Reconstruction of neocortex: Organelles, compartments, cells, circuits, and activity.

We assembled a semi-automated reconstruction of L2/3 mouse primary visual cortex from ∼250 × 140 × 90 µm3 of electron microscopic images, including pyramidal and non-pyramidal neurons, astrocytes, microglia, oligodendrocytes and precursors, pericytes, vasculature, nuclei, mitochondria, and synapses. Visual responses of a subset of pyramidal cells are included. The data are publicly available, along with tools for programmatic and three-dimensional interactive access. Brief vignettes illustrate the breadth of potential applications relating structure to function in cortical circuits and neuronal cell biology. Mitochondria and synapse organization are characterized as a function of path length from the soma. Pyramidal connectivity motif frequencies are predicted accurately using a configuration model of random graphs. Pyramidal cells receiving more connections from nearby cells exhibit stronger and more reliable visual responses. Sample code shows data access and analysis.

Multi-layered maps of neuropil with segmentation-guided contrastive learning.

Maps of the nervous system that identify individual cells along with their type, subcellular components and connectivity have the potential to elucidate fundamental organizational principles of neural circuits. Nanometer-resolution imaging of brain tissue provides the necessary raw data, but inferring cellular and subcellular annotation layers is challenging. We present segmentation-guided contrastive learning of representations (SegCLR), a self-supervised machine learning technique that produces representations of cells directly from 3D imagery and segmentations. When applied to volumes of human and mouse cortex, SegCLR enables accurate classification of cellular subcompartments and achieves performance equivalent to a supervised approach while requiring 400-fold fewer labeled examples. SegCLR also enables inference of cell types from fragments as small as 10 µm, which enhances the utility of volumes in which many neurites are truncated at boundaries. Finally, SegCLR enables exploration of layer 5 pyramidal cell subtypes and automated large-scale analysis of synaptic partners in mouse visual cortex.

Oligodendrocyte precursor cells ingest axons in the mouse neocortex.

Neurons in the developing brain undergo extensive structural refinement as nascent circuits adopt their mature form. This physical transformation of neurons is facilitated by the engulfment and degradation of axonal branches and synapses by surrounding glial cells, including microglia and astrocytes. However, the small size of phagocytic organelles and the complex, highly ramified morphology of glia have made it difficult to define the contribution of these and other glial cell types to this crucial process. Here, we used large-scale, serial section transmission electron microscopy (TEM) with computational volume segmentation to reconstruct the complete 3D morphologies of distinct glial types in the mouse visual cortex, providing unprecedented resolution of their morphology and composition. Unexpectedly, we discovered that the fine processes of oligodendrocyte precursor cells (OPCs), a population of abundant, highly dynamic glial progenitors, frequently surrounded small branches of axons. Numerous phagosomes and phagolysosomes (PLs) containing fragments of axons and vesicular structures were present inside their processes, suggesting that OPCs engage in axon pruning. Single-nucleus RNA sequencing from the developing mouse cortex revealed that OPCs express key phagocytic genes at this stage, as well as neuronal transcripts, consistent with active axon engulfment. Although microglia are thought to be responsible for the majority of synaptic pruning and structural refinement, PLs were ten times more abundant in OPCs than in microglia at this stage, and these structures were markedly less abundant in newly generated oligodendrocytes, suggesting that OPCs contribute substantially to the refinement of neuronal circuits during cortical development.

Ultrastructural differences impact cilia shape and external exposure across cell classes in the visual cortex.

A primary cilium is a membrane-bound extension from the cell surface that contains receptors for perceiving and transmitting signals that modulate cell state and activity. Primary cilia in the brain are less accessible than cilia on cultured cells or epithelial tissues because in the brain they protrude into a deep, dense network of glial and neuronal processes. Here, we investigated cilia frequency, internal structure, shape, and position in large, high-resolution transmission electron microscopy volumes of mouse primary visual cortex. Cilia extended from the cell bodies of nearly all excitatory and inhibitory neurons, astrocytes, and oligodendrocyte precursor cells (OPCs) but were absent from oligodendrocytes and microglia. Ultrastructural comparisons revealed that the base of the cilium and the microtubule organization differed between neurons and glia. Investigating cilia-proximal features revealed that many cilia were directly adjacent to synapses, suggesting that cilia are poised to encounter locally released signaling molecules. Our analysis indicated that synapse proximity is likely due to random encounters in the neuropil, with no evidence that cilia modulate synapse activity as would be expected in tetrapartite synapses. The observed cell class differences in proximity to synapses were largely due to differences in external cilia length. Many key structural features that differed between neuronal and glial cilia influenced both cilium placement and shape and, thus, exposure to processes and synapses outside the cilium. Together, the ultrastructure both within and around neuronal and glial cilia suggest differences in cilia formation and function across cell types in the brain.

