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The cerebellum is thought to help detect and correct errors between intended and executed commands(1,2) and is critical for social behaviours, cognition and emotion 3 Computations for motor control must be performed quicklyto correct errors in real time and should be sensitive to small differences between patterns for fine error correction while being resilient to noise(7). Influential theories of cerebellar information processing have largely assumed random network connectivity, which increases the encoding capacity ofthe network's first layer(8-)(13). However, maximizing encoding capacity reduces the resilience to noise(7). To understand how neuronal circuits address this fundamental trade-off, we mapped the feedforward connectivity in the mouse cerebellar cortex using automated large-scale transmission electron microscopy and convolutional neural network-based image segmentation. We found that both the input and output layers ofthe circuit exhibit redundant and selective connectivity motifs, which contrast with prevailing models. Numerical simulations suggest that these redundant, non-random connectivity motifs increase the resilience to noise at a negligible cost to the overall encoding capacity. This work reveals how neuronal network structure can support a trade-off between encoding capacity and redundancy, unveiling principles of biological network architecture with implications for the design of artificial neural networks.

Animal movement is controlled by motor neurons (MNs), which project out of the central nervous system to activate muscles. Because individual muscles may be used in many different behaviors, MN activity must be flexibly coordinated by dedicated premotor circuitry, the organization of which remains largely unknown. Here, we use comprehensive reconstruction of neuron anatomy and synaptic connectivity from volumetric electron microscopy (i.e., connectomics) to analyze the wiring logic of motor circuits controlling theDrosophilaleg and wing. We find that both leg and wing premotor networks are organized into modules that link MNs innervating muscles with related functions. However, the connectivity patterns within leg and wing motor modules are distinct. Leg premotor neurons exhibit proportional gradients of synaptic input onto MNs within each module, revealing a novel circuit basis for hierarchical MN recruitment. In comparison, wing premotor neurons lack proportional synaptic connectivity, which may allow muscles to be recruited in different combinations or with different relative timing. By comparing the architecture of distinct limb motor control systems within the same animal, we identify common principles of premotor network organization and specializations that reflect the unique biomechanical constraints and evolutionary origins of leg and wing motor control.

To understand how the cerebellar cortex transforms mossy fiber (MF) inputs into Purkinje cell (PC) outputs, it is vital to delineate the elements of this circuit. Candelabrum cells (CCs) are enigmatic interneurons of the cerebellar cortex that have been identified based on their morphology, but their electrophysiological properties, synaptic connections and function remain unknown. Here, we clarify these properties using electrophysiology, single-nucleus RNA sequencing, in situ hybridization and serial electron microscopy in mice. We find that CCs are the most abundant PC layer interneuron. They are GABAergic, molecularly distinct and present in all cerebellar lobules. Their high resistance renders CC firing highly sensitive to synaptic inputs. CCs are excited by MFs and granule cells and are strongly inhibited by PCs. CCs in turn primarily inhibit molecular layer interneurons, which leads to PC disinhibition. Thus, inputs, outputs and local signals converge onto CCs to allow them to assume a unique role in controlling cerebellar output.

Specialized mechanosensory end organs within mammalian skin—hair follicle-associated lanceolate complexes, Meissner corpuscles, and Pacinian corpuscles—enable our perception of light, dynamic touch1. In each of these end organs, fast-conducting mechanically sensitive neurons, called Aβ low-threshold mechanoreceptors (Aβ LTMRs), associate with resident glial cells, known as terminal Schwann cells (TSCs) or lamellar cells, to form complex axon ending structures. Lanceolate-forming and corpuscle-innervating Aβ LTMRs share a low threshold for mechanical activation, a rapidly adapting (RA) response to force indentation, and high sensitivity to dynamic stimuli1–6. How mechanical stimuli lead to activation of the requisite mechanotransduction channel Piezo27–15and Aβ RA-LTMR excitation across the morphologically dissimilar mechanosensory end organ structures is not understood. Here, we report the precise subcellular distribution of Piezo2 and high-resolution, isotropic 3D reconstructions of all three end organs formed by Aβ RA-LTMRs determined by large volume enhanced Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) imaging. We found that within each end organ, Piezo2 is enriched along the sensory axon membrane and is minimally or not expressed in TSCs and lamellar cells. We also observed a large number of small cytoplasmic protrusions enriched along the Aβ RA-LTMR axon terminals associated with hair follicles, Meissner corpuscles, and Pacinian corpuscles. These axon protrusions reside within close proximity to axonal Piezo2, occasionally contain the channel, and often form adherens junctions with nearby non-neuronal cells. Our findings support a unified model for Aβ RA-LTMR activation in which axon protrusions anchor Aβ RA-LTMR axon terminals to specialized end organ cells, enabling mechanical stimuli to stretch the axon in hundreds to thousands of sites across an individual end organ and leading to activation of proximal Piezo2 channels and excitation of the neuron.

