cortex, characterized by the absence of layer 5 pyramidal tract neurons and an expansion of layer 6 intratelencephalic neurons, we observed a corresponding decrease in associated layer 5b interneurons and an increase in layer 6 subtypes. Interestingly, these shifts in composition are achieved through mechanisms specific to different interneuron types. While SST interneurons adjust their abundance to the change in pyramidal neuron prevalence through the regulation of programmed cell death, parvalbumin interneurons alter their identity. These findings illustrate two key strategies by which the dynamic interplay between pyramidal neurons and interneurons allows local microcircuits to be sculpted precisely. These insights underscore the precise roles of extrinsic signals from pyramidal cells in the establishment of interneuron diversity and their subsequent integration into local cortical microcircuits.

Modulation of large rhythmic depolarizations in human large basket cells by norepinephrine and acetylcholine

Rhythmic brain activity is critical to many brain functions and is sensitive to neuromodulation, but so far very few studies have investigated this activity on the cellular level in vitro in human brain tissue samples. This study reveals and characterizes a novel rhythmic network activity in the human neocortex. Using intracellular patch-clamp recordings of human cortical neurons, we identify large rhythmic depolarizations (LRDs) driven by glutamate release but not by GABA. These LRDs are intricate events made up of multiple depolarizing phases, occurring at ~0.3 Hz, have large amplitudes and long decay times. Unlike human tissue, rat neocortex layers 2/3 exhibit no such activity under identical conditions. LRDs are mainly observed in a subset of L2/3 interneurons that receive substantial excitatory inputs and are likely large basket cells based on their morphology. LRDs are highly sensitive to norepinephrine (NE) and acetylcholine (ACh), two neuromodulators that affect network dynamics. NE increases LRD frequency through β-adrenergic receptor activity while ACh decreases it via M4 muscarinic receptor activation. Multi-electrode array recordings show that NE enhances and synchronizes oscillatory network activity, whereas ACh causes desynchronization. Thus, NE and ACh distinctly modulate LRDs, exerting specific control over human neocortical activity.

Primary auditory thalamus relays directly to cortical layer 1 interneurons

Inhibitory interneurons within cortical layer 1 (L1-INs) integrate inputs from diverse brain regions to modulate sensory processing and plasticity, but the sensory inputs that recruit these interneurons have not been identified. Here we used monosynaptic retrograde tracing and whole-cell electrophysiology to characterize the thalamic inputs onto two major subpopulations of L1-INs in the mouse auditory cortex. We find that the vast majority of auditory thalamic inputs to these L1-INs unexpectedly arise from the ventral subdivision of the medial geniculate body (MGBv), the tonotopically-organized primary auditory thalamus. Moreover, these interneurons receive robust functional monosynaptic MGBv inputs that are comparable to those recorded in the L4 excitatory pyramidal neurons. Our findings identify a direct pathway from the primary auditory thalamus to the L1-INs, suggesting that these interneurons are uniquely positioned to integrate thalamic inputs conveying precise sensory information with top-down inputs carrying information about brain states and learned associations.

A brief history of somatostatin interneuron taxonomy or: how many somatostatin subtypes are there, really?

We provide a brief (and unabashedly biased) overview of the pre-transcriptomic history of somatostatin interneuron taxonomy, followed by a chronological summary of the large-scale, NIH-supported effort over the last ten years to generate a comprehensive, single-cell RNA-seq-based taxonomy of cortical neurons. Focusing on somatostatin interneurons, we present the perspective of experimental neuroscientists trying to incorporate the new classification schemes into their own research while struggling to keep up with the ever-increasing number of proposed cell types, which seems to double every two years. We suggest that for experimental analysis, the most useful taxonomic level is the subdivision of somatostatin interneurons into ten or so "supertypes," which closely agrees with their more traditional classification by morphological, electrophysiological and neurochemical features. We argue that finer subdivisions ("t-types" or "clusters"), based on slight variations in gene expression profiles but lacking clear phenotypic differences, are less useful to researchers and may actually defeat the purpose of classifying neurons to begin with. We end by stressing the need for generating novel tools (mouse lines, viral vectors) for genetically targeting distinct supertypes for expression of fluorescent reporters, calcium sensors and excitatory or inhibitory opsins, allowing neuroscientists to chart the input and output synaptic connections of each proposed subtype, reveal the position they occupy in the cortical network and examine experimentally their roles in sensorimotor behaviors and cognitive brain functions.