Cell-type-specific inhibitory circuitry from a connectomic census of mouse visual cortex.

Mammalian cortex features a vast diversity of neuronal cell types, each with characteristic anatomical, molecular and functional properties. Synaptic connectivity powerfully shapes how each cell type participates in the cortical circuit, but mapping connectivity rules at the resolution of distinct cell types remains difficult. Here, we used millimeter-scale volumetric electron microscopy1 to investigate the connectivity of all inhibitory neurons across a densely-segmented neuronal population of 1352 cells spanning all layers of mouse visual cortex, producing a wiring diagram of inhibitory connections with more than 70,000 synapses. Taking a data-driven approach inspired by classical neuroanatomy, we classified inhibitory neurons based on the relative targeting of dendritic compartments and other inhibitory cells and developed a novel classification of excitatory neurons based on the morphological and synaptic input properties. The synaptic connectivity between inhibitory cells revealed a novel class of disinhibitory specialist targeting basket cells, in addition to familiar subclasses. Analysis of the inhibitory connectivity onto excitatory neurons found widespread specificity, with many interneurons exhibiting differential targeting of certain subpopulations spatially intermingled with other potential targets. Inhibitory targeting was organized into "motif groups," diverse sets of cells that collectively target both perisomatic and dendritic compartments of the same excitatory targets. Collectively, our analysis identified new organizing principles for cortical inhibition and will serve as a foundation for linking modern multimodal neuronal atlases with the cortical wiring diagram.

Nanometer-scale views of visual cortex reveal anatomical features of primary cilia poised to detect synaptic spillover.

A primary cilium is a thin membrane-bound extension off a cell surface that contains receptors for perceiving and transmitting signals that modulate cell state and activity. While many cell types have a primary cilium, little is known about primary cilia in the brain, where they are less accessible than cilia on cultured cells or epithelial tissues and protrude from cell bodies into a deep, dense network of glial and neuronal processes. Here, we investigated cilia frequency, internal structure, shape, and position in large, high-resolution transmission electron microscopy volumes of mouse primary visual cortex. Cilia extended from the cell bodies of nearly all excitatory and inhibitory neurons, astrocytes, and oligodendrocyte precursor cells (OPCs), but were absent from oligodendrocytes and microglia. Structural comparisons revealed that the membrane structure at the base of the cilium and the microtubule organization differed between neurons and glia. OPC cilia were distinct in that they were the shortest and contained pervasive internal vesicles only occasionally observed in neuron and astrocyte cilia. Investigating cilia-proximal features revealed that many cilia were directly adjacent to synapses, suggesting cilia are well poised to encounter locally released signaling molecules. Cilia proximity to synapses was random, not enriched, in the synapse-rich neuropil. The internal anatomy, including microtubule changes and centriole location, defined key structural features including cilium placement and shape. Together, the anatomical insights both within and around neuron and glia cilia provide new insights into cilia formation and function across cell types in the brain.

NEURD: automated proofreading and feature extraction for connectomics.