Like the vertebrate spinal cord, the insect ventral nerve cord (VNC) mediates limb sensation and motor control. Here, we applied automated tools for electron microscopy (EM) volume alignment, neuron reconstruction, and synapse prediction to create a draft connectome of theDrosophilaVNC. To interpret the VNC connectome, it is crucial to know its relationship with the rest of the body. We therefore mapped the muscle targets of leg and wing motor neurons in the connectome by comparing their morphology to genetic driver lines, dye fills, and x-ray holographic nano-tomography volumes of the fly leg and wing. Knowing the outputs of the connectome allowed us to identify neural circuits that coordinate the wings with the middle and front legs during escape takeoff. We provide the draft VNC connectome and motor neuron atlas, along with tools for programmatic and interactive access, as community resources.

Our ability to sense and move our bodies relies on proprioceptors, sensory neurons that detect mechanical forces within the body. Proprioceptors are diverse: different subtypes detect different features of joint kinematics, such as position, directional movement, and vibration. However, because they are located within complex and dynamic peripheral tissues, the underlying mechanisms of proprioceptor feature selectivity remain poorly understood. Here, we investigate molecular and biomechanical contributions to proprioceptor diversity in theDrosophilaleg. Using single-nucleus RNA sequencing, we found that different proprioceptor subtypes express similar complements of mechanosensory and other ion channels. However, anatomical reconstruction of the proprioceptive organ and connected tendons revealed major biomechanical differences between proprioceptor subtypes. We constructed a computational model of the proprioceptors and tendons, which identified a putative biomechanical mechanism for joint angle selectivity. The model also predicted the existence of a goniotopic map of joint angle among position-tuned proprioceptors, which we confirmed using calcium imaging. Our findings suggest that biomechanical specialization is a key determinant of proprioceptor feature selectivity inDrosophila. More broadly, our discovery of proprioceptive maps in the fly leg reveals common organizational principles between proprioception and other topographically organized sensory systems.

We develop an automatic method for synaptic partner identification in insect brains and use it to predict synaptic partners in a whole-brain electron microscopy dataset of the fruit fly. The predictions can be used to infer a connectivity graph with high accuracy, thus allowing fast identification of neural pathways. To facilitate circuit reconstruction using our results, we develop CIRCUITMAP, a user interface add-on for the circuit annotation tool CATMAID. A deep-learning-based approach enables automatic identification of synaptically connected neurons in electron microscopy datasets of the fly brain.

Electron microscopy (EM) is a powerful tool for circuit mapping, but identifying specific cell types in EM datasets remains a major challenge. Here we describe a technique enabling simultaneous visualization of multiple genetically identified neuronal populations so that synaptic interactions between them can be unequivocally defined. We present 15 adeno-associated virus constructs and 6 mouse reporter lines for multiplexed EM labeling in the mammalian nervous system. These reporters feature dAPEX2, which exhibits dramatically improved signal compared with previously described ascorbate peroxidases. By targeting this enhanced peroxidase to different subcellular compartments, multiple orthogonal reporters can be simultaneously visualized and distinguished under EM using a protocol compatible with existing EM pipelines. Proof-of-principle double and triple EM labeling experiments demonstrated synaptic connections between primary afferents, descending cortical inputs, and inhibitory interneurons in the spinal cord dorsal horn. Our multiplexed peroxidase-based EM labeling system should therefore greatly facilitate analysis of connectivity in the nervous system.

Neuron-glia interactions play a critical role in the regulation of synapse formation and circuit assembly. Here we demonstrate that canonical Sonic hedgehog (Shh) pathway signaling in cortical astrocytes acts to coordinate layer-specific synaptic connectivity. We show that the Shh receptor Ptch1 is expressed by cortical astrocytes during development and that Shh signaling is necessary and sufficient to promote the expression of genes involved in regulating synaptic development and layer-enriched astrocyte molecular identity. Loss of Shh in layer V neurons reduces astrocyte complexity and coverage by astrocytic processes in tripartite synapses; conversely, cell-autonomous activation of Shh signaling in astrocytes promotes cortical excitatory synapse formation. Furthermore, Shh-dependent genes Lrig1 and Sparc distinctively contribute to astrocyte morphology and synapse formation. Together, these results suggest that Shh secreted from deep-layer cortical neurons acts to specialize the molecular and functional features of astrocytes during development to shape circuit assembly and function.