Specific and comprehensive genetic targeting reveals brain-wide distribution and synaptic input patterns of GABAergic axo-axonic interneurons

Axo-axonic cells (AACs), also called chandelier cells (ChCs) in the cerebral cortex, are the most distinctive type of GABAergic interneurons described in the neocortex, hippocampus, and basolateral amygdala (BLA). AACs selectively innervate glutamatergic projection neurons (PNs) at their axon initial segment (AIS), thus may exert decisive control over PN spiking and regulate PN functional ensembles. However, the brain-wide distribution, synaptic connectivity, and circuit function of AACs remain poorly understood, largely due to the lack of specific and reliable experimental tools. Here, we have established an intersectional genetic strategy that achieves specific and comprehensive targeting of AACs throughout the mouse brain based on their lineage (Nkx2.1) and molecular (Unc5b, Pthlh) markers. We discovered that AACs are deployed across essentially all the pallium-derived brain structures, including not only the dorsal pallium-derived neocortex and medial pallium-derived hippocampal formation, but also the lateral pallium-derived claustrum-insular complex, and the ventral pallium-derived extended amygdaloid complex and olfactory centers. AACs are also abundant in anterior olfactory nucleus, taenia tecta, and lateral septum. AACs show characteristic variations in density across neocortical areas and layers and across subregions of the hippocampal formation. Neocortical AACs comprise multiple laminar subtypes with distinct dendritic and axonal arborization patterns. Retrograde monosynaptic tracing from AACs across neocortical, hippocampal, and BLA regions reveal shared as well as distinct patterns of synaptic input. Specific and comprehensive targeting of AACs facilitates the study of their developmental genetic program and circuit function across brain structures, providing a ground truth platform for understanding the conservation and variation of a bona fide cell type across brain regions and species.

A dendritic substrate for temporal diversity of cortical inhibition

In the mammalian neocortex, GABAergic interneurons (INs) inhibit cortical networks in profoundly different ways. The extent to which this depends on how different INs process excitatory signals along their dendrites is poorly understood. Here, we reveal that the functional specialization of two major populations of cortical INs is determined by the unique association of different dendritic integration modes with distinct synaptic organization motifs. We found that somatostatin (SST)-INs exhibit NMDAR-dependent dendritic integration and uniform synapse density along the dendritic tree. In contrast, dendrites of parvalbumin (PV)-INs exhibit passive synaptic integration coupled with proximally enriched synaptic distributions. Theoretical analysis shows that these two dendritic configurations result in different strategies to optimize synaptic efficacy in thin dendritic structures. Yet, the two configurations lead to distinct temporal engagement of each IN during network activity. We confirmed these predictions with in vivo recordings of IN activity in the visual cortex of awake mice, revealing a rapid and linear recruitment of PV-INs as opposed to a long-lasting integrative activation of SST-INs. Our work reveals the existence of distinct dendritic strategies that confer distinct temporal representations for the two major classes of neocortical INs and thus dynamics of inhibition.

Control of innate olfactory valence by segregated cortical amygdala circuits

Animals perform innate behaviors that are stereotyped responses to specific evolutionarily relevant stimuli in the absence of prior learning or experience. These behaviors can be reduced to an axis of valence, whereby specific odors evoke approach or avoidance. The cortical amygdala (plCoA) mediates innate attraction and aversion to odor. However, little is known about how this brain area gives rise to behaviors of opposing motivational valence. Here, we sought to define the circuit features of plCoA that give rise to innate olfactory behaviors of valence. We characterized the physiology, gene expression, and projections of this structure, identifying a divergent, topographic organization that selectively controls innate attraction and avoidance to odor. First, we examined odor-evoked responses in these areas and found sparse encoding of odor identity, but not valence. We next considered a topographic organization and found that optogenetic stimulation of the anterior and posterior domains of plCoA elicits attraction and avoidance, respectively, suggesting a functional axis for valence. Using single cell and spatial RNA sequencing, we identified the molecular cell types in plCoA, revealing an anteroposterior gradient in cell types, whereby anterior glutamatergic neurons preferentially express Slc17a6 and posterior neurons express Slc17a7. Activation of these respective cell types recapitulates appetitive and aversive valence behaviors, and chemogenetic inhibition reveals partial necessity for valence responses to innate appetitive or aversive odors. Finally, we identified topographically organized circuits defined by projections, whereby anterior neurons preferentially project to medial amygdala, and posterior neurons preferentially project to nucleus accumbens, which are respectively sufficient and necessary for innate negative and positive olfactory valence. Together, these data advance our understanding of how the olfactory system generates stereotypic, hardwired attraction and avoidance, and supports a model whereby distinct, topographically distributed plCoA populations direct innate olfactory valence responses by signaling to divergent valence-specific targets, linking upstream olfactory identity to downstream valence behaviors, through a population code. This represents a novel circuit motif in which valence encoding is represented not by the firing properties of individual neurons, but by population level identity encoding that is routed through divergent targets to mediate distinct valence.