We are now in the era of millimeter-scale electron microscopy (EM) volumes collected at nanometer resolution (Shapson-Coe et al., 2021; Consortium et al., 2021). Dense reconstruction of cellular compartments in these EM volumes has been enabled by recent advances in Machine Learning (ML) (Lee et al., 2017; Wu et al., 2021; Lu et al., 2021; Macrina et al., 2021). Automated segmentation methods can now yield exceptionally accurate reconstructions of cells, but despite this accuracy, laborious post-hoc proofreading is still required to generate large connectomes free of merge and split errors. The elaborate 3-D meshes of neurons produced by these segmentations contain detailed morphological information, from the diameter, shape, and branching patterns of axons and dendrites, down to the fine-scale structure of dendritic spines. However, extracting information about 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 each meshed neuron into a compact and extensively-annotated graph representation. With these feature-rich graphs, we implement workflows for state of the art automated post-hoc proofreading of merge errors, cell classification, spine detection, axon-dendritic proximities, and other features that can enable many downstream analyses of neural morphology and connectivity. NEURD can make these new massive and complex datasets more accessible to neuroscience researchers focused on a variety of scientific questions.

Functional connectomics reveals general wiring rule in mouse visual cortex.

To understand how the brain computes, it is important to unravel the relationship between circuit connectivity and function. Previous research has shown that excitatory neurons in layer 2/3 of the primary visual cortex of mice with similar response properties are more likely to form connections. However, technical challenges of combining synaptic connectivity and functional measurements have limited these studies to few, highly local connections. Utilizing the millimeter scale and nanometer resolution of the MICrONS dataset, we studied the connectivity-function relationship in excitatory neurons of the mouse visual cortex across interlaminar and interarea projections, assessing connection selectivity at the coarse axon trajectory and fine synaptic formation levels. A digital twin model of this mouse, that accurately predicted responses to arbitrary video stimuli, enabled a comprehensive characterization of the function of neurons. We found that neurons with highly correlated responses to natural videos tended to be connected with each other, not only within the same cortical area but also across multiple layers and visual areas, including feedforward and feedback connections, whereas we did not find that orientation preference predicted connectivity. The digital twin model separated each neuron's tuning into a feature component (what the neuron responds to) and a spatial component (where the neuron's receptive field is located). We show that the feature, but not the spatial component, predicted which neurons were connected at the fine synaptic scale. Together, our results demonstrate the "like-to-like" connectivity rule generalizes to multiple connection types, and the rich MICrONS dataset is suitable to further refine a mechanistic understanding of circuit structure and function.

CAVE: Connectome Annotation Versioning Engine.

Advances in Electron Microscopy, image segmentation and computational infrastructure have given rise to large-scale and richly annotated connectomic datasets which are increasingly shared across communities. To enable collaboration, users need to be able to concurrently create new annotations and correct errors in the automated segmentation by proofreading. In large datasets, every proofreading edit relabels cell identities of millions of voxels and thousands of annotations like synapses. For analysis, users require immediate and reproducible access to this constantly changing and expanding data landscape. Here, we present the Connectome Annotation Versioning Engine (CAVE), a computational infrastructure for immediate and reproducible connectome analysis in up-to petascale datasets (~1mm3) while proofreading and annotating is ongoing. For segmentation, CAVE provides a distributed proofreading infrastructure for continuous versioning of large reconstructions. Annotations in CAVE are defined by locations such that they can be quickly assigned to the underlying segment which enables fast analysis queries of CAVE's data for arbitrary time points. CAVE supports schematized, extensible annotations, so that researchers can readily design novel annotation types. CAVE is already used for many connectomics datasets, including the largest datasets available to date.

Binary and analog variation of synapses between cortical pyramidal neurons.

Learning from experience depends at least in part on changes in neuronal connections. We present the largest map of connectivity to date between cortical neurons of a defined type (layer 2/3 [L2/3] pyramidal cells in mouse primary visual cortex), which was enabled by automated analysis of serial section electron microscopy images with improved handling of image defects (250 × 140 × 90 µm3 volume). We used the map to identify constraints on the learning algorithms employed by the cortex. Previous cortical studies modeled a continuum of synapse sizes by a log-normal distribution. A continuum is consistent with most neural network models of learning, in which synaptic strength is a continuously graded analog variable. Here, we show that synapse size, when restricted to synapses between L2/3 pyramidal cells, is well modeled by the sum of a binary variable and an analog variable drawn from a log-normal distribution. Two synapses sharing the same presynaptic and postsynaptic cells are known to be correlated in size. We show that the binary variables of the two synapses are highly correlated, while the analog variables are not. Binary variation could be the outcome of a Hebbian or other synaptic plasticity rule depending on activity signals that are relatively uniform across neuronal arbors, while analog variation may be dominated by other influences such as spontaneous dynamical fluctuations. We discuss the implications for the longstanding hypothesis that activity-dependent plasticity switches synapses between bistable states.