To effectively control their bodies, animals rely on feedback from proprioceptive mechanosensory neurons. In the Drosophila leg, different proprioceptor subtypes monitor joint position, movement direction, and vibration. Here, we investigate how these diverse sensory signals are integrated by central proprioceptive circuits. We find that signals for leg joint position and directional movement converge in second-order neurons, revealing pathways for local feedback control of leg posture. Distinct populations of second-order neurons integrate tibia vibration signals across pairs of legs, suggesting a role in detecting external substrate vibration. In each pathway, the flow of sensory information is dynamically gated and sculpted by inhibition. Overall, our results reveal parallel pathways for processing of internal and external mechanosensory signals, which we propose mediate feedback control of leg movement and vibration sensing, respectively. The existence of a functional connectivity map also provides a resource for interpreting connectomic reconstruction of neural circuits for leg proprioception.

SUMMARYThe blood-brain barrier (BBB) is critical for protecting the brain and maintaining neuronal homeostasis. Although the BBB is a unique feature of the central nervous system (CNS) vasculature, not all brain regions have the same degree of impermeability. Differences in BBB permeability are important for controlling the local extracellular environment of specific brain regions to regulate the function and plasticity of particular neural circuits. However, how BBB heterogeneity occurs is poorly understood. Here, we demonstrate how regional specialization of the BBB is achieved. With unbiased cell profiling in small, defined brain regions, we compare the median eminence, which has a naturally leaky BBB, with the cortex, which has an impermeable BBB. We identify hundreds of molecular differences in endothelial cells (ECs) and demonstrate the existence of differences in perivascular astrocytes and pericytes in these regions, finding 3 previously unknown subtypes of astrocytes and several key differences in pericytes. By serial electron microscopy reconstruction and a novel, aqueous-based tissue clearing imaging method, we further reveal previously unknown anatomical specializations of these perivascular cells and their unique physical interactions with neighboring ECs. Finally, we identify ligand-receptor pairs between ECs and perivascular cells that may regulate regional BBB integrity in ECs. Using a bioinformatic approach we identified 26 and 26 ligand-receptor pairs underlying EC-pericyte and EC-astrocyte interactions, respectively. Our results demonstrate that differences in ECs, together with region-specific physical and molecular interactions with local perivascular cells, contribute to BBB functional heterogeneity. These regional cell inventories serve as a platform for further investigation of the dynamic and heterogeneous nature of the BBB in other brain regions. Identification of local BBB specializations provides insight into the function of different brain regions and will permit the development of region-specific drug delivery in the CNS.

To understand how the cerebellar cortex transforms mossy fiber (MF) inputs into Purkinje cell (PC) outputs, it is vital to delineate the elements of this circuit. Candelabrum cells (CCs) are enigmatic interneurons of the cerebellar cortex that have been identified based on their morphology, but their electrophysiological properties, synaptic connections, and function remain unknown. Here we clarify these properties using electrophysiology, snRNA sequencing, in situ hybridization, and serial electron microscopy. We find that CCs are the most abundant PC layer interneuron. They are GABAergic, molecularly distinct, and present in all cerebellar lobules. Their high resistance renders CC firing highly sensitive to synaptic inputs. CCs are excited by MFs and granule cells, and strongly inhibited by PCs. CCs in turn inhibit molecular layer interneurons, which leads to PC disinhibition. Thus, inputs, outputs and local signals all converge onto CCs to allow them to assume a unique role in controlling cerebellar output.

Neuron-glia interactions play a critical role in the regulation of synapse formation and neuron specification. The cellular and molecular mechanisms by which neurons and astrocytes communicate and coordinate are not well understood. Here we demonstrate that canonical Sonic hedgehog (Shh) pathway signaling in cortical astrocytes acts to coordinate layer-specific synaptic connectivity and functional circuit development. We show that the Shh receptor Ptch1 is expressed by cortical astrocytes during development and that Shh signaling is necessary and sufficient to promote the expression of genes involved in regulating synaptic development and layer-specific astrocyte molecular identity. Loss of Shh in layer V neurons reduces astrocyte complexity and coverage by astrocytic processes in tripartite synapses, conversely, cell-autonomous activation of Shh signaling in astrocytes promotes cortical excitatory synapse formation. Furthermore, we determined that Shh-dependent genes Lrig1 and Sparc distinctively contribute to astrocyte morphology and synapse formation. Together, these results suggest that Shh secreted from deep layer cortical neurons acts to specialize the molecular and functional features of astrocytes during development to shape circuit assembly and function.