Making Ramón y Cajal proud: Development of cell identity and diversity in the cerebral cortex

Since the beautiful images of Santiago Ramón y Cajal provided a first glimpse into the immense diversity and complexity of cell types found in the cerebral cortex, neuroscience has been challenged and inspired to understand how these diverse cells are generated and how they interact with each other to orchestrate the development of this remarkable tissue. Some fundamental questions drive the field's quest to understand cortical development: what are the mechanistic principles that govern the emergence of neuronal diversity? How do extrinsic and intrinsic signals integrate with physical forces and activity to shape cell identity? How do the diverse populations of neurons and glia influence each other during development to guarantee proper integration and function? The advent of powerful new technologies to profile and perturb cortical development at unprecedented resolution and across a variety of modalities has offered a new opportunity to integrate past knowledge with brand new data. Here, we review some of this progress using cortical excitatory projection neurons as a system to draw out general principles of cell diversification and the role of cell-cell interactions during cortical development.

Neurogliaform Cells Exhibit Laminar-specific Responses in the Visual Cortex and Modulate Behavioral State-dependent Cortical Activity

Neurogliaform cells are a distinct type of GABAergic cortical interneurons known for their 'volume transmission' output property. However, their activity and function within cortical circuits remain unclear. Here, we developed two genetic tools to target these neurons and examine their function in the primary visual cortex. We found that the spontaneous activity of neurogliaform cells positively correlated with locomotion. Silencing these neurons increased spontaneous activity during locomotion and impaired visual responses in L2/3 pyramidal neurons. Furthermore, the contrast-dependent visual response of neurogliaform cells varies with their laminar location and is constrained by their morphology and input connectivity. These findings demonstrate the importance of neurogliaform cells in regulating cortical behavioral state-dependent spontaneous activity and indicate that their functional engagement during visual stimuli is influenced by their laminar positioning and connectivity.

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

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

Deciphering brain cellular and behavioral mechanisms: Insights from single-cell and spatial RNA sequencing

The brain is a complex computing system composed of a multitude of interacting neurons. The computational outputs of this system determine the behavior and perception of every individual. Each brain cell expresses thousands of genes that dictate the cell's function and physiological properties. Therefore, deciphering the molecular expression of each cell is of great significance for understanding its characteristics and role in brain function. Additionally, the positional information of each cell can provide crucial insights into their involvement in local brain circuits. In this review, we briefly overview the principles of single-cell RNA sequencing and spatial transcriptomics, the potential issues and challenges in their data processing, and their applications in brain research. We further outline several promising directions in neuroscience that could be integrated with single-cell RNA sequencing, including neurodevelopment, the identification of novel brain microstructures, cognition and behavior, neuronal cell positioning, molecules and cells related to advanced brain functions, sleep-wake cycles/circadian rhythms, and computational modeling of brain function. We believe that the deep integration of these directions with single-cell and spatial RNA sequencing can contribute significantly to understanding the roles of individual cells or cell types in these specific functions, thereby making important contributions to addressing critical questions in those fields. This article is categorized under: RNA Evolution and Genomics > Computational Analyses of RNA RNA in Disease and Development > RNA in Development RNA in Disease and Development > RNA in Disease.

Neocortical long-range inhibition promotes cortical synchrony and sleep

Behavioral states such as sleep and wake are highly correlated with specific patterns of rhythmic activity in the cortex. During low arousal states such as slow wave sleep, the cortex is synchronized and dominated by low frequency rhythms coordinated across multiple regions. Although recent evidence suggests that GABAergic inhibitory neurons are key players in cortical state modulation, the in vivo circuit mechanisms coordinating synchronized activity among local and distant neocortical networks are not well understood. Here, we show that somatostatin and chondrolectin co-expressing cells (Sst-Chodl cells), a sparse and unique class of neocortical inhibitory neurons, are selectively active during low arousal states and are largely silent during periods of high arousal. In contrast to other neocortical inhibitory neurons, we show these neurons have long-range axons that project across neocortical areas. Activation of Sst-Chodl cells is sufficient to promote synchronized cortical states characteristic of low arousal, with increased spike co-firing and low frequency brain rhythms, and to alter behavioral states by promoting sleep. Contrary to the prevailing belief that sleep is exclusively driven by subcortical mechanisms, our findings reveal that these long-range inhibitory neurons not only track changes in behavioral state but are sufficient to induce both sleep-like cortical states and sleep behavior, establishing a crucial circuit component in regulating behavioral states.

