The Mind of a Mouse.

Large scientific projects in genomics and astronomy are influential not because they answer any single question but because they enable investigation of continuously arising new questions from the same data-rich sources. Advances in automated mapping of the brain's synaptic connections (connectomics) suggest that the complicated circuits underlying brain function are ripe for analysis. We discuss benefits of mapping a mouse brain at the level of synapses.

Neuropathic pain caused by miswiring and abnormal end organ targeting.

Nerve injury leads to chronic pain and exaggerated sensitivity to gentle touch (allodynia) as well as a loss of sensation in the areas in which injured and non-injured nerves come together1-3. The mechanisms that disambiguate these mixed and paradoxical symptoms are unknown. Here we longitudinally and non-invasively imaged genetically labelled populations of fibres that sense noxious stimuli (nociceptors) and gentle touch (low-threshold afferents) peripherally in the skin for longer than 10 months after nerve injury, while simultaneously tracking pain-related behaviour in the same mice. Fully denervated areas of skin initially lost sensation, gradually recovered normal sensitivity and developed marked allodynia and aversion to gentle touch several months after injury. This reinnervation-induced neuropathic pain involved nociceptors that sprouted into denervated territories precisely reproducing the initial pattern of innervation, were guided by blood vessels and showed irregular terminal connectivity in the skin and lowered activation thresholds mimicking low-threshold afferents. By contrast, low-threshold afferents-which normally mediate touch sensation as well as allodynia in intact nerve territories after injury4-7-did not reinnervate, leading to an aberrant innervation of tactile end organs such as Meissner corpuscles with nociceptors alone. Genetic ablation of nociceptors fully abrogated reinnervation allodynia. Our results thus reveal the emergence of a form of chronic neuropathic pain that is driven by structural plasticity, abnormal terminal connectivity and malfunction of nociceptors during reinnervation, and provide a mechanistic framework for the paradoxical sensory manifestations that are observed clinically and can impose a heavy burden on patients.

RoboEM: automated 3D flight tracing for synaptic-resolution connectomics.

Mapping neuronal networks from three-dimensional electron microscopy (3D-EM) data still poses substantial reconstruction challenges, in particular for thin axons. Currently available automated image segmentation methods require manual proofreading for many types of connectomic analysis. Here we introduce RoboEM, an artificial intelligence-based self-steering 3D 'flight' system trained to navigate along neurites using only 3D-EM data as input. Applied to 3D-EM data from mouse and human cortex, RoboEM substantially improves automated state-of-the-art segmentations and can replace manual proofreading for more complex connectomic analysis problems, yielding computational annotation cost for cortical connectomes about 400-fold lower than the cost of manual error correction.

High-contrast en bloc staining of mouse whole-brain and human brain samples for EM-based connectomics.

Connectomes of human cortical gray matter require high-contrast homogeneously stained samples sized at least 2 mm on a side, and a mouse whole-brain connectome requires samples sized at least 5-10 mm on a side. Here we report en bloc staining and embedding protocols for these and other applications, removing a key obstacle for connectomic analyses at the mammalian whole-brain level.

Axonal synapse sorting in medial entorhinal cortex.

Research on neuronal connectivity in the cerebral cortex has focused on the existence and strength of synapses between neurons, and their location on the cell bodies and dendrites of postsynaptic neurons. The synaptic architecture of individual presynaptic axonal trees, however, remains largely unknown. Here we used dense reconstructions from three-dimensional electron microscopy in rats to study the synaptic organization of local presynaptic axons in layer 2 of the medial entorhinal cortex, the site of grid-like spatial representations. We observe path-length-dependent axonal synapse sorting, such that axons of excitatory neurons sequentially target inhibitory neurons followed by excitatory neurons. Connectivity analysis revealed a cellular feedforward inhibition circuit involving wide, myelinated inhibitory axons and dendritic synapse clustering. Simulations show that this high-precision circuit can control the propagation of synchronized activity in the medial entorhinal cortex, which is known for temporally precise discharges.

webKnossos: efficient online 3D data annotation for connectomics.

We report webKnossos, an in-browser annotation tool for 3D electron microscopic data. webKnossos provides flight mode, a single-view egocentric reconstruction method enabling trained annotator crowds to reconstruct at a speed of 1.5 ± 0.6 mm/h for axons and 2.1 ± 0.9 mm/h for dendrites in 3D electron microscopic data from mammalian cortex. webKnossos accelerates neurite reconstruction for connectomics by 4- to 13-fold compared with current state-of-the-art tools, thus extending the range of connectomes that can realistically be mapped in the future.

Connectomic reconstruction of the inner plexiform layer in the mouse retina.