SUMMARYNeuron-glia relationships play a critical role in the regulation of synapse formation and neuronal specification. The cellular and molecular mechanisms by which neurons and astrocytes communicate and coordinate are not well understood. Here we demonstrate that the canonical Sonic hedgehog (Shh) pathway is active in cortical astrocytes, where it acts to coordinate layer-specific synaptic connectivity and functional circuit development. We show that Ptch1 is a Shh receptor that is expressed by cortical astrocytes during development and that Shh signaling is necessary and sufficient to promote the expression of layer-specific astrocyte genes involved in regulating synapse formation and function. Loss of Shh in layer V neurons reduces astrocyte complexity and coverage by astrocytic processes in tripartite synapses, moreover, cell-autonomous activation of Shh signaling in astrocytes promotes cortical excitatory synapse formation. Together, these results suggest that Shh secreted from deep layer cortical neurons acts to specialize the molecular and functional features of astrocytes during development to shape circuit assembly and function.

SUMMARYMany animals use coordinated limb movements to interact with and navigate through the environment. To investigate circuit mechanisms underlying locomotor behavior, we used serial-section electron microscopy (EM) to map synaptic connectivity within a neuronal network that controls limb movements. We present a synapse-resolution EM dataset containing the ventral nerve cord (VNC) of an adult femaleDrosophila melanogaster. To generate this dataset, we developed GridTape, a technology that combines automated serial-section collection with automated high-throughput transmission EM. Using this dataset, we reconstructed 507 motor neurons, including all those that control the legs and wings. We show that a specific class of leg sensory neurons directly synapse onto the largest-caliber motor neuron axons on both sides of the body, representing a unique feedback pathway for fast limb control. We provide open access to the dataset and reconstructions registered to a standard atlas to permit matching of cells between EM and light microscopy data. We also provide GridTape instrumentation designs and software to make large-scale EM data acquisition more accessible and affordable to the scientific community.

SUMMARY To effectively control their bodies, animals rely on feedback from proprioceptive mechanosensory neurons. In the Drosophila leg, different proprioceptor subtypes monitor joint position, movement direction, and vibration. Here, we investigate how these diverse sensory signals are integrated by central proprioceptive circuits. We find that signals for leg joint position and directional movement converge in second-order neurons, revealing pathways for local feedback control of leg posture. Distinct populations of second-order neurons integrate tibia vibration signals across pairs of legs, suggesting a role in detecting external substrate vibration. In each pathway, the flow of sensory information is dynamically gated and sculpted by inhibition. Overall, our results reveal parallel pathways for processing of internal and external mechanosensory signals, which we propose mediate feedback control of leg movement and vibration sensing, respectively. The existence of a functional connectivity map also provides a resource for interpreting connectomic reconstruction of neural circuits for leg proprioception., In brief To understand how diverse proprioceptive signals from the Drosophila leg are integrated by downstream circuits, Chen et al. use optogenetics and calcium imaging to map functional connectivity between sensory and central neurons. This work identifies parallel neural pathways for processing leg vibration vs. joint position and movement., Graphical abstract

Investigating the dense meshwork of wires and synapses that form neuronal circuits is possible with the high resolution of serial-section electron microscopy (ssEM)1. However, the imaging scale required to comprehensively reconstruct axons and dendrites is more than 10 orders of magnitude smaller than the spatial extents occupied by networks of interconnected neurons2—some of which span nearly the entire brain. The difficulties in generating and handling data for relatively large volumes at nanoscale resolution has thus restricted all studies in vertebrates to neuron fragments, thereby hindering investigations of complete circuits. These efforts were transformed by recent advances in computing, sample handling, and imaging techniques1, but examining entire brains at high resolution remains a challenge. Here we present ssEM data for a complete 5.5 days post-fertilisation larval zebrafish brain. Our approach utilizes multiple rounds of targeted imaging at different scales to reduce acquisition time and data management. The resulting dataset can be analysed to reconstruct neuronal processes, allowing us to, for example, survey all the myelinated axons (the projectome). Further, our reconstructions enabled us to investigate the precise projections of neurons and their contralateral counterparts. In particular, we observed that myelinated axons of reticulospinal and lateral line afferent neurons exhibit remarkable bilateral symmetry. Additionally, we found that fasciculated reticulospinal axons maintain the same neighbour relations throughout the extent of their projections. Furthermore, we use the dataset to set the stage for whole-brain comparisons of structure and function by co-registering functional reference atlases and in vivo two-photon fluorescence microscopy data from the same specimen. We provide the complete dataset and reconstructions as an open-access resource for neurobiologists and others interested in the ultrastructure of the larval zebrafish.