Variation and convergence in the morpho-functional properties of the mammalian neocortex

Man's natural inclination to classify and hierarchize the living world has prompted neurophysiologists to explore possible differences in brain organisation between mammals, with the aim of understanding the diversity of their behavioural repertoires. But what really distinguishes the human brain from that of a platypus, an opossum or a rodent? In this review, we compare the structural and electrical properties of neocortical neurons in the main mammalian radiations and examine their impact on the functioning of the networks they form. We discuss variations in overall brain size, number of neurons, length of their dendritic trees and density of spines, acknowledging their increase in humans as in most large-brained species. Our comparative analysis also highlights a remarkable consistency, particularly pronounced in marsupial and placental mammals, in the cell typology, intrinsic and synaptic electrical properties of pyramidal neuron subtypes, and in their organisation into functional circuits. These shared cellular and network characteristics contribute to the emergence of strikingly similar large-scale physiological and pathological brain dynamics across a wide range of species. These findings support the existence of a core set of neural principles and processes conserved throughout mammalian evolution, from which a number of species-specific adaptations appear, likely allowing distinct functional needs to be met in a variety of environmental contexts.

Somatostatin interneurons control the timing of developmental desynchronization in cortical networks

Synchronous neuronal activity is a hallmark of the developing brain. In the mouse cerebral cortex, activity decorrelates during the second week of postnatal development, progressively acquiring the characteristic sparse pattern underlying the integration of sensory information. The maturation of inhibition seems critical for this process, but the interneurons involved in this crucial transition of network activity in the developing cortex remain unknown. Using in vivo longitudinal two-photon calcium imaging during the period that precedes the change from highly synchronous to decorrelated activity, we identify somatostatin-expressing (SST+) interneurons as critical modulators of this switch in mice. Modulation of the activity of SST+ cells accelerates or delays the decorrelation of cortical network activity, a process that involves regulating the maturation of parvalbumin-expressing (PV+) interneurons. SST+ cells critically link sensory inputs with local circuits, controlling the neural dynamics in the developing cortex while modulating the integration of other interneurons into nascent cortical circuits.

Synaptic Organization-Function Relationships of Amygdala Interneurons Supporting Associative Learning

Coordinated activity of basolateral amygdala (BLA) GABAergic interneurons (INs) and glutamatergic principal cells (PCs) is critical for associative learning, however the microcircuit organization-function relationships of distinct IN classes remain uncertain. Here, we show somatostatin (SOM) INs provide inhibition onto, and are excited by, local PCs, whereas vasoactive intestinal peptide (VIP) INs are driven by extrinsic afferents. Parvalbumin (PV) INs inhibit PCs and are activated by local and extrinsic inputs. Thus, SOM and VIP INs exhibit complementary roles in feedback and feedforward inhibition, respectively, while PV INs contribute to both microcircuit motifs. Functionally, each IN subtype reveals unique activity patterns across fear- and extinction learning with SOM and VIP INs showing most divergent characteristics, and PV INs display an intermediate phenotype parallelling synaptic data. Finally, SOM and PV INs dynamically track behavioral state transitions across learning. These data provide insight into the synaptic microcircuit organization-function relationships of distinct BLA IN classes.

The transcriptomic and spatial organization of telencephalic GABAergic neuronal types

The telencephalon of the mammalian brain comprises multiple regions and circuit pathways that play adaptive and integrative roles in a variety of brain functions. There is a wide array of GABAergic neurons in the telencephalon; they play a multitude of circuit functions, and dysfunction of these neurons has been implicated in diverse brain disorders. In this study, we conducted a systematic and in-depth analysis of the transcriptomic and spatial organization of GABAergic neuronal types in all regions of the mouse telencephalon and their developmental origins. This was accomplished by utilizing 611,423 single-cell transcriptomes from the comprehensive and high-resolution transcriptomic and spatial cell type atlas for the adult whole mouse brain we have generated, supplemented with an additional single-cell RNA-sequencing dataset containing 99,438 high-quality single-cell transcriptomes collected from the pre- and postnatal developing mouse brain. We present a hierarchically organized adult telencephalic GABAergic neuronal cell type taxonomy of 7 classes, 52 subclasses, 284 supertypes, and 1,051 clusters, as well as a corresponding developmental taxonomy of 450 clusters across different ages. Detailed charting efforts reveal extraordinary complexity where relationships among cell types reflect both spatial locations and developmental origins. Transcriptomically and developmentally related cell types can often be found in distant and diverse brain regions indicating that long-distance migration and dispersion is a common characteristic of nearly all classes of telencephalic GABAergic neurons. Additionally, we find various spatial dimensions of both discrete and continuous variations among related cell types that are correlated with gene expression gradients. Lastly, we find that cortical, striatal and some pallidal GABAergic neurons undergo extensive postnatal diversification, whereas septal and most pallidal GABAergic neuronal types emerge simultaneously during the embryonic stage with limited postnatal diversification. Overall, the telencephalic GABAergic cell type taxonomy can serve as a foundational reference for molecular, structural and functional studies of cell types and circuits by the entire community.

