Wiring specificity in the direction-selectivity circuit of the retina

ON and OFF starburst amacrine cells are controlled by distinct cholinergic pathways

Cholinergic signaling in the retina is mediated by acetylcholine (ACh) released from starburst amacrine cells (SACs), which are key neurons for motion detection. SACs comprise ON and OFF subtypes, which morphologically show mirror symmetry to each other. Although many physiological studies on SACs have targeted ON cells only, the synaptic computation of ON and OFF SACs is assumed to be similar. Recent studies demonstrated that gene expression patterns and receptor types differed between ON and OFF SACs, suggesting differences in their functions. Here, we compared cholinergic signaling pathways between ON and OFF SACs in the mouse retina using the patch clamp technique. The application of ACh increased GABAergic feedback, observed as postsynaptic currents to SACs, in both ON and OFF SACs; however, the mode of GABAergic feedback differed. Nicotinic receptors mediated GABAergic feedback in both ON and OFF SACs, while muscarinic receptors mediated GABAergic feedback in ON SACs only in adults. Neither tetrodotoxin, which blocked action potentials, nor LY354740, which blocked neurotransmitter release from SACs, eliminated ACh-induced GABAergic feedback in SACs. These results suggest that ACh-induced GABAergic feedback in ON and OFF SACs is regulated by different feedback mechanisms in adults and mediated by non-spiking amacrine cells other than SACs.

Dysregulated energy and protein homeostasis and the loss of GABAergic amacrine cells in aging retina

Aging is a major risk factor for the development or the worsening of retinal degenerative conditions. The intricate network of the neural retina determined that the retinal aging is a complicated process. The aim of this study is to delineate the transcriptomic changes of major retinal neurons during aging in C57BL/6 mice at single-cell level. We analyzed the transcriptional profiles of the photoreceptor, bipolar, amacrine, and Müller glial cells of 1.5-2 and 24-30 months old mice using single-cell RNA sequencing technique. We selectively confirmed the differences in gene expression using immunofluorescence staining and RNA in situ hybridization analysis. We found that each retinal cell type had unique changes upon aging. However, they all showed signs of dysregulated glucose and energy metabolism, and perturbed proteostasis. In particular, old Müller glia exhibited the most profound changes, including the upregulation of cell metabolism, stress-responses, antigen-presentation and immune responses and metal ion homeostasis. The dysregulated gliogenesis and differentiation was confirmed by the presence of Müller glia expressing rod-specific genes in the inner nuclear layer and the outer plexiform layer of the old retina. We further pinpointed the specific loss of GABAergic amacrine cells in old retina. Our study emphasized changes of amacrine and Müller glia during retinal aging, provided resources for further research on the molecular and cellular regulatory mechanisms underlying aging-associated retinal deterioration.

2D vs. 3D Evaluation of Osteocyte Lacunae - Methodological Approaches, Recommended Parameters, and Challenges: A Narrative Review by the European Calcified Tissue Society (ECTS)

PURPOSE OF REVIEW

Quantification of the morphology of osteocyte lacunae has become a powerful tool to investigate bone metabolism, pathologies and aging. This review will provide a brief overview of 2D and 3D imaging methods for the determination of lacunar shape, orientation, density, and volume. Deviations between 2D-based and 3D-based lacunar volume estimations are often not sufficiently addressed and may give rise to contradictory findings. Thus, the systematic error arising from 2D-based estimations of lacunar volume will be discussed, and an alternative calculation proposed. Further, standardized morphological parameters and best practices for sampling and segmentation are suggested.

RECENT FINDINGS

We quantified the errors in reported estimation methods of lacunar volume based on 2D cross-sections, which increase with variations in lacunar orientation and histological cutting plane. The estimations of lacunar volume based on common practice in 2D imaging methods resulted in an underestimation of lacunar volume of up to 85% compared to actual lacunar volume in an artificial dataset. For a representative estimation of lacunar size and morphology based on 2D images, at least 400 lacunae should be assessed per sample.

Imaging brain tissue architecture across millimeter to nanometer scales

Mapping the complex and dense arrangement of cells and their connectivity in brain tissue demands nanoscale spatial resolution imaging. Super-resolution optical microscopy excels at visualizing specific molecules and individual cells but fails to provide tissue context. Here we developed Comprehensive Analysis of Tissues across Scales (CATS), a technology to densely map brain tissue architecture from millimeter regional to nanometer synaptic scales in diverse chemically fixed brain preparations, including rodent and human. CATS uses fixation-compatible extracellular labeling and optical imaging, including stimulated emission depletion or expansion microscopy, to comprehensively delineate cellular structures. It enables three-dimensional reconstruction of single synapses and mapping of synaptic connectivity by identification and analysis of putative synaptic cleft regions. Applying CATS to the mouse hippocampal mossy fiber circuitry, we reconstructed and quantified the synaptic input and output structure of identified neurons. We furthermore demonstrate applicability to clinically derived human tissue samples, including formalin-fixed paraffin-embedded routine diagnostic specimens, for visualizing the cellular architecture of brain tissue in health and disease.

Individual thalamic inhibitory interneurons are functionally specialized toward distinct visual features

Inhibitory interneurons in the dorsolateral geniculate nucleus (dLGN) are situated at the first central synapse of the image-forming visual pathway, but little is known about their function. Given their anatomy, they are expected to be multiplexors, integrating many different retinal channels along their dendrites. Here, using targeted single-cell-initiated rabies tracing, we found that mouse dLGN interneurons exhibit a degree of retinal input specialization similar to thalamocortical neurons. Some are anatomically highly specialized, for example, toward motion-selective information. Two-photon calcium imaging performed in vivo revealed that interneurons are also functionally specialized. In mice lacking retinal horizontal direction selectivity, horizontal direction selectivity is reduced in interneurons, suggesting a causal link between input and functional specialization. Functional specialization is not only present at interneuron somata but also extends into their dendrites. Altogether, inhibitory interneurons globally display distinct visual features which reflect their retinal input specialization and are ideally suited to perform feature-selective inhibition.