The study of neural circuits requires the reconstruction of neurons and the identification of synaptic connections between them. To scale the reconstruction to the size of whole-brain datasets, semi-automatic methods are needed to solve those tasks. Here, we present an automatic method for synaptic partner identification in insect brains, which uses convolutional neural networks to identify post-synaptic sites and their pre-synaptic partners. The networks can be trained from human generated point annotations alone and require only simple post-processing to obtain final predictions. We used our method to extract 244 million putative synaptic partners in the fifty-teravoxel full adult fly brain (FAFB) electron microscopy (EM) dataset and evaluated its accuracy on 146,643 synapses from 702 neurons with a total cable length of 312 mm in four different brain regions. The predicted synaptic connections can be used together with a neuron segmentation to infer a connectivity graph with high accuracy: between 92% and 96% of edges linking connected neurons are correctly classified as weakly connected (less than five synapses) and strongly connected (at least five synapses). Our synaptic partner predictions for the FAFB dataset are publicly available, together with a query library allowing automatic retrieval of up- and downstream neurons.

To investigate circuit mechanisms underlying locomotor behavior, we used serial-section electron microscopy (EM) to acquire a synapse-resolution dataset containing the ventral nerve cord (VNC) of an adult female Drosophila melanogaster. To generate this dataset, we developed GridTape, a technology that combines automated serial-section collection with automated high-throughput transmission EM. Using this dataset, we studied neuronal networks that control leg and wing movements by reconstructing all 507 motor neurons that control the limbs. We show that a specific class of leg sensory neurons synapses directly onto motor neurons with the largest-caliber axons on both sides of the body, representing a unique pathway for fast limb control. We provide open access to the dataset and reconstructions registered to a standard atlas to permit matching of cells between EM and light microscopy data. We also provide GridTape instrumentation designs and software to make large-scale EM more accessible and affordable to the scientific community.

Serial-section electron microscopy is the method of choice for studying cellular structure and network connectivity in the brain. We have built a pipeline of parallel imaging using transmission electron automated microscopes (piTEAM) that scales this technology and enables the acquisition of petascale datasets containing local cortical microcircuits. The distributed platform is composed of multiple transmission electron microscopes that image, in parallel, different sections from the same block of tissue, all under control of a custom acquisition software (pyTEM) that implements 24/7 continuous autonomous imaging. The suitability of this architecture for large scale electron microscopy imaging was demonstrated by acquiring a volume of more than 1 mm3 of mouse neocortex spanning four different visual areas. Over 26,500 ultrathin tissue sections were imaged, yielding a dataset of more than 2 petabytes. Our current burst imaging rate is 500 Mpixel/s (image capture only) per microscope and net imaging rate is 100 Mpixel/s (including stage movement, image capture, quality control, and post processing). This brings the combined burst acquisition rate of the pipeline to 3 Gpixel/s and the net rate to 600 Mpixel/s with six microscopes running acquisition in parallel, which allowed imaging a cubic millimeter of mouse visual cortex at synaptic resolution in less than 6 months.

We propose an asymmetrically cyclic adversarial network that performs denoising tasks to improve electron microscopy (EM) image analysis. Deep learning-based denoising methods have typically been trained either with matching pairs of noise-free and noise-corrupted images or by leveraging prior knowledge of noise distributions. Neither of these options is feasible in high-throughput EM imaging pipelines. Our proposed denoising method employs independently acquired noise-free, noise pattern, and noise-corrupted images to automatically learn the underlying noise model and generate denoised outputs. This method is based on three-way cyclic constraints with adversarial training of a deep network to improve the quality of acquired images without paired training data. Its utility is demonstrated for cases where imaging substrates add noise and where acquisition conditions contribute noise. We show that our method, which builds on the concept of CycleGAN, outperforms the current state-of-the-art denoising approaches Noise2Noise and Noise2Void, as well as other learning-based techniques.

Transmission electron microscopy (TEM) is an essential tool for studying cells and molecules. We present a tape-based, reel-to-reel pipeline that combines automated serial sectioning with automated high-throughput TEM imaging. This acquisition platform provides nanometer-resolution imaging at fast rates for a fraction of the cost of alternative approaches. We demonstrate the utility of this imaging platform for generating datasets of biological tissues with a focus on examining brain circuits.

Elucidating the structure of neuronal networks provides a foundation for understanding how the nervous system processes information to generate behavior. Despite technological breakthroughs in visible light and electron microscopy, imaging dense nanometer-scale neuronal structures over millimeter-scale tissue volumes remains a challenge. Here, we demonstrate that X-ray holographic nano-tomography is capable of imaging large tissue volumes with sufficient resolution to disentangle dense neuronal circuitry in Drosophila melanogaster and mammalian central and peripheral nervous tissue. Furthermore, we show that automatic segmentation using convolutional neural networks enables rapid extraction of neuronal morphologies from these volumetric datasets. The technique we present allows rapid data collection and analysis of multiple specimens, and can be used correlatively with light microscopy and electron microscopy on the same samples. Thus, X-ray holographic nano-tomography provides a new avenue for discoveries in neuroscience and life sciences in general.