Comprehensive high-resolution structural maps are central to functional exploration and understanding in biology. For the nervous system, in which high resolution and large spatial extent are both needed, such maps are scarce as they challenge data acquisition and analysis capabilities. Here we present for the mouse inner plexiform layer--the main computational neuropil region in the mammalian retina--the dense reconstruction of 950 neurons and their mutual contacts. This was achieved by applying a combination of crowd-sourced manual annotation and machine-learning-based volume segmentation to serial block-face electron microscopy data. We characterize a new type of retinal bipolar interneuron and show that we can subdivide a known type based on connectivity. Circuit motifs that emerge from our data indicate a functional mechanism for a known cellular response in a ganglion cell that detects localized motion, and predict that another ganglion cell is motion sensitive.

Structural neurobiology: missing link to a mechanistic understanding of neural computation.

High-resolution, comprehensive structural information is often the final arbiter between competing mechanistic models of biological processes, and can serve as inspiration for new hypotheses. In molecular biology, definitive structural data at atomic resolution are available for many macromolecules; however, information about the structure of the brain is much less complete, both in scope and resolution. Several technical developments over the past decade, such as serial block-face electron microscopy and trans-synaptic viral tracing, have made the structural biology of neural circuits conceivable: we may be able to obtain the structural information needed to reconstruct the network of cellular connections for large parts of, or even an entire, mouse brain within a decade or so. Given that the brain's algorithms are ultimately encoded by this network, knowing where all of these connections are should, at the very least, provide the data needed to distinguish between models of neural computation.

Wiring specificity in the direction-selectivity circuit of the retina.

The proper connectivity between neurons is essential for the implementation of the algorithms used in neural computations, such as the detection of directed motion by the retina. The analysis of neuronal connectivity is possible with electron microscopy, but technological limitations have impeded the acquisition of high-resolution data on a large enough scale. Here we show, using serial block-face electron microscopy and two-photon calcium imaging, that the dendrites of mouse starburst amacrine cells make highly specific synapses with direction-selective ganglion cells depending on the ganglion cell's preferred direction. Our findings indicate that a structural (wiring) asymmetry contributes to the computation of direction selectivity. The nature of this asymmetry supports some models of direction selectivity and rules out others. It also puts constraints on the developmental mechanisms behind the formation of synaptic connections. Our study demonstrates how otherwise intractable neurobiological questions can be addressed by combining functional imaging with the analysis of neuronal connectivity using large-scale electron microscopy.

Cellular-resolution connectomics: challenges of dense neural circuit reconstruction.

Neuronal networks are high-dimensional graphs that are packed into three-dimensional nervous tissue at extremely high density. Comprehensively mapping these networks is therefore a major challenge. Although recent developments in volume electron microscopy imaging have made data acquisition feasible for circuits comprising a few hundreds to a few thousands of neurons, data analysis is massively lagging behind. The aim of this perspective is to summarize and quantify the challenges for data analysis in cellular-resolution connectomics and describe current solutions involving online crowd-sourcing and machine-learning approaches.

A barrel-related interneuron in layer 4 of rat somatosensory cortex with a high intrabarrel connectivity.

Synaptic connections between identified fast-spiking (FS), parvalbumin (PV)-positive interneurons, and excitatory spiny neurons in layer 4 (L4) of the barrel cortex were investigated using patch-clamp recordings and simultaneous biocytin fillings. Three distinct clusters of FS L4 interneurons were identified based on their axonal morphology relative to the barrel column suggesting that these neurons do not constitute a homogeneous interneuron population. One L4 FS interneuron type had an axonal domain strictly confined to a L4 barrel and was therefore named "barrel-confined inhibitory interneuron" (BIn). BIns established reliable inhibitory synaptic connections with L4 spiny neurons at a high connectivity rate of 67%, of which 69% were reciprocal. Unitary IPSPs at these connections had a mean amplitude of 0.9 ± 0.8 mV with little amplitude variation and weak short-term synaptic depression. We found on average 3.7 ± 1.3 putative inhibitory synaptic contacts that were not restricted to perisomatic areas. In conclusion, we characterized a novel type of barrel cortex interneuron in the major thalamo-recipient layer 4 forming dense synaptic networks with L4 spiny neurons. These networks constitute an efficient and powerful inhibitory feedback system, which may serve to rapidly reset the barrel microcircuitry following sensory activation.

Synaptic Conductance Estimates of the Connection Between Local Inhibitor Interneurons and Pyramidal Neurons in Layer 2/3 of a Cortical Column.