ElecFeX is a user-friendly toolbox for efficient feature extraction from single-cell electrophysiological recordings

Characterizing neurons by their electrophysiological phenotypes is essential for understanding the neural basis of behavioral and cognitive functions. Technological developments have enabled the collection of hundreds of neural recordings; this calls for new tools capable of performing feature extraction efficiently. To address the urgent need for a powerful and accessible tool, we developed ElecFeX, an open-source MATLAB-based toolbox that (1) has an intuitive graphical user interface, (2) provides customizable measurements for a wide range of electrophysiological features, (3) processes large-size datasets effortlessly via batch analysis, and (4) yields formatted output for further analysis. We implemented ElecFeX on a diverse set of neural recordings; demonstrated its functionality, versatility, and efficiency in capturing electrical features; and established its significance in distinguishing neuronal subgroups across brain regions and species. ElecFeX is thus presented as a user-friendly toolbox to benefit the neuroscience community by minimizing the time required for extracting features from their electrophysiological datasets.

Neurogliaform Cells Exhibit Laminar-specific Responses in the Visual Cortex and Modulate Behavioral State-dependent Cortical Activity

Neurogliaform cells are a distinct type of GABAergic cortical interneurons known for their "volume transmission" output property. However, their activity and function within cortical circuits remain unclear. Here, we developed two genetic tools to target these neurons and examine their function in the primary visual cortex. We found that the spontaneous activity of neurogliaform cells positively correlated with locomotion. Silencing these neurons increased spontaneous activity during locomotion and impaired visual responses in L2/3 pyramidal neurons. Furthermore, the contrast-dependent visual response of neurogliaform cells varies with their laminar location and is constrained by their morphology and input connectivity. These findings demonstrate the importance of neurogliaform cells in regulating cortical behavioral state-dependent spontaneous activity and indicate that their functional engagement during visual stimuli is influenced by their laminar positioning and connectivity.

NARP-related alterations in the excitatory and inhibitory circuitry of socially isolated mice: developmental insights and implications for autism spectrum disorder

Background

Social isolation during critical periods of development is associated with alterations in behavior and neuronal circuitry. This study aimed to investigate the immediate and developmental effects of social isolation on firing properties, neuronal activity-regulated pentraxin (NARP) and parvalbumin (PV) expression in the prefrontal cortex (PFC), social behavior in juvenile socially isolated mice, and the biological relevance of NARP expression in autism spectrum disorder (ASD).

Methods

Mice were subjected to social isolation during postnatal days 21-35 (P21-P35) and were compared with group-housed control mice. Firing properties in the PFC pyramidal neurons were altered in P35 socially isolated mice, which might be associated with alterations in NARP and PV expression.

Results

In adulthood, mice that underwent juvenile social isolation exhibited difficulty distinguishing between novel and familiar mice during a social memory task, while maintaining similar levels of social interaction as the control mice. Furthermore, a marked decrease in NARP expression in lymphoblastoid cell lines derived from adolescent humans with ASD as compared to typically developing (TD) humans was found.

Conclusion

Our study highlights the role of electrophysiological properties, as well as NARP and PV expression in the PFC in mediating the developmental consequences of social isolation on behavior.