Structure and function of axo-axonic inhibition.

Inhibitory neurons in mammalian cortex exhibit diverse physiological, morphological, molecular, and connectivity signatures. While considerable work has measured the average connectivity of several interneuron classes, there remains a fundamental lack of understanding of the connectivity distribution of distinct inhibitory cell types with synaptic resolution, how it relates to properties of target cells, and how it affects function. Here, we used large-scale electron microscopy and functional imaging to address these questions for chandelier cells in layer 2/3 of the mouse visual cortex. With dense reconstructions from electron microscopy, we mapped the complete chandelier input onto 153 pyramidal neurons. We found that synapse number is highly variable across the population and is correlated with several structural features of the target neuron. This variability in the number of axo-axonic ChC synapses is higher than the variability seen in perisomatic inhibition. Biophysical simulations show that the observed pattern of axo-axonic inhibition is particularly effective in controlling excitatory output when excitation and inhibition are co-active. Finally, we measured chandelier cell activity in awake animals using a cell-type-specific calcium imaging approach and saw highly correlated activity across chandelier cells. In the same experiments, in vivo chandelier population activity correlated with pupil dilation, a proxy for arousal. Together, these results suggest that chandelier cells provide a circuit-wide signal whose strength is adjusted relative to the properties of target neurons.

Millisecond timescale disinhibition mediates fast information transmission through an avian basal ganglia loop.

Avian song learning shares striking similarities with human speech acquisition and requires a basal ganglia (BG)-thalamo-cortical circuit. Information processing and transmission speed in the BG is thought to be limited by synaptic architecture of two serial inhibitory connections. Propagation speed may be critical in the avian BG circuit given the temporally precise control of musculature during vocalization. We used electrical stimulation of the cortical inputs to the BG to study, with fine time resolution, the functional connectivity within this network. We found that neurons in thalamic and cortical nuclei that are not directly connected with the stimulated area can respond to the stimulation with extremely short latencies. Through pharmacological manipulations, we trace this property back to the BG and show that the cortical stimulation triggers fast disinhibition of the thalamic neurons. Surprisingly, feedforward inhibition mediated by striatal inhibitory neurons onto BG output neurons sometimes precedes the monosynaptic excitatory drive from cortical afferents. The fast feedforward inhibition lengthens a single interspike interval in BG output neurons by just a few milliseconds. This short delay is sufficient to drive a strong, brief increase in firing probability in the target thalamic neurons, evoking short-latency responses. By blocking glutamate receptors in vivo, we show that thalamic responses do not appear to rely on excitatory drive, and we show in a theoretical model that they could be mediated by postinhibitory rebound properties. Such fast signaling through disinhibition and rebound may be a crucial specialization for learning of rapid and temporally precise motor acts such as vocal communication.

Structural correlates of efficient GABAergic transmission in the basal ganglia-thalamus pathway.

Giant inhibitory terminals with multiple synapses, the counterparts of excitatory "detonator" or "driver" terminals, have not been described in the forebrain. Using three-dimensional reconstructions of electron microscopic images, we quantitatively characterize a GABAergic pathway that establishes synaptic contacts exclusively via multiple synapses. Axon terminals of the nigrothalamic pathway formed, on average, 8.5 synapses on large-diameter dendrites and somata of relay cells in the ventromedial nucleus of the rat thalamus. All synapses of a given terminal converged on a single postsynaptic element. The vast majority of the synapses established by a single terminal were not separated by astrocytic processes. Nigrothalamic terminals in the macaque monkey showed the same ultrastructural features both in qualitative and quantitative terms (the median number of synapse per target was also 8.5). The individual synapses were closely spaced in both species. The nearest-neighbor synaptic distances were 169 nm in the rat and 178 nm in the monkey. The average number of synapses within 0.75 microm from any given synapse was 3.8 in the rat and 3.5 in the monkey. The arrangement of synapses described in this study creates favorable conditions for intersynaptic spillover of GABA among the multiple synapses of a single bouton, which can result in larger charge transfer. This could explain faithful and efficient GABAergic signal transmission in the nigrothalamic pathway in the healthy condition and during Parkinson's disease. In addition, our structural data suggest that the rodent nigrothalamic pathway can be a valid model of the primate condition, when the mechanism of GABAergic transmission is studied.