Stimulation of a principal whisker yields sparse action potential (AP) spiking in layer 2/3 (L2/3) pyramidal neurons in a cortical column of rat barrel cortex. The low AP rates in pyramidal neurons could be explained by activation of interneurons in L2/3 providing inhibition onto L2/3 pyramidal neurons. L2/3 interneurons classified as local inhibitors based on their axonal projection in the same column were reported to receive strong excitatory input from spiny neurons in L4, which are also the main source of the excitatory input to L2/3 pyramidal neurons. Here, we investigated the remaining synaptic connection in this intracolumnar microcircuit. We found strong and reliable inhibitory synaptic transmission between intracolumnar L2/3 local-inhibitor-to-L2/3 pyramidal neuron pairs [inhibitory postsynaptic potential (IPSP) amplitude -0.88 ± 0.67 mV]. On average, 6.2 ± 2 synaptic contacts were made by L2/3 local inhibitors onto L2/3 pyramidal neurons at 107 ± 64 µm path distance from the pyramidal neuron soma, thus overlapping with the distribution of synaptic contacts from L4 spiny neurons onto L2/3 pyramidal neurons (67 ± 34 µm). Finally, using compartmental simulations, we determined the synaptic conductance per synaptic contact to be 0.77 ± 0.4 nS. We conclude that the synaptic circuit from L4 to L2/3 can provide efficient shunting inhibition that is temporally and spatially aligned with the excitatory input from L4 to L2/3.

Inhibitory interneurons in a cortical column form hot zones of inhibition in layers 2 and 5A.

Although physiological data on microcircuits involving a few inhibitory neurons in the mammalian cerebral cortex are available, data on the quantitative relation between inhibition and excitation in cortical circuits involving thousands of neurons are largely missing. Because the distribution of neurons is very inhomogeneous in the cerebral cortex, it is critical to map all neurons in a given volume rather than to rely on sparse sampling methods. Here, we report the comprehensive mapping of interneurons (INs) in cortical columns of rat somatosensory cortex, immunolabeled for neuron-specific nuclear protein and glutamate decarboxylase. We found that a column contains ~2,200 INs (11.5% of ~19,000 neurons), almost a factor of 2 less than previously estimated. The density of GABAergic neurons was inhomogeneous between layers, with peaks in the upper third of L2/3 and in L5A. IN density therefore defines a distinct layer 2 in the sensory neocortex. In addition, immunohistochemical markers of IN subtypes were layer-specific. The "hot zones" of inhibition in L2 and L5A match the reported low stimulus-evoked spiking rates of excitatory neurons in these layers, suggesting that these inhibitory hot zones substantially suppress activity in the neocortex.

Petilla terminology: nomenclature of features of GABAergic interneurons of the cerebral cortex.

Neuroscience produces a vast amount of data from an enormous diversity of neurons. A neuronal classification system is essential to organize such data and the knowledge that is derived from them. Classification depends on the unequivocal identification of the features that distinguish one type of neuron from another. The problems inherent in this are particularly acute when studying cortical interneurons. To tackle this, we convened a representative group of researchers to agree on a set of terms to describe the anatomical, physiological and molecular features of GABAergic interneurons of the cerebral cortex. The resulting terminology might provide a stepping stone towards a future classification of these complex and heterogeneous cells. Consistent adoption will be important for the success of such an initiative, and we also encourage the active involvement of the broader scientific community in the dynamic evolution of this project.

3D reconstruction and standardization of the rat vibrissal cortex for precise registration of single neuron morphology.

The three-dimensional (3D) structure of neural circuits is commonly studied by reconstructing individual or small groups of neurons in separate preparations. Investigation of structural organization principles or quantification of dendritic and axonal innervation thus requires integration of many reconstructed morphologies into a common reference frame. Here we present a standardized 3D model of the rat vibrissal cortex and introduce an automated registration tool that allows for precise placement of single neuron reconstructions. We (1) developed an automated image processing pipeline to reconstruct 3D anatomical landmarks, i.e., the barrels in Layer 4, the pia and white matter surfaces and the blood vessel pattern from high-resolution images, (2) quantified these landmarks in 12 different rats, (3) generated an average 3D model of the vibrissal cortex and (4) used rigid transformations and stepwise linear scaling to register 94 neuron morphologies, reconstructed from in vivo stainings, to the standardized cortex model. We find that anatomical landmarks vary substantially across the vibrissal cortex within an individual rat. In contrast, the 3D layout of the entire vibrissal cortex remains remarkably preserved across animals. This allows for precise registration of individual neuron reconstructions with approximately 30 µm accuracy. Our approach could be used to reconstruct and standardize other anatomically defined brain areas and may ultimately lead to a precise digital reference atlas of the rat brain.

Cell type-specific three-dimensional structure of thalamocortical circuits in a column of rat vibrissal cortex.