Volume electron microscopy for genetically and molecularly defined neural circuits

The brain networks responsible for adaptive behavioral changes are based on the physical connections between neurons. Light and electron microscopy have long been used to study neural projections and the physical connections between neurons. Volume electron microscopy has recently expanded its scale of analysis due to methodological advances, resulting in complete wiring maps of neurites in a large volume of brain tissues and even entire nervous systems in a growing number of species. However, structural approaches frequently suffer from inherent limitations in which elements in images are identified solely by morphological criteria. Recently, an increasing number of tools and technologies have been developed to characterize cells and cellular components in the context of molecules and gene expression. These advancements include newly developed probes for visualization in electron microscopic images as well as correlative integration methods for the same elements across multiple microscopic modalities. Such approaches advance our understanding of interactions between specific neurons and circuits and may help to elucidate novel aspects of the basal ganglia network involving dopamine neurons. These advancements are expected to reveal mechanisms for processing adaptive changes in specific neural circuits that modulate brain functions.

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.

The retina's neurovascular unit: Müller glial sheaths and neuronal contacts

The neurovascular unit (NVU), comprising vascular, glial and neural elements, supports the energetic demands of neural computation, but this aspect of the retina's trilaminar vessel network is poorly understood. Only the innermost vessel layer - the superficial vascular plexus (SVP) - is ensheathed by astrocytes, like brain capillaries, whereas glial ensheathment in other layers derives from radial Müller glia. Using serial electron microscopy reconstructions from mouse and primate retina, we find that Müller processes cover capillaries in a tessellating pattern, mirroring the tiled astrocytic endfeet wrapping brain capillaries. However, gaps in the Müller sheath, found mainly in the intermediate vascular plexus (IVP), permit different neuron types to contact pericytes and the endothelial cells directly. Pericyte somata are a favored target, often at spine-like structures with a reduced or absent vascular basement lamina. Focal application of adenosine triphosphate (ATP) to the vitreal surface evoked Ca2+ signals in Müller sheaths in all three vascular layers. Pharmacological experiments confirmed that Müller sheaths express purinergic receptors that, when activated, trigger intracellular Ca2+ signals that are amplified by IP3-controlled intracellular Ca2+ stores. When rod photoreceptors die in a mouse model of retinitis pigmentosa (rd10), Müller sheaths dissociate from the deep vascular plexus (DVP) but are largely unchanged within the IVP or SVP. Thus, Müller glia interact with retinal vessels in a laminar, compartmentalized manner: glial sheathes are virtually complete in the SVP but fenestrated in the IVP, permitting direct neural-to-vascular contacts. In the DVP, the glial sheath is only modestly fenestrated and is vulnerable to photoreceptor degeneration.

Regional differences in the ultrastructure of mucosal macrophages in the rat large intestine

We previously clarified the histological characteristics of macrophages in the rat small intestine using serial block-face scanning electron microscopy (SBF-SEM). However, the regional differences in the characteristics of macrophages throughout the large intestine remain unknown. Here, we performed a pilot study to explore the regional differences in the ultrastructure of mucosal macrophages in the large intestine by using SBF-SEM analysis. SBF-SEM analysis conducted on the luminal side of the cecum and descending colon revealed macrophages as amorphous cells possessing abundant lysosomes and vacuoles. Macrophages in the cecum exhibited a higher abundance of lysosomes and a lower abundance of vacuoles than those in the descending colon. Macrophages with many intraepithelial cellular processes were observed beneath the intestinal superficial epithelium in the descending colon. Moreover, macrophages in contact with nerve fibers were more prevalent in the cecum than in the descending colon, and a subset of them surrounded a nerve bundle only in the cecum. In conclusion, the present pilot study suggested that the quantity of some organelles (lysosomes and vacuoles) in macrophages differed between the cecum and the descending colon and that there were some region-specific subsets of macrophages like nerve-associated macrophages in the cecum.

Photoemission electron microscopy for connectomics

Detailing the physical basis of neural circuits with large-volume serial electron microscopy (EM), 'connectomics', has emerged as an invaluable tool in the neuroscience armamentarium. However, imaging synaptic resolution connectomes is currently limited to either transmission electron microscopy (TEM) or scanning electron microscopy (SEM). Here, we describe a third way, using photoemission electron microscopy (PEEM) which illuminates ultra-thin brain slices collected on solid substrates with UV light and images the photoelectron emission pattern with a wide-field electron microscope. PEEM works with existing sample preparations for EM and routinely provides sufficient resolution and contrast to reveal myelinated axons, somata, dendrites, and sub-cellular organelles. Under optimized conditions, PEEM provides synaptic resolution; and simulation and experiments show that PEEM can be transformatively fast, at Gigahertz pixel rates. We conclude that PEEM imaging leverages attractive aspects of SEM and TEM, namely reliable sample collection on robust substrates combined with fast wide-field imaging, and could enable faster data acquisition for next-generation circuit mapping.

GAUSS-EM, guided accumulation of ultrathin serial sections with a static magnetic field for volume electron microscopy

Serial sectioning electron microscopy (EM) of millimeter-scale three-dimensional (3D) anatomical volumes requires the collection of thousands of ultrathin sections. Here, we report a high-throughput automated approach, GAUSS-EM (guided accumulation of ultrathin serial sections-EM), utilizing a static magnetic field to collect and densely pack thousands of sections onto individual silicon wafers. The method is capable of sectioning hundreds of microns of tissue per day at section thicknesses down to 35 nm. Relative to other automated volume EM approaches, GAUSS-EM democratizes the ability to collect large 3D EM volumes because it is simple and inexpensive to implement. We present two exemplar EM volumes of a zebrafish eye and mouse olfactory bulb collected with the method.