Contrasting the functional properties of GABAergic axon terminals with single and multiple synapses in the thalamus.

Diverse sources of GABAergic inhibition are a major feature of cortical networks, but distinct inhibitory input systems have not been systematically characterized in the thalamus. Here, we contrasted the properties of two independent GABAergic pathways in the posterior thalamic nucleus of rat, one input from the reticular thalamic nucleus (nRT), and one "extrareticular" input from the anterior pretectal nucleus (APT). The vast majority of nRT-thalamic terminals formed single synapses per postsynaptic target and innervated thin distal dendrites of relay cells. In contrast, single APT-thalamic terminals formed synaptic contacts exclusively via multiple, closely spaced synapses on thick relay cell dendrites. Quantal analysis demonstrated that the two inputs displayed comparable quantal amplitudes, release probabilities, and multiple release sites. The morphological and physiological data together indicated multiple, single-site contacts for nRT and multisite contacts for APT axons. The contrasting synaptic arrangements of the two pathways were paralleled by different short-term plasticities. The multisite APT-thalamic pathway showed larger charge transfer during 50-100 Hz stimulation compared with the nRT pathway and a greater persistent inhibition accruing during stimulation trains. Our results demonstrate that the two inhibitory systems are morpho-functionally distinct and suggest and that multisite GABAergic terminals are tailored for maintained synaptic inhibition even at high presynaptic firing rates. These data explain the efficacy of extrareticular inhibition in timing relay cell activity in sensory and motor thalamic nuclei. Finally, based on the classic nomenclature and the difference between reticular and extrareticular terminals, we define a novel, multisite GABAergic terminal type (F3) in the thalamus.

Expression of the potassium-chloride co-transporter, KCC2, within the avian song system.

Songbirds learn to produce vocalizations early in life by listening to, then copying the songs of conspecific males. The anterior forebrain pathway, homologous to a basal ganglia-forebrain circuit, is essential for song learning. The projection between the striato-pallidal structure, Area X, and the medial portion of the dorsolateral thalamic nucleus (DLM) is strongly hyperpolarizing in adults, due to a very negative chloride reversal potential (Person & Perkel, Neuron 46:129-140, 2005). The chloride reversal potential is determined, in part, by the expression level of a neuron-specific potassium-chloride cotransporter, KCC2, which is developmentally upregulated in mammals. To determine whether a similar upregulation in KCC2 expression occurs at the Area X to DLM synapse during development, we examined the expression level of KCC2 in adult zebra finches across the song system as well as during development in the Area X - DLM synapse. We demonstrate that KCC2 is expressed in a subset of neurons throughout the song system, including HVC (used as a proper name), robust nucleus of the arcopallium (RA), lateral magnocellular nucleus of the anterior nidopallium (LMAN), Area X, and DLM. The majority of pallidal-like projection neurons in Area X showed KCC2 immunoreactivity. In adults, KCC2 expression was robust within DLM, and was upregulated between 14 and 24 days post hatching, before the onset of song learning. Light and electron microscopic analysis indicated that KCC2 immunoreactivity is strongly associated with the plasma membrane. Thus, in the song system as in the mammalian brain, KCC2 expression is well placed to modulate the GABAA reversal potential.

Endocannabinoid signaling in rat somatosensory cortex: laminar differences and involvement of specific interneuron types.