Sensory experience remodels neural circuits in the early postnatal brain through mechanisms that remain to be elucidated. Applying a new method of ultrastructural analysis to the retinogeniculate circuit, we find that visual experience alters the number and structure of synapses between the retina and the thalamus. These changes require the vision-dependent transcription of the receptor Fn14 in thalamic relay neurons and the induction of its ligand TWEAK in microglia. Fn14 functions to increase the number of bulbous spine-associated synapses at retinogeniculate connections likely contributing to the strengthening of the circuit that occurs in response to visual experience. However, at retinogeniculate connections nearby TWEAK-expressing microglia, TWEAK signals via Fn14 to restrict the number of bulbous spines on relay neurons, leading to the elimination of a subset of connections. Thus, TWEAK and Fn14 represent an intercellular signaling axis through which microglia shape retinogeniculate connectivity in response to sensory experience.

SUMMARY Endosomal sorting complex required for transport (ESCRT) complex proteins regulate biogenesis and release of extracellular vesicles (EVs), which enable cell-to-cell communication in the nervous system essential for development and adult function. We recently showed human loss-of-function (LOF) mutations in ESCRT-III member CHMP1A cause autosomal recessive microcephaly with pontocerebellar hypoplasia, but its mechanism was unclear. Here, we show Chmp1a is required for progenitor proliferation in mouse cortex and cerebellum and progenitor maintenance in human cerebral organoids. In Chmp1a null mice, this defect is associated with impaired sonic hedgehog (Shh) secretion and intraluminal vesicle (ILV) formation in multivesicular bodies (MVBs). Furthermore, we show CHMP1A is important for release of an EV subtype that contains AXL, RAB18, and TMED10 (ART) and SHH. Our findings show CHMP1A loss impairs secretion of SHH on ART-EVs, providing molecular mechanistic insights into the role of ESCRT proteins and EVs in the brain., Graphical Abstract, In Brief Extracellular vesicles (EVs) are essential for cell-to-cell communication in developing brain. Coulter et al. show that the human microcephaly gene CHMP1A is required for neuroprogenitor proliferation through regulation of vesicular secretion of the growth factor sonic hedgehog (SHH). CHMP1A specifically impairs SHH secretion on a distinctive EV subtype, ART-EV.

cpg15 is an activity-regulated gene that encodes a membrane-bound ligand that coordinately regulates growth of apposing dendritic and axonal arbors and the maturation of their synapses. These properties make it an attractive candidate for participating in plasticity of the mammalian visual system. Here we compare cpg15 expression during normal development of the rat visual system with that seen in response to dark rearing, monocular blockade of retinal action potentials, or monocular deprivation. Our results show that the onset of cpg15 expression in the visual cortex is coincident with eye opening, and it increases until the peak of the critical period at postnatal day 28 (P28). This early expression is independent of both retinal activity and visual experience. After P28, a component of cpg15 expression in the visual cortex, lateral geniculate nucleus (LGN), and superior colliculus (SC) develops a progressively stronger dependence on retinally driven action potentials. Dark rearing does not affect cpg15 mRNA expression in the LGN and SC at any age, but it does significantly affect its expression in the visual cortex from the peak of the critical period and into adulthood. In dark-reared rats, the peak level of cpg15 expression in the visual cortex at P28 is lower than in controls. Rather than showing the normal decline with maturation, these levels are maintained in dark-reared animals. We suggest that the prolonged plasticity in the visual cortex that is seen in dark-reared animals may result from failure to downregulate genes such as cpg15 that could promote structural remodeling and synaptic maturation.

Circuits in the cerebral cortex consist of thousands of neurons connected by millions of synapses. A precise understanding of these local networks requires relating circuit activity with the underlying network structure. For pyramidal cells in superficial mouse visual cortex (V1), a consensus is emerging that neurons with similar visual response properties excite each other1–5, but the anatomical basis of this recurrent synaptic network is unknown. We combined physiological imaging and large-scale electron microscopy (EM) to study an excitatory network in V1. We found that layer 2/3 neurons organized into subnetworks defined by anatomical connectivity, with more connections within than between groups. More specifically, we found that pyramidal neurons with similar orientation selectivity preferentially formed synapses with each other, despite the fact that axons and dendrites of all orientation selectivities pass near (< 5 μm) each other with roughly equal probability. Therefore, we predict that mechanisms of functionally specific connectivity take place at the length scale of spines. Neurons with similar orientation tuning formed larger synapses, potentially enhancing the net effect of synaptic specificity. With the ability to study thousands of connections in a single circuit, functional connectomics is proving a powerful method to uncover the organizational logic of cortical networks.