Neural Circuits Underlying Multifeature Extraction in the Retina

Classic ON-OFF direction-selective ganglion cells (DSGCs) that encode the four cardinal directions were recently shown to also be orientation-selective. To clarify the mechanisms underlying orientation selectivity, we employed a variety of electrophysiological, optogenetic, and gene knock-out strategies to test the relative contributions of glutamate, GABA, and acetylcholine (ACh) input that are known to drive DSGCs, in male and female mouse retinas. Extracellular spike recordings revealed that DSGCs respond preferentially to either vertical or horizontal bars, those that are perpendicular to their preferred-null motion axes. By contrast, the glutamate input to all four DSGC types measured using whole-cell patch-clamp techniques was found to be tuned along the vertical axis. Tuned glutamatergic excitation was heavily reliant on type 5A bipolar cells, which appear to be electrically coupled via connexin 36 containing gap junctions to the vertically oriented processes of wide-field amacrine cells. Vertically tuned inputs are transformed by the GABAergic/cholinergic "starburst" amacrine cells (SACs), which are critical components of the direction-selective circuit, into distinct patterns of inhibition and excitation. Feed-forward SAC inhibition appears to "veto" preferred orientation glutamate excitation in dorsal/ventral (but not nasal/temporal) coding DSGCs "flipping" their orientation tuning by 90° and accounts for the apparent mismatch between glutamate input tuning and the DSGC's spiking response. Together, these results reveal how two distinct synaptic motifs interact to generate complex feature selectivity, shedding light on the intricate circuitry that underlies visual processing in the retina.

Ancestral photoreceptor diversity as the basis of visual behaviour

Animal colour vision is based on comparing signals from different photoreceptors. It is generally assumed that processing different spectral types of photoreceptor mainly serves colour vision. Here I propose instead that photoreceptors are parallel feature channels that differentially support visual-motor programmes like motion vision behaviours, prey capture and predator evasion. Colour vision may have emerged as a secondary benefit of these circuits, which originally helped aquatic vertebrates to visually navigate and segment their underwater world. Specifically, I suggest that ancestral vertebrate vision was built around three main systems, including a high-resolution general purpose greyscale system based on ancestral red cones and rods to mediate visual body stabilization and navigation, a high-sensitivity specialized foreground system based on ancestral ultraviolet cones to mediate threat detection and prey capture, and a net-suppressive system based on ancestral green and blue cones for regulating red/rod and ultraviolet circuits. This ancestral strategy probably still underpins vision today, and different vertebrate lineages have since adapted their original photoreceptor circuits to suit their diverse visual ecologies.

Dendritic mGluR2 and perisomatic Kv3 signaling regulate dendritic computation of mouse starburst amacrine cells

Dendritic mechanisms driving input-output transformation in starburst amacrine cells (SACs) are not fully understood. Here, we combine two-photon subcellular voltage and calcium imaging and electrophysiological recording to determine the computational architecture of mouse SAC dendrites. We found that the perisomatic region integrates motion signals over the entire dendritic field, providing a low-pass-filtered global depolarization to dendrites. Dendrites integrate local synaptic inputs with this global signal in a direction-selective manner. Coincidental local synaptic inputs and the global motion signal in the outward motion direction generate local suprathreshold calcium transients. Moreover, metabotropic glutamate receptor 2 (mGluR2) signaling in SACs modulates the initiation of calcium transients in dendrites but not at the soma. In contrast, voltage-gated potassium channel 3 (Kv3) dampens fast voltage transients at the soma. Together, complementary mGluR2 and Kv3 signaling in different subcellular regions leads to dendritic compartmentalization and direction selectivity, highlighting the importance of these mechanisms in dendritic computation.

A unified model for cross-modal plasticity and skill acquisition

Historically, cross-modal plasticity following early blindness has been largely studied in the context of visual deprivation. However, more recently, there has been a shift in focus towards understanding cross-modal plasticity from the perspective of skill acquisition: the striking plasticity observed in early blind individuals reflects the extraordinary perceptual and cognitive challenges they solve. Here, inspired by two seminal papers on skill learning (the "cortical recycling" theory) and cross-modal plasticity (the "metamodal" hypothesis) respectively, we present a unified hypothesis of cortical specialization that describes how shared functional, algorithmic, and structural constraints might mediate both types of plasticity.

Synaptic promiscuity in brain development

Precise synaptic connectivity is a prerequisite for the function of neural circuits, yet individual neurons, taken out of their developmental context, readily form unspecific synapses. How does the genome encode brain wiring in light of this apparent contradiction? Synaptic specificity is the outcome of a long series of developmental processes and mechanisms before, during and after synapse formation. How much promiscuity is permissible or necessary at the moment of synaptic partner choice depends on the extent to which prior development restricts available partners or subsequent development corrects initially made synapses. Synaptic promiscuity at the moment of choice can thereby play important roles in the development of precise connectivity, but also facilitate developmental flexibility and robustness. In this review, we assess the experimental evidence for the prevalence and roles of promiscuous synapse formation during brain development. Many well-established experimental approaches are based on developmental genetic perturbation and an assessment of synaptic connectivity only in the adult; this can make it difficult to pinpoint when a given defect or mechanism occurred. In many cases, such studies reveal mechanisms that restrict partner availability already prior to synapse formation. Subsequently, at the moment of choice, factors including synaptic competency, interaction dynamics and molecular recognition further restrict synaptic partners. The discussion of the development of synaptic specificity through the lens of synaptic promiscuity suggests an algorithmic process based on neurons capable of promiscuous synapse formation that are continuously prevented from making the wrong choices, with no single mechanism or developmental time point sufficient to explain the outcome.