CCK+ Interneurons Contribute to Thalamus-Evoked Feed-Forward Inhibition in the Prelimbic Prefrontal Cortex

Interneurons in the medial prefrontal cortex (PFC) regulate local neural activity to influence cognitive, motivated, and emotional behaviors. Parvalbumin-expressing (PV+) interneurons are the primary mediators of thalamus-evoked feed-forward inhibition across the mouse cortex, including the anterior cingulate cortex, where they are engaged by inputs from the mediodorsal (MD) thalamus. In contrast, in the adjacent prelimbic (PL) cortex, we find that PV+ interneurons are scarce in the principal thalamorecipient layer 3 (L3), suggesting distinct mechanisms of inhibition. To identify the interneurons that mediate MD-evoked inhibition in PL, we combine slice physiology, optogenetics, and intersectional genetic tools in mice of both sexes. We find interneurons expressing cholecystokinin (CCK+) are abundant in L3 of PL, with cells exhibiting fast-spiking (fs) or non-fast-spiking (nfs) properties. MD inputs make stronger connections onto fs-CCK+ interneurons, driving them to fire more readily than nearby L3 pyramidal cells and other interneurons. CCK+ interneurons in turn make inhibitory, perisomatic connections onto L3 pyramidal cells, where they exhibit cannabinoid 1 receptor (CB1R) mediated modulation. Moreover, MD-evoked feed-forward inhibition, but not direct excitation, is also sensitive to CB1R modulation. Our findings indicate that CCK+ interneurons contribute to MD-evoked inhibition in PL, revealing a mechanism by which cannabinoids can modulate MD-PFC communication.

Feedforward and disinhibitory circuits differentially control activity of cortical somatostatin interneurons during behavioral state transitions

Interneurons (INs), specifically those in disinhibitory circuits like somatostatin (SST) and vasoactive intestinal peptide (VIP)-INs, are strongly modulated by the behavioral context. Yet, the mechanisms by which these INs are recruited during active states and whether their activity is consistent across sensory cortices remain unclear. We now report that in mice, locomotor activity strongly recruits SST-INs in the primary somatosensory (S1) but not the visual (V1) cortex. This diverse engagement of SST-INs cannot be explained by differences in VIP-IN function but is absent in the presence of visual input, suggesting the involvement of feedforward sensory pathways. Accordingly, inactivating the somatosensory thalamus, but not decreasing VIP-IN activity, significantly reduces the modulation of SST-INs by locomotion. Model simulations suggest that the differences in SST-INs across behavioral states can be explained by varying ratios of VIP- and thalamus-driven activity. By integrating feedforward activity with neuromodulation, SST-INs are anticipated to be crucial for adapting sensory processing to behavioral states.

Simple synaptic modulations implement diverse novelty computations

Detecting novelty is ethologically useful for an organism's survival. Recent experiments characterize how different types of novelty over timescales from seconds to weeks are reflected in the activity of excitatory and inhibitory neuron types. Here, we introduce a learning mechanism, familiarity-modulated synapses (FMSs), consisting of multiplicative modulations dependent on presynaptic or pre/postsynaptic neuron activity. With FMSs, network responses that encode novelty emerge under unsupervised continual learning and minimal connectivity constraints. Implementing FMSs within an experimentally constrained model of a visual cortical circuit, we demonstrate the generalizability of FMSs by simultaneously fitting absolute, contextual, and omission novelty effects. Our model also reproduces functional diversity within cell subpopulations, leading to experimentally testable predictions about connectivity and synaptic dynamics that can produce both population-level novelty responses and heterogeneous individual neuron signals. Altogether, our findings demonstrate how simple plasticity mechanisms within a cortical circuit structure can produce qualitatively distinct and complex novelty responses.

Layer 1 NDNF interneurons are specialized top-down master regulators of cortical circuits

Diverse types of inhibitory interneurons (INs) impart computational power and flexibility to neocortical circuits. Whereas markers for different IN types in cortical layers 2-6 (L2-L6) have been instrumental for generating a wealth of functional insights, only the recent identification of a selective marker (neuron-derived neurotrophic factor [NDNF]) has opened comparable opportunities for INs in L1 (L1INs). However, at present we know very little about the connectivity of NDNF L1INs with other IN types, their input-output conversion, and the existence of potential NDNF L1IN subtypes. Here, we report pervasive inhibition of L2/3 INs (including parvalbumin INs and vasoactive intestinal peptide INs) by NDNF L1INs. Intersectional genetics revealed similar physiology and connectivity in the NDNF L1IN subpopulation co-expressing neuropeptide Y. Finally, NDNF L1INs prominently and selectively engage in persistent firing, a physiological hallmark disconnecting their output from the current input. Collectively, our work therefore identifies NDNF L1INs as specialized master regulators of superficial neocortex according to their pervasive top-down afferents.