Endocannabinoid-mediated retrograde signaling exerts powerful control over synaptic transmission in many brain areas. However, in the neocortex, the precise laminar, cellular, and subcellular localization of the type 1 cannabinoid receptor (CB1) as well as its function has been elusive. Here we combined multiple immunolabeling with whole-cell recordings to investigate the morpho-functional characteristics of cannabinoid signaling in rat somatosensory cortex. Immunostaining for CB1 revealed axonal and somatic labeling with striking layer specificity: a high density of CB1-positive fibers was seen in layers II-III, in layer VI, and in upper layer V, whereas other layers had sparse (layer IV) or hardly any (layer I) staining. Membrane staining for CB1 was only found in axon terminals, all of which contained GABA and formed symmetric synapses. Double immunostaining also revealed that CB1-positive cells formed two neurochemically distinct subpopulations: two-thirds were cholecystokinin positive and one-third expressed calbindin, each subserving specific inhibitory functions in cortical networks. In addition, cannabinoid sensitivity of GABAergic input showed striking layer specificity, as revealed by both electrophysiological and anatomical experiments. We found a unique population of large pyramidal neurons in layer VB that received much less perisomatic innervation from CB1-expressing GABAergic axon terminals and, accordingly, showed no depolarization-induced suppression of inhibition, unlike pyramidal cells in layer II, and a population of small pyramidal cells in layer V. This suggests that inhibitory control of pyramidal cells involved in intracortical or corticostriatal processing is fine-tuned by activity-dependent endocannabinoid signaling, whereas inhibition of pyramidal cells relaying cortical information to lower subcortical effector centers often lacks this plasticity.

The serine hydrolase ABHD6 controls the accumulation and efficacy of 2-AG at cannabinoid receptors.

The endocannabinoid 2-arachidonoylglycerol (2-AG) regulates neurotransmission and neuroinflammation by activating CB1 cannabinoid receptors on neurons and CB2 cannabinoid receptors on microglia. Enzymes that hydrolyze 2-AG, such as monoacylglycerol lipase, regulate the accumulation and efficacy of 2-AG at cannabinoid receptors. We found that the recently described serine hydrolase alpha-beta-hydrolase domain 6 (ABHD6) also controls the accumulation and efficacy of 2-AG at cannabinoid receptors. In cells from the BV-2 microglia cell line, ABHD6 knockdown reduced hydrolysis of 2-AG and increased the efficacy with which 2-AG can stimulate CB2-mediated cell migration. ABHD6 was expressed by neurons in primary culture and its inhibition led to activity-dependent accumulation of 2-AG. In adult mouse cortex, ABHD6 was located postsynaptically and its selective inhibition allowed the induction of CB1-dependent long-term depression by otherwise subthreshold stimulation. Our results indicate that ABHD6 is a rate-limiting step of 2-AG signaling and is therefore a bona fide member of the endocannabinoid signaling system.

Heterogeneous output pathways link the anterior pretectal nucleus with the zona incerta and the thalamus in rat.

The anterior pretectal nucleus (APT) and the zona incerta (ZI) are diencephalic nuclei that exert a strong inhibitory influence selectively in higher order thalamic relays. The APT is also known to project to the ZI as well as the thalamus, but anatomical details of the APT-ZI projection have not been described. In the present study, the efferent pathways of the APT were examined in the APT-ZI-thalamus network by using anterograde and retrograde tracing in combination with pre- and postembedding immunocytochemical stainings and in situ hybridization. The vast majority of APT fibers selectively innervated the parvalbumin-positive, ventral part of the ZI, which contains ZI neurons with axons projecting to higher order thalamic nuclei. The APT-ZI pathway consisted of both gamma-aminobutyric acid (GABA)-negative and GABA-positive components; 38.2% of the terminals in the ZI contained GABA, and 8.6% of the projecting somata in the APT were glutamic acid decarboxylase 67 (GAD67) mRNA positive. The combination of parvalbumin immunostaining with retrograde tracing showed that strongly and weakly parvalbumin-positive as well as parvalbumin-negative neurons were all among the population of APT cells projecting to the ZI. Similar heterogeneity was found among the APT cells projecting to the thalamus. Double retrograde tracing from higher order thalamic nuclei and their topographically matched ZI regions revealed hardly any APT neuron with dual projections. Our data suggest that both ZI and the higher order thalamic relays are innervated by distinct, physiologically heterogeneous APT neurons. These various efferent pathways probably interact via the rich recurrent collaterals of the projecting APT cells. Therefore, the powerful, GABAergic APT and ZI outputs to the thalamus are apparently co-modulated in a synergistic manner via dual excitatory and inhibitory APT-ZI connections.