Connectivity Matrix Seriation via Relaxation

Volume electron microscopy together with computer-based image analysis are yielding neural circuit diagrams of ever larger regions of the brain. These datasets are usually represented in a cell-to-cell connectivity matrix and contain important information about prevalent circuit motifs allowing to directly test various theories on the computation in that brain structure. Of particular interest are the detection of cell assemblies and the quantification of feedback, which can profoundly change circuit properties. While the ordering of cells along the rows and columns doesn't change the connectivity, it can make special connectivity patterns recognizable. For example, ordering the cells along the flow of information, feedback and feedforward connections are segregated above and below the main matrix diagonal, respectively. Different algorithms are used to renumber matrices such as to minimize a given cost function, but either their performance becomes unsatisfying at a given size of the circuit or the CPU time needed to compute them scales in an unfavorable way with increasing number of neurons. Based on previous ideas, I describe an algorithm which is effective in matrix reordering with respect to both its performance as well as to its scaling in computing time. Rather than trying to reorder the matrix in discrete steps, the algorithm transiently relaxes the integer program by assigning a real-valued parameter to each cell describing its location on a continuous axis ('smooth-index') and finds the parameter set that minimizes the cost. I find that the smooth-index algorithm outperforms all algorithms I compared it to, including those based on topological sorting.

New twists in the evolution of retinal direction selectivity

In mammals, starburst amacrine cells are centrally involved in motion vision and a new study in PLOS Biology, by Yan and colleagues finds that zebrafish have them, too. They coexist with a second pair of starburst-like neurons, but neither appears to be strongly motion selective.

Hierarchies in Visual Pathway: Functions and Inspired Artificial Vision

The development of artificial intelligence has posed a challenge to machine vision based on conventional complementary metal-oxide semiconductor (CMOS) circuits owing to its high latency and inefficient power consumption originating from the data shuffling between memory and computation units. Gaining more insights into the function of every part of the visual pathway for visual perception can bring the capabilities of machine vision in terms of robustness and generality. Hardware acceleration of more energy-efficient and biorealistic artificial vision highly necessitates neuromorphic devices and circuits that are able to mimic the function of each part of the visual pathway. In this paper, we review the structure and function of the entire class of visual neurons from the retina to the primate visual cortex within reach (Chapter 2) are reviewed. Based on the extraction of biological principles, the recent hardware-implemented visual neurons located in different parts of the visual pathway are discussed in detail in Chapters 3 and 4. Furthermore, valuable applications of inspired artificial vision in different scenarios (Chapter 5) are provided. The functional description of the visual pathway and its inspired neuromorphic devices/circuits are expected to provide valuable insights for the design of next-generation artificial visual perception systems.

A presynaptic source drives differing levels of surround suppression in two mouse retinal ganglion cell types

In early sensory systems, cell-type diversity generally increases from the periphery into the brain, resulting in a greater heterogeneity of responses to the same stimuli. Surround suppression is a canonical visual computation that begins within the retina and is found at varying levels across retinal ganglion cell types. Our results show that heterogeneity in the level of surround suppression occurs subcellularly at bipolar cell synapses. Using single-cell electrophysiology and serial block-face scanning electron microscopy, we show that two retinal ganglion cell types exhibit very different levels of surround suppression even though they receive input from the same bipolar cell types. This divergence of the bipolar cell signal occurs through synapse-specific regulation by amacrine cells at the scale of tens of microns. These findings indicate that each synapse of a single bipolar cell can carry a unique visual signal, expanding the number of possible functional channels at the earliest stages of visual processing.

Molecular identification of wide-field amacrine cells in mouse retina that encode stimulus orientation

Visual information processing is sculpted by a diverse group of inhibitory interneurons in the retina called amacrine cells. Yet, for most of the >60 amacrine cell types, molecular identities and specialized functional attributes remain elusive. Here, we developed an intersectional genetic strategy to target a group of wide-field amacrine cells (WACs) in mouse retina that co-express the transcription factor Bhlhe22 and the Kappa Opioid Receptor (KOR; B/K WACs). B/K WACs feature straight, unbranched dendrites spanning over 0.5 mm (∼15° visual angle) and produce non-spiking responses to either light increments or decrements. Two-photon dendritic population imaging reveals Ca 2+ signals tuned to the physical orientations of B/K WAC dendrites, signifying a robust structure-function alignment. B/K WACs establish divergent connections with multiple retinal neurons, including unexpected connections with non-orientation-tuned ganglion cells and bipolar cells. Our work sets the stage for future comprehensive investigations of the most enigmatic group of retinal neurons: WACs.

Heterogeneous presynaptic receptive fields contribute to directional tuning in starburst amacrine cells

The processing of visual information by retinal starburst amacrine cells (SACs) involves transforming excitatory input from bipolar cells (BCs) into directional calcium output. While previous studies have suggested that an asymmetry in the kinetic properties of BCs along the soma-dendritic axes of the postsynaptic cell could enhance directional tuning at the level of individual branches, it remains unclear whether biologically relevant presynaptic kinetics contribute to direction selectivity (DS) when visual stimulation engages the entire dendritic tree. To address this question, we built multicompartmental models of the bipolar-SAC circuit and trained them to boost directional tuning. We report that despite significant dendritic crosstalk and dissimilar directional preferences along the dendrites that occur during whole-cell stimulation, the rules that guide BC kinetics leading to optimal DS are similar to the single-dendrite condition. To correlate model predictions to empirical findings, we utilized two-photon glutamate imaging to study the dynamics of bipolar release onto ON- and OFF-starburst dendrites in the murine retina. We reveal diverse presynaptic dynamics in response to motion in both BC populations; algorithms trained on the experimental data suggested that the differences in the temporal release kinetics are likely to correspond to heterogeneous receptive field properties among the different BC types, including the spatial extent of the center and surround components. In addition, we demonstrate that circuit architecture composed of presynaptic units with experimentally recorded dynamics could enhance directional drive but not to levels that replicate empirical findings, suggesting other DS mechanisms are required to explain SAC function. Our study provides new insights into the complex mechanisms underlying DS in retinal processing and highlights the potential contribution of presynaptic kinetics to the computation of visual information by SACs.

msemalign: a pipeline for serial section multibeam scanning electron microscopy volume alignment

Serial section multibeam scanning electron microscopy (ssmSEM) is currently among the fastest technologies available for acquiring 3D anatomical data spanning relatively large neural tissue volumes, on the order of 1 mm3 or larger, at a resolution sufficient to resolve the fine detail of neuronal morphologies and synapses. These petabyte-scale volumes can be analyzed to create connectomes, datasets that contain detailed anatomical information including synaptic connectivity, neuronal morphologies and distributions of cellular organelles. The mSEM acquisition process creates hundreds of millions of individual image tiles for a single cubic-millimeter-sized dataset and these tiles must be aligned to create 3D volumes. Here we introduce msemalign, an alignment pipeline that strives for scalability and design simplicity. The pipeline can align petabyte-scale datasets such that they contain smooth transitions as the dataset is navigated in all directions, but critically that does so in a fashion that minimizes the overall magnitude of section distortions relative to the originally acquired micrographs.