Organization of corticocortical and thalamocortical top-down inputs in the primary visual cortex

Unified visual perception requires integration of bottom-up and top-down inputs in the primary visual cortex (V1), yet the organization of top-down inputs in V1 remains unclear. Here, we used optogenetics-assisted circuit mapping to identify how multiple top-down inputs from higher-order cortical and thalamic areas engage V1 excitatory and inhibitory neurons. Top-down inputs overlap in superficial layers yet segregate in deep layers. Inputs from the medial secondary visual cortex (V2M) and anterior cingulate cortex (ACA) converge on L6 Pyrs, whereas ventrolateral orbitofrontal cortex (ORBvl) and lateral posterior thalamic nucleus (LP) inputs are processed in parallel in Pyr-type-specific subnetworks (Pyr←ORBvl and Pyr←LP) and drive mutual inhibition between them via local interneurons. Our study deepens understanding of the top-down modulation mechanisms of visual processing and establishes that V2M and ACA inputs in L6 employ integrated processing distinct from the parallel processing of LP and ORBvl inputs in L5.

Activity-Dependent Ectopic Spiking in Parvalbumin-Expressing Interneurons of the Neocortex

Canonically, action potentials of most mammalian neurons initiate at the axon initial segment (AIS) and propagate bidirectionally: orthodromically along the distal axon and retrogradely into the soma and dendrites. Under some circumstances, action potentials may initiate ectopically, at sites distal to the AIS, and propagate antidromically along the axon. These "ectopic action potentials" (EAPs) have been observed in experimental models of seizures and chronic pain, and more rarely in nonpathological forebrain neurons. Here we report that a large majority of parvalbumin-expressing (PV+) interneurons in the upper layers of mouse neocortex, from both orbitofrontal and primary somatosensory areas, fire EAPs after sufficient activation of their somata. Somatostatin-expressing interneurons also fire EAPs, though less robustly. Ectopic firing in PV+ cells occurs in varying temporal patterns and can persist for several seconds. PV+ cells evoke strong synaptic inhibition in pyramidal neurons and interneurons and play critical roles in cortical function. Our results suggest that ectopic spiking of PV+ interneurons is common and may contribute to both normal and pathological network functions of the neocortex.

Multimodal cortical neuronal cell type classification

Since more than a century, neuroscientists have distinguished excitatory (glutamatergic) neurons with long-distance projections from inhibitory (GABAergic) neurons with local projections and established layer-dependent schemes for the ~ 80% excitatory (principal) cells as well as the ~ 20% inhibitory neurons. Whereas, in the early days, mainly morphological criteria were used to define cell types, later supplemented by electrophysiological and neurochemical properties, nowadays. single-cell transcriptomics is the method of choice for cell type classification. Bringing recent insight together, we conclude that despite all established layer- and area-dependent differences, there is a set of reliably identifiable cortical cell types that were named (among others) intratelencephalic (IT), extratelencephalic (ET), and corticothalamic (CT) for the excitatory cells, which altogether comprise ~ 56 transcriptomic cell types (t-types). By the same means, inhibitory neurons were subdivided into parvalbumin (PV), somatostatin (SST), vasoactive intestinal polypeptide (VIP), and "other (i.e. Lamp5/Sncg)" subpopulations, which altogether comprise ~ 60 t-types. The coming years will show which t-types actually translate into "real" cell types that show a common set of multimodal features, including not only transcriptome but also physiology and morphology as well as connectivity and ultimately function. Only with the better knowledge of clear-cut cell types and experimental access to them, we will be able to reveal their specific functions, a task which turned out to be difficult in a part of the brain being so much specialized for cognition as the cerebral cortex.

Projection-TAGs enable multiplex projection tracing and multi-modal profiling of projection neurons

Single-cell multiomic techniques have sparked immense interest in developing a comprehensive multi-modal map of diverse neuronal cell types and their brain wide projections. However, investigating the spatial organization, transcriptional and epigenetic landscapes of brain wide projection neurons is hampered by the lack of efficient and easily adoptable tools. Here we introduce Projection-TAGs, a retrograde AAV platform that allows multiplex tagging of projection neurons using RNA barcodes. By using Projection-TAGs, we performed multiplex projection tracing of the mouse cortex and high-throughput single-cell profiling of the transcriptional and epigenetic landscapes of the cortical projection neurons. Projection-TAGs can be leveraged to obtain a snapshot of activity-dependent recruitment of distinct projection neurons and their molecular features in the context of a specific stimulus. Given its flexibility, usability, and compatibility, we envision that Projection-TAGs can be readily applied to build a comprehensive multi-modal map of brain neuronal cell types and their projections.

Ndnf Interneuron Excitability Is Spared in a Mouse Model of Dravet Syndrome

Dravet syndrome (DS) is a neurodevelopmental disorder characterized by epilepsy, developmental delay/intellectual disability, and features of autism spectrum disorder, caused by heterozygous loss-of-function variants in SCN1A encoding the voltage-gated sodium channel α subunit Nav1.1. The dominant model of DS pathogenesis is the "interneuron hypothesis," whereby GABAergic interneurons (INs) express and preferentially rely on Nav1.1-containing sodium channels for action potential (AP) generation. This has been shown for three of the major subclasses of cerebral cortex GABAergic INs: those expressing parvalbumin (PV), somatostatin, and vasoactive intestinal peptide. Here, we define the function of a fourth major subclass of INs expressing neuron-derived neurotrophic factor (Ndnf) in male and female DS (Scn1a+/-) mice. Patch-clamp electrophysiological recordings of Ndnf-INs in brain slices from Scn1a+/â mice and WT controls reveal normal intrinsic membrane properties, properties of AP generation and repetitive firing, and synaptic transmission across development. Immunohistochemistry shows that Nav1.1 is strongly expressed at the axon initial segment (AIS) of PV-expressing INs but is absent at the Ndnf-IN AIS. In vivo two-photon calcium imaging demonstrates that Ndnf-INs in Scn1a+/â mice are recruited similarly to WT controls during arousal. These results suggest that Ndnf-INs are the only major IN subclass that does not prominently rely on Nav1.1 for AP generation and thus retain their excitability in DS. The discovery of a major IN subclass with preserved function in the Scn1a+/â mouse model adds further complexity to the "interneuron hypothesis" and highlights the importance of considering cell-type heterogeneity when investigating mechanisms underlying neurodevelopmental disorders.

Functional specialization of hippocampal somatostatin-expressing interneurons

Hippocampal somatostatin-expressing (Sst) GABAergic interneurons (INs) exhibit considerable anatomical and functional heterogeneity. Recent single-cell transcriptome analyses have provided a comprehensive Sst-IN subpopulations census, a plausible molecular ground truth of neuronal identity whose links to specific functionality remain incomplete. Here, we designed an approach to identify and access subpopulations of Sst-INs based on transcriptomic features. Four mouse models based on single or combinatorial Cre- and Flp- expression differentiated functionally distinct subpopulations of CA1 hippocampal Sst-INs that largely tiled the morpho-functional parameter space of the Sst-INs superfamily. Notably, the Sst;;Tac1 intersection revealed a population of bistratified INs that preferentially synapsed onto fast-spiking interneurons (FS-INs) and were sufficient to interrupt their firing. In contrast, the Ndnf;;Nkx2-1 intersection identified a population of oriens lacunosum-moleculare INs that predominantly targeted CA1 pyramidal neurons, avoiding FS-INs. Overall, our results provide a framework to translate neuronal transcriptomic identity into discrete functional subtypes that capture the diverse specializations of hippocampal Sst-INs.

The spike-timing-dependent plasticity of VIP interneurons in motor cortex

The plasticity of inhibitory interneurons (INs) plays an important role in the organization and maintenance of cortical microcircuits. Given the many different IN types, there is an even greater diversity in synapse-type-specific plasticity learning rules at excitatory to excitatory (E→I), I→E, and I→I synapses. I→I synapses play a key disinhibitory role in cortical circuits. Because they typically target other INs, vasoactive intestinal peptide (VIP) INs are often featured in I→I→E disinhibition, which upregulates activity in nearby excitatory neurons. VIP IN dysregulation may thus lead to neuropathologies such as epilepsy. In spite of the important activity regulatory role of VIP INs, their long-term plasticity has not been described. Therefore, we characterized the phenomenology of spike-timing-dependent plasticity (STDP) at inputs and outputs of genetically defined VIP INs. Using a combination of whole-cell recording, 2-photon microscopy, and optogenetics, we explored I→I STDP at layer 2/3 (L2/3) VIP IN outputs onto L5 Martinotti cells (MCs) and basket cells (BCs). We found that VIP IN→MC synapses underwent causal long-term depression (LTD) that was presynaptically expressed. VIP IN→BC connections, however, did not undergo any detectable plasticity. Conversely, using extracellular stimulation, we explored E→I STDP at inputs to VIP INs which revealed long-term potentiation (LTP) for both causal and acausal timings. Taken together, our results demonstrate that VIP INs possess synapse-type-specific learning rules at their inputs and outputs. This suggests the possibility of harnessing VIP IN long-term plasticity to control activity-related neuropathologies such as epilepsy.