Soma location, dendrite morphology, and synaptic innervation may represent key determinants of functional responses of individual neurons, such as sensory-evoked spiking. Here, we reconstruct the 3D circuits formed by thalamocortical afferents from the lemniscal pathway and excitatory neurons of an anatomically defined cortical column in rat vibrissal cortex. We objectively classify 9 cortical cell types and estimate the number and distribution of their somata, dendrites, and thalamocortical synapses. Somata and dendrites of most cell types intermingle, while thalamocortical connectivity depends strongly upon the cell type and the 3D soma location of the postsynaptic neuron. Correlating dendrite morphology and thalamocortical connectivity to functional responses revealed that the lemniscal afferents can account for some of the cell type- and location-specific subthreshold and spiking responses after passive whisker touch (e.g., in layer 4, but not for other cell types, e.g., in layer 5). Our data provides a quantitative 3D prediction of the cell type-specific lemniscal synaptic wiring diagram and elucidates structure-function relationships of this physiologically relevant pathway at single-cell resolution.

Large-scale automated histology in the pursuit of connectomes.

How does the brain compute? Answering this question necessitates neuronal connectomes, annotated graphs of all synaptic connections within defined brain areas. Further, understanding the energetics of the brain's computations requires vascular graphs. The assembly of a connectome requires sensitive hardware tools to measure neuronal and neurovascular features in all three dimensions, as well as software and machine learning for data analysis and visualization. We present the state of the art on the reconstruction of circuits and vasculature that link brain anatomy and function. Analysis at the scale of tens of nanometers yields connections between identified neurons, while analysis at the micrometer scale yields probabilistic rules of connection between neurons and exact vascular connectivity.

Connectomic comparison of mouse and human cortex.

The human cerebral cortex houses 1000 times more neurons than that of the cerebral cortex of a mouse, but the possible differences in synaptic circuits between these species are still poorly understood. We used three-dimensional electron microscopy of mouse, macaque, and human cortical samples to study their cell type composition and synaptic circuit architecture. The 2.5-fold increase in interneurons in humans compared with mice was compensated by a change in axonal connection probabilities and therefore did not yield a commensurate increase in inhibitory-versus-excitatory synaptic input balance on human pyramidal cells. Rather, increased inhibition created an expanded interneuron-to-interneuron network, driven by an expansion of interneuron-targeting interneuron types and an increase in their synaptic selectivity for interneuron innervation. These constitute key neuronal network alterations in the human cortex.

Connectomic analysis of thalamus-driven disinhibition in cortical layer 4.

Sensory signals are transmitted via the thalamus primarily to layer 4 (L4) of the primary sensory cortices. While information about average neuronal connectivity in L4 is available, its detailed higher-order circuit structure is not known. Here, we used three-dimensional electron microscopy for a connectomic analysis of the thalamus-driven inhibitory network in L4. We find that thalamic input drives a subset of interneurons with high specificity, which in turn target excitatory neurons with subtype specificity. These interneurons create a directed disinhibitory network directly driven by the thalamic input. Neuronal activity recordings show that strong synchronous sensory activation yields about 1.5-fold stronger activation of star pyramidal cells than spiny stellates, in line with differential windows of opportunity for activation of excitatory neurons in the thalamus-driven disinhibitory circuit model. With this, we have identified a high degree of specialization of the microcircuitry in L4 of the primary sensory cortex.

Cell type-specific thalamic innervation in a column of rat vibrissal cortex.

This is the concluding article in a series of 3 studies that investigate the anatomical determinants of thalamocortical (TC) input to excitatory neurons in a cortical column of rat primary somatosensory cortex (S1). We used viral synaptophysin-enhanced green fluorescent protein expression in thalamic neurons and reconstructions of biocytin-labeled cortical neurons in TC slices to quantify the number and distribution of boutons from the ventral posterior medial (VPM) and posteromedial (POm) nuclei potentially innervating dendritic arbors of excitatory neurons located in layers (L)2-6 of a cortical column in rat somatosensory cortex. We found that 1) all types of excitatory neurons potentially receive substantial TC input (90-580 boutons per neuron); 2) pyramidal neurons in L3-L6 receive dual TC input from both VPM and POm that is potentially of equal magnitude for thick-tufted L5 pyramidal neurons (ca. 300 boutons each from VPM and POm); 3) L3, L4, and L5 pyramidal neurons have multiple (2-4) subcellular TC innervation domains that match the dendritic compartments of pyramidal cells; and 4) a subtype of thick-tufted L5 pyramidal neurons has an additional VPM innervation domain in L4. The multiple subcellular TC innervation domains of L5 pyramidal neurons may partly explain their specific action potential patterns observed in vivo. We conclude that the substantial potential TC innervation of all excitatory neuron types in a cortical column constitutes an anatomical basis for the initial near-simultaneous representation of a sensory stimulus in different neuron types.