Genetically encoded barcodes for correlative volume electron microscopy

While genetically encoded reporters are common for fluorescence microscopy, equivalent multiplexable gene reporters for electron microscopy (EM) are still scarce. Here, by installing a variable number of fixation-stable metal-interacting moieties in the lumen of encapsulin nanocompartments of different sizes, we developed a suite of spherically symmetric and concentric barcodes (EMcapsulins) that are readable by standard EM techniques. Six classes of EMcapsulins could be automatically segmented and differentiated. The coding capacity was further increased by arranging several EMcapsulins into distinct patterns via a set of rigid spacers of variable length. Fluorescent EMcapsulins were expressed to monitor subcellular structures in light and EM. Neuronal expression in Drosophila and mouse brains enabled the automatic identification of genetically defined cells in EM. EMcapsulins are compatible with transmission EM, scanning EM and focused ion beam scanning EM. The expandable palette of genetically controlled EM-readable barcodes can augment anatomical EM images with multiplexed gene expression maps.

Emerging computational motifs: Lessons from the retina

The retinal neuronal circuit is the first stage of visual processing in the central nervous system. The efforts of scientists over the last few decades indicate that the retina is not merely an array of photosensitive cells, but also a processor that performs various computations. Within a thickness of only ∼200 µm, the retina consists of diverse forms of neuronal circuits, each of which encodes different visual features. Since the discovery of direction-selective cells by Horace Barlow and Richard Hill, the mechanisms that generate direction selectivity in the retina have remained a fascinating research topic. This review provides an overview of recent advances in our understanding of direction-selectivity circuits. Beyond the conventional wisdom of direction selectivity, emerging findings indicate that the retina utilizes complicated and sophisticated mechanisms in which excitatory and inhibitory pathways are involved in the efficient encoding of motion information. As will become evident, the discovery of computational motifs in the retina facilitates an understanding of how sensory systems establish feature selectivity.

An ON-type direction-selective ganglion cell in primate retina

To maintain a stable and clear image of the world, our eyes reflexively follow the direction in which a visual scene is moving. Such gaze-stabilization mechanisms reduce image blur as we move in the environment. In non-primate mammals, this behaviour is initiated by retinal output neurons called ON-type direction-selective ganglion cells (ON-DSGCs), which detect the direction of image motion and transmit signals to brainstem nuclei that drive compensatory eye movements1. However, ON-DSGCs have not yet been identified in the retina of primates, raising the possibility that this reflex is mediated by cortical visual areas. Here we mined single-cell RNA transcriptomic data from primate retina to identify a candidate ON-DSGC. We then combined two-photon calcium imaging, molecular identification and morphological analysis to reveal a population of ON-DSGCs in the macaque retina. The morphology, molecular signature and GABA (γ-aminobutyric acid)-dependent mechanisms that underlie direction selectivity in primate ON-DSGCs are highly conserved with those in other mammals. We further identify a candidate ON-DSGC in human retina. The presence of ON-DSGCs in primates highlights the need to examine the contribution of subcortical retinal mechanisms to normal and aberrant gaze stabilization in the developing and mature visual system.

Rejection of inappropriate synaptic partners in mouse retina mediated by transcellular FLRT2-UNC5 signaling

During nervous system development, neurons choose synaptic partners with remarkable specificity; however, the cell-cell recognition mechanisms governing rejection of inappropriate partners remain enigmatic. Here, we show that mouse retinal neurons avoid inappropriate partners by using the FLRT2-uncoordinated-5 (UNC5) receptor-ligand system. Within the inner plexiform layer (IPL), FLRT2 is expressed by direction-selective (DS) circuit neurons, whereas UNC5C/D are expressed by non-DS neurons projecting to adjacent IPL sublayers. In vivo gain- and loss-of-function experiments demonstrate that FLRT2-UNC5 binding eliminates growing DS dendrites that have strayed from the DS circuit IPL sublayers. Abrogation of FLRT2-UNC5 binding allows mistargeted arbors to persist, elaborate, and acquire synapses from inappropriate partners. Conversely, UNC5C misexpression within DS circuit sublayers inhibits dendrite growth and drives arbors into adjacent sublayers. Mechanistically, UNC5s promote dendrite elimination by interfering with FLRT2-mediated adhesion. Based on their broad expression, FLRT-UNC5 recognition is poised to exert widespread effects upon synaptic partner choices across the nervous system.

Direct comparison reveals algorithmic similarities in fly and mouse visual motion detection

Evolution has equipped vertebrates and invertebrates with neural circuits that selectively encode visual motion. While similarities in the computations performed by these circuits in mouse and fruit fly have been noted, direct experimental comparisons have been lacking. Because molecular mechanisms and neuronal morphology in the two species are distinct, we directly compared motion encoding in these two species at the algorithmic level, using matched stimuli and focusing on a pair of analogous neurons, the mouse ON starburst amacrine cell (ON SAC) and Drosophila T4 neurons. We find that the cells share similar spatiotemporal receptive field structures, sensitivity to spatiotemporal correlations, and tuning to sinusoidal drifting gratings, but differ in their responses to apparent motion stimuli. Both neuron types showed a response to summed sinusoids that deviates from models for motion processing in these cells, underscoring the similarities in their processing and identifying response features that remain to be explained.

Heterogeneous presynaptic receptive fields contribute to directional tuning in starburst amacrine cells

The processing of visual information by retinal starburst amacrine cells (SACs) involves transforming excitatory input from bipolar cells (BCs) into directional calcium output. While previous studies have suggested that an asymmetry in the kinetic properties of bipolar cells along the soma-dendritic axes of the postsynaptic cell could enhance directional tuning at the level of individual branches, it remains unclear whether biologically relevant presynaptic kinetics contribute to direction selectivity when visual stimulation engages the entire dendritic tree. To address this question, we built multicompartmental models of the bipolar-SAC circuit and trained them to boost directional tuning. We report that despite significant dendritic crosstalk and dissimilar directional preferences along the dendrites that occur during whole-cell stimulation, the rules that guide BC kinetics leading to optimal directional selectivity are similar to the single-dendrite condition. To correlate model predictions to empirical findings, we utilized two-photon glutamate imaging to study the dynamics of bipolar release onto ON- and OFF-starburst dendrites in the murine retina. We reveal diverse presynaptic dynamics in response to motion in both BC populations; algorithms trained on the experimental data suggested that the differences in the temporal release kinetics are likely to correspond to heterogeneous receptive field (RF) properties among the different BC types, including the spatial extent of the center and surround components. In addition, we demonstrate that circuit architecture composed of presynaptic units with experimentally recorded dynamics could enhance directional drive but not to levels that replicate empirical findings, suggesting other DS mechanisms are required to explain SAC function. Our study provides new insights into the complex mechanisms underlying direction selectivity in retinal processing and highlights the potential contribution of presynaptic kinetics to the computation of visual information by starburst amacrine cells.

Segmentation in large-scale cellular electron microscopy with deep learning: A literature survey

Electron microscopy (EM) enables high-resolution imaging of tissues and cells based on 2D and 3D imaging techniques. Due to the laborious and time-consuming nature of manual segmentation of large-scale EM datasets, automated segmentation approaches are crucial. This review focuses on the progress of deep learning-based segmentation techniques in large-scale cellular EM throughout the last six years, during which significant progress has been made in both semantic and instance segmentation. A detailed account is given for the key datasets that contributed to the proliferation of deep learning in 2D and 3D EM segmentation. The review covers supervised, unsupervised, and self-supervised learning methods and examines how these algorithms were adapted to the task of segmenting cellular and sub-cellular structures in EM images. The special challenges posed by such images, like heterogeneity and spatial complexity, and the network architectures that overcame some of them are described. Moreover, an overview of the evaluation measures used to benchmark EM datasets in various segmentation tasks is provided. Finally, an outlook of current trends and future prospects of EM segmentation is given, especially with large-scale models and unlabeled images to learn generic features across EM datasets.

Asymmetric connections with starburst amacrine cells underlie the upward motion selectivity of J-type retinal ganglion cells

Motion is an important aspect of visual information. The directions of visual motion are encoded in the retina by direction-selective ganglion cells (DSGCs). ON-OFF DSGCs and ON DSGCs co-stratify with starburst amacrine cells (SACs) in the inner plexiform layer and depend on SACs for their direction selectivity. J-type retinal ganglion cells (J-RGCs), a type of OFF DSGCs in the mouse retina, on the other hand, do not co-stratify with SACs, and how direction selectivity in J-RGCs emerges has not been understood. Here, we report that both the excitatory and inhibitory synaptic inputs to J-RGCs are direction-selective (DS), with the inhibitory inputs playing a more important role for direction selectivity. The DS inhibitory inputs come from SACs, and the functional connections between J-RGCs and SACs are spatially asymmetric. Thus, J-RGCs and SACs form functionally important synaptic contacts even though their dendritic arbors show little overlap. These findings underscore the need to look beyond the neurons' stratification patterns in retinal circuit studies. Our results also highlight the critical role of SACs for retinal direction selectivity.

Application of fluorescence micro-optical sectioning tomography in the cerebrovasculature and applicable vascular labeling methods

Fluorescence micro-optical sectioning tomography (fMOST) is a three-dimensional (3d) imaging method at the mesoscopic level. The whole-brain of mice can be imaged at a high resolution of 0.32 × 0.32 × 1.00 μm3. It is useful for revealing the fine morphology of intact organ tissue, even for positioning the single vessel connected with a complicated vascular network across different brain regions in the whole mouse brain. Featuring its 3d visualization of whole-brain cross-scale connections, fMOST has a vast potential to decipher brain function and diseases. This article begins with the background of fMOST technology including a widespread 3D imaging methods comparison and the basic technical principal illustration, followed by the application of fMOST in cerebrovascular research and relevant vascular labeling techniques applicable to different scenarios.

Presynaptic depolarization differentially regulates dual neurotransmitter release from starburst amacrine cells in the mouse retina

The retina is comprised of diverse neural networks, signaling from photoreceptors to ganglion cells to encode images. The synaptic connections between these retinal neurons are crucial points for information transfer; however, the input-output relations of many synapses are understudied. Starburst amacrine cells in the retina are known to contribute to retinal motion detection circuits, providing a unique window for understanding neural computations. We examined the dual transmitter release of GABA and acetylcholine from starburst amacrine cells by optogenetic activation of these cells, and conducted patch clamp recordings from postsynaptic ganglion cells to record excitatory and inhibitory postsynaptic currents (EPSCs and IPSCs). As starburst amacrine cells exhibit distinct kinetics in response to objects moving in a preferred or null direction, we mimicked their depolarization kinetics using optogenetic stimuli by varying slopes of the rising phase. The amplitudes of EPSCs and IPSCs in postsynaptic ganglion cells were reduced as the stimulus rising speed was prolonged. However, the sensitivity of postsynaptic currents to the stimulus slope differed. EPSC amplitudes were consistently reduced as the steepness of the rising phase fell. By contrast, IPSCs were less sensitive to the slope of the stimulus rise phase and maintained their amplitudes until the slope became shallow. These results indicate that distinct synaptic release mechanisms contribute to acetylcholine and GABA release from starburst amacrine cells, which could contribute to the ganglion cells' direction selectivity.