The mammalian neocortex is functionally subdivided into architectonically distinct regions that process various types of information based on their source of afferent input. Yet, the modularity of neocortical organization in terms of cell type and intrinsic circuitry allows afferent drive to continuously reassign cortical map space. New aspects of cortical map plasticity include dynamic turnover of dendritic spines on pyramidal neurons and remodeling of interneuron dendritic arbors. While spine remodeling occurs in multiple cortical regions, it is not yet known whether interneuron dendrite remodeling is common across primary sensory and higher-level cortices. It is also unknown whether, like pyramidal dendrites, inhibitory dendrites respect functional domain boundaries. Given the importance of the inhibitory circuitry to adult cortical plasticity and the reorganization of cortical maps, we sought to address these questions by using two-photon microscopy to monitor interneuron dendritic arbors ofthy1-GFP-S transgenic mice expressing GFP in neurons sparsely distributed across the superficial layers of the neocortex. We find that interneuron dendritic branch tip remodeling is a general feature of the adult cortical microcircuit, and that remodeling rates are similar across primary sensory regions of different modalities, but may differ in magnitude between primary sensory versus higher cortical areas. We also show that branch tip remodeling occurs in bursts and respects functional domain boundaries.

A fundamental but unsolved problem in neuroscience is how connections between neurons might underlie information processing in central circuits. Building wiring diagrams of neural networks may accelerate our understanding of how they compute. But even if we had wiring diagrams, it is critical to know what neurons in a circuit are doing: their physiology. In both the retina and cerebral cortex, a great deal is known about topographic specificity, such as lamination, and cell-type specificity of connections. Little, however, is known about connections as they relate to function. Here, we review how advances in functional imaging and electron microscopy have recently allowed the examination of relationships between sensory physiology and synaptic connections in cortical and retinal circuits.

In the cerebral cortex, local circuits consist of tens of thousands of neurons, each of which makes thousands of synaptic connections. Perhaps the biggest impediment to understanding these networks is that we have no wiring diagrams of their interconnections. Even if we had a partial or complete wiring diagram, however, understanding the network would also require information about each neuron's function. Here we show that the relationship between structure and function can be studied in the cortex with a combination of in vivo physiology and network anatomy. We used two-photon calcium imaging to characterize a functional property—the preferred stimulus orientation—of a group of neurons in the mouse primary visual cortex. We then used large-scale electron microscopy (EM) of serial thin sections to trace a portion of these neurons’ local network. Consistent with a prediction from recent physiological experiments, inhibitory interneurons received convergent anatomical input from nearby excitatory neurons with a broad range of preferred orientations, although weak biases could not be rejected.

Multifocal multiphoton microscopy (MMM) enhances imaging speed by parallelization. It is not well understood why the imaging depth of MMM is significantly shorter than conventional single-focus multiphoton microscopy (SMM). In this report, we show that the need for spatially resolved detectors in MMM results in a system that is more sensitive to the scattering of emission photons with reduced imaging depth. For imaging depths down to twice the scattering mean free path length of emission photons (2xl (s) (em)), the emission point spread function (PSF(em)) is found to consist of a narrow, diffraction limited distribution from ballistic emission photons and a broad, relatively low amplitude distribution from scattered photons. Since the scattered photon distribution is approximately 100 times wider than that of the unscattered photons at 2xl (s) (em), image contrast and depth are degraded without compromising resolution. To overcome the imaging depth limitation of MMM, we present a new design that replaces CCD cameras with multi-anode photomultiplier tubes (MAPMTs) allowing more efficient collection of scattered emission photons. We demonstrate that MAPMT-based MMM has imaging depth comparable to SMM with equivalent sensitivity by imaging tissue phantoms, ex vivo human skin specimens based on endogenous fluorophores, and green fluorescent protein (GFP) expressing neurons in mouse brain slices.

To understand the cellular and circuit mechanisms of experience-dependent plasticity, neurons and their synapses need to be studied in the intact brain over extended periods of time. Two-photon excitation laser scanning microscopy (2PLSM), together with expression of fluorescent proteins, enables high-resolution imaging of neuronal structure in vivo. In this protocol we describe a chronic cranial window to obtain optical access to the mouse cerebral cortex for long-term imaging. A small bone flap is replaced with a coverglass, which is permanently sealed in place with dental acrylic, providing a clear imaging window with a large field of view (approximately 0.8-12 mm(2)). The surgical procedure can be completed within approximately 1 h. The preparation allows imaging over time periods of months with arbitrary imaging intervals. The large size of the imaging window facilitates imaging of ongoing structural plasticity of small neuronal structures in mice, with low densities of labeled neurons. The entire dendritic and axonal arbor of individual neurons can be reconstructed.