A circuit suppressing retinal drive to the optokinetic system during fast image motion

Optokinetic nystagmus (OKN) assists stabilization of the retinal image during head rotation. OKN is driven by ON direction selective retinal ganglion cells (ON DSGCs), which encode both the direction and speed of global retinal slip. The synaptic circuits responsible for the direction selectivity of ON DSGCs are well understood, but those sculpting their slow-speed preference remain enigmatic. Here, we probe this mechanism in mouse retina through patch clamp recordings, functional imaging, genetic manipulation, and electron microscopic reconstructions. We confirm earlier evidence that feedforward glycinergic inhibition is the main suppressor of ON DSGC responses to fast motion, and reveal the source for this inhibition-the VGluT3 amacrine cell, a dual neurotransmitter, excitatory/inhibitory interneuron. Together, our results identify a role for VGluT3 cells in limiting the speed range of OKN. More broadly, they suggest VGluT3 cells shape the response of many retinal cell types to fast motion, suppressing it in some while enhancing it in others.

Correlative light and volume electron microscopy to study brain development

Recent advances in volume electron microscopy (EM) have been driving our thorough understanding of the brain architecture. Volume EM becomes increasingly powerful when cells and their subcellular structures that are imaged in light microscopy are correlated to those in ultramicrographs obtained with EM. This correlative approach, called correlative light and volume electron microscopy (vCLEM), is used to link three-dimensional ultrastructural information with physiological data such as intracellular Ca2+ dynamics. Genetic tools to express fluorescent proteins and/or an engineered form of a soybean ascorbate peroxidase allow us to perform vCLEM using natural landmarks including blood vessels without immunohistochemical staining. This immunostaining-free vCLEM has been successfully employed in two-photon Ca2+ imaging in vivo as well as in studying complex synaptic connections in thalamic neurons that receive a variety of specialized inputs from the cerebral cortex. In this mini-review, we overview how volume EM and vCLEM have contributed to studying the developmental processes of the brain. We also discuss potential applications of genetic manipulation of target cells using clustered regularly interspaced short palindromic repeats-associated protein 9 and subsequent volume EM to the analysis of protein localization as well as to loss-of-function studies of genes regulating brain development. We give examples for the combinatorial usage of genetic tools with vCLEM that will further enhance our understanding of regulatory mechanisms underlying brain development.

TARPγ2 Is Required for Normal AMPA Receptor Expression and Function in Direction-Selective Circuits of the Mammalian Retina

AMPA receptors (AMPARs) are the major mediators of fast excitatory neurotransmission in the retina as in other parts of the brain. In most neurons, the synaptic targeting, pharmacology, and function of AMPARs are influenced by auxiliary subunits including the transmembrane AMPA receptor regulatory proteins (TARPs). However, it is unclear which TARP subunits are present at retinal synapses and how they influence receptor localization and function. Here, we show that TARPɣ2 (stargazin) is associated with AMPARs in the synaptic layers of the mouse, rabbit, macaque, and human retina. In most species, TARPɣ2 expression was high where starburst amacrine cells (SACs) ramify and transcriptomic analyses suggest correspondingly high gene expression in mouse and human SACs. Synaptic expression of GluA2, GluA3, and GluA4 was significantly reduced in a mouse mutant lacking TARPɣ2 expression (stargazer mouse; stg), whereas GluA1 levels were unaffected. AMPAR-mediated light-evoked EPSCs in ON-SACs from stg mice were ∼30% smaller compared with heterozygous littermates. There was also loss of a transient ON pathway-driven GABAergic input to ON-SACs in stg mutants. Direction-selective ganglion cells in the stg mouse showed normal directional tuning, but their surround inhibition and thus spatial tuning was reduced. Our results indicate that TARPɣ2 is required for normal synaptic expression of GluA2, GluA3, and GluA4 in the inner retina. The presence of residual AMPAR expression in the stargazer mutant suggests that other TARP subunits may compensate in the absence of TARPɣ2.

Cell-type specification in the retina: Recent discoveries from transcriptomic approaches

Understanding the formation of the complex nervous system hinges on decoding the mechanism that specifies a vast array of neuronal types, each endowed with a unique morphology, physiology, and connectivity. As a pivotal step towards addressing this problem, seminal work has been devoted to characterizing distinct neuronal types. In recent years, high-throughput, single-cell transcriptomic methods have enabled a rapid inventory of cell types in various regions of the nervous system, with the retina exhibiting complete molecular characterization across many vertebrate species. This invaluable resource has furnished a fresh perspective for investigating the molecular principles of cell-type specification, thereby advancing our understanding of retinal development. Accordingly, this review focuses on the most recent transcriptomic characterizations of retinal cells, with a particular focus on amacrine cells and retinal ganglion cells. These investigations have unearthed new insights into their cell-type specification.

Dense 4D nanoscale reconstruction of living brain tissue

Three-dimensional (3D) reconstruction of living brain tissue down to an individual synapse level would create opportunities for decoding the dynamics and structure-function relationships of the brain's complex and dense information processing network; however, this has been hindered by insufficient 3D resolution, inadequate signal-to-noise ratio and prohibitive light burden in optical imaging, whereas electron microscopy is inherently static. Here we solved these challenges by developing an integrated optical/machine-learning technology, LIONESS (live information-optimized nanoscopy enabling saturated segmentation). This leverages optical modifications to stimulated emission depletion microscopy in comprehensively, extracellularly labeled tissue and previous information on sample structure via machine learning to simultaneously achieve isotropic super-resolution, high signal-to-noise ratio and compatibility with living tissue. This allows dense deep-learning-based instance segmentation and 3D reconstruction at a synapse level, incorporating molecular, activity and morphodynamic information. LIONESS opens up avenues for studying the dynamic functional (nano-)architecture of living brain tissue.

The evolution of Big Data in neuroscience and neurology

Neurological diseases are on the rise worldwide, leading to increased healthcare costs and diminished quality of life in patients. In recent years, Big Data has started to transform the fields of Neuroscience and Neurology. Scientists and clinicians are collaborating in global alliances, combining diverse datasets on a massive scale, and solving complex computational problems that demand the utilization of increasingly powerful computational resources. This Big Data revolution is opening new avenues for developing innovative treatments for neurological diseases. Our paper surveys Big Data's impact on neurological patient care, as exemplified through work done in a comprehensive selection of areas, including Connectomics, Alzheimer's Disease, Stroke, Depression, Parkinson's Disease, Pain, and Addiction (e.g., Opioid Use Disorder). We present an overview of research and the methodologies utilizing Big Data in each area, as well as their current limitations and technical challenges. Despite the potential benefits, the full potential of Big Data in these fields currently remains unrealized. We close with recommendations for future research aimed at optimizing the use of Big Data in Neuroscience and Neurology for improved patient outcomes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40537-023-00751-2.

Volume EM: a quiet revolution takes shape

Volume Electron Microscopy is a group of techniques that reveal the 3D ultrastructure of cells and tissues through volumes greater than 1 cubic micron. A burgeoning grass roots community effort is fast building the profile, and revealing the impact, of vEM technology in the life sciences and clinical research.

Starburst amacrine cells form gap junctions in the early postnatal stage of the mouse retina

Although gap junctional coupling in the developing retina is important for the maturation of neuronal networks, its role in the development of individual neurons remains unclear. Therefore, we herein investigated whether gap junctional coupling by starburst amacrine cells (SACs), a key neuron for the formation of direction selectivity, occurs during the developmental stage in the mouse retina. Neurobiotin-injected SACs coupled with many neighboring cells before eye-opening. The majority of tracer-coupled cells were retinal ganglion cells, and tracer coupling was not detected between SACs. The number of tracer-coupled cells significantly decreased after eye-opening and mostly disappeared by postnatal day 28 (P28). Membrane capacitance (Cm), an indicator of the formation of electrical coupling with gap junctions, was larger in SACs before than after eye-opening. The application of meclofenamic acid, a gap junction blocker, reduced the Cm of SACs. Gap junctional coupling by SACs was regulated by dopamine D1 receptors before eye-opening. In contrast, the reduction in gap junctional coupling after eye-opening was not affected by visual experience. At the mRNA level, 4 subtypes of connexins (23, 36, 43, and 45) were detected in SACs before eye-opening. Connexin 43 expression levels significantly decreased after eye-opening. These results indicate that gap junctional coupling by SACs occurs during the developmental period and suggest that the elimination of gap junctions proceeds with the innate system.

Two mechanisms for direction selectivity in a model of the primate starburst amacrine cell

In a recent study, visual signals were recorded for the first time in starburst amacrine cells of the macaque retina, and, as for mouse and rabbit, a directional bias observed in calcium signals was recorded from near the dendritic tips. Stimulus motion from the soma toward the tip generated a larger calcium signal than motion from the tip toward the soma. Two mechanisms affecting the spatiotemporal summation of excitatory postsynaptic currents have been proposed to contribute to directional signaling at the dendritic tips of starbursts: (1) a "morphological" mechanism in which electrotonic propagation of excitatory synaptic currents along a dendrite sums bipolar cell inputs at the dendritic tip preferentially for stimulus motion in the centrifugal direction; (2) a "space-time" mechanism that relies on differences in the time-courses of proximal and distal bipolar cell inputs to favor centrifugal stimulus motion. To explore the contributions of these two mechanisms in the primate, we developed a realistic computational model based on connectomic reconstruction of a macaque starburst cell and the distribution of its synaptic inputs from sustained and transient bipolar cell types. Our model suggests that both mechanisms can initiate direction selectivity in starburst dendrites, but their contributions differ depending on the spatiotemporal properties of the stimulus. Specifically, the morphological mechanism dominates when small visual objects are moving at high velocities, and the space-time mechanism contributes most for large visual objects moving at low velocities.

Connecting Connectomes to Physiology

With the advent of volumetric EM techniques, large connectomic datasets are being created, providing neuroscience researchers with knowledge about the full connectivity of neural circuits under study. This allows for numerical simulation of detailed, biophysical models of each neuron participating in the circuit. However, these models typically include a large number of parameters, and insight into which of these are essential for circuit function is not readily obtained. Here, we review two mathematical strategies for gaining insight into connectomics data: linear dynamical systems analysis and matrix reordering techniques. Such analytical treatment can allow us to make predictions about time constants of information processing and functional subunits in large networks.SIGNIFICANCE STATEMENT This viewpoint provides a concise overview on how to extract important insights from Connectomics data by mathematical methods. First, it explains how new dynamics and new time constants can evolve, simply through connectivity between neurons. These new time-constants can be far longer than the intrinsic membrane time-constants of the individual neurons. Second, it summarizes how structural motifs in the circuit can be discovered. Specifically, there are tools to decide whether or not a circuit is strictly feed-forward or whether feed-back connections exist. Only by reordering connectivity matrices can such motifs be made visible.

Signaling - transcription interactions in mouse retinal ganglion cells early axon pathfinding -a literature review

Sending an axon out of the eye and into the target brain nuclei is the defining feature of retinal ganglion cells (RGCs). The literature on RGC axon pathfinding is vast, but it focuses mostly on decision making events such as midline crossing at the optic chiasm or retinotopic mapping at the target nuclei. In comparison, the exit of RGC axons out of the eye is much less explored. The first checkpoint on the RGC axons' path is the optic cup - optic stalk junction (OC-OS). OC-OS development and the exit of the RGC pioneer axons out of the eye are coordinated spatially