The contribution of structural remodeling to long-term adult brain plasticity is unclear. Here, we investigate features of GABAergic interneuron dendrite dynamics and extract clues regarding its potential role in cortical function and circuit plasticity. We show that remodeling interneurons are contained within a “dynamic zone” corresponding to a superficial strip of layers 2/3, and remodeling dendrites respect the lower border of this zone. Remodeling occurs primarily at the periphery of dendritic fields with addition and retraction of new branch tips. We further show that dendrite remodeling is not intrinsic to a specific interneuron class. These data suggest that interneuron remodeling is not a feature predetermined by genetic lineage, but rather, it is imposed by cortical laminar circuitry. Our findings are consistent with dynamic GABAergic modulation of feedforward and recurrent connections in response to top-down feedback and suggest a structural component to functional plasticity of supragranular neocortical laminae.

Chronic in vivo imaging of fluorescent-labeled neurons in adult mice reveals extension and retraction of dendrites in GABAergic non-pyramidal interneurons of the cerebral cortex.

Despite decades of evidence for functional plasticity in the adult brain, the role of structural plasticity in its manifestation remains unclear. To examine the extent of neuronal remodeling that occurs in the brain on a day-to-day basis, we used a multiphoton-based microscopy system for chronic in vivo imaging and reconstruction of entire neurons in the superficial layers of the rodent cerebral cortex. Here we show the first unambiguous evidence (to our knowledge) of dendrite growth and remodeling in adult neurons. Over a period of months, neurons could be seen extending and retracting existing branches, and in rare cases adding new branch tips. Neurons exhibiting dynamic arbor rearrangements were GABA-positive non-pyramidal interneurons, while pyramidal cells remained stable. These results are consistent with the idea that dendritic structural remodeling is a substrate for adult plasticity and they suggest that circuit rearrangement in the adult cortex is restricted by cell type–specific rules., Chronic in vivo imaging of fluorescent-labeled neurons in adult mice reveals extension and retraction of dendrites in GABAergic non-pyramidal interneurons of the cerebral cortex.

Transcriptional activation is a key link between neuronal activity and long-term synaptic plasticity. Little is known about genes responding to this activation whose products directly effect functional and structural changes at the synapse. cpg15 is an activity-regulated gene encoding a membrane-bound ligand that regulates dendritic and axonal arbor growth and synaptic maturation. We report that cpg15 is an immediate-early gene induced by Ca(2+) influx through NMDA receptors and L-type voltage-sensitive calcium channels. Activity-dependent cpg15 expression requires convergent activation of the CaM kinase and MAP kinase pathways. Although activation of PKA is not required for activity-dependent expression, cpg15 is induced by cAMP in active neurons. CREB binds the cpg15 promoter in vivo and partially regulates its activity-dependent expression. cpg15 is an effector gene that is a target for signal transduction pathways that mediate synaptic plasticity and thus may take part in an activity-regulated transcriptional program that directs long-term changes in synaptic connections.

cpg15 is an activity-regulated gene that encodes a membrane-bound ligand that coordinately regulates growth of apposing dendritic and axonal arbors and the maturation of their synapses. These properties make it an attractive candidate for participating in plasticity of the mammalian visual system. Here we compare cpg15 expression during normal development of the rat visual system with that seen in response to dark rearing, monocular blockade of retinal action potentials, or monocular deprivation. Our results show that the onset of cpg15 expression in the visual cortex is coincident with eye opening, and it increases until the peak of the critical period at postnatal day 28 (P28). This early expression is independent of both retinal activity and visual experience. After P28, a component of cpg15 expression in the visual cortex, lateral geniculate nucleus (LGN), and superior colliculus (SC) develops a progressively stronger dependence on retinally driven action potentials. Dark rearing does not affect cpg15 mRNA expression in the LGN and SC at any age, but it does significantly affect its expression in the visual cortex from the peak of the critical period and into adulthood. In dark-reared rats, the peak level of cpg15 expression in the visual cortex at P28 is lower than in controls. Rather than showing the normal decline with maturation, these levels are maintained in dark-reared animals. We suggest that the prolonged plasticity in the visual cortex that is seen in dark-reared animals may result from failure to downregulate genes such as cpg15 that could promote structural remodeling and synaptic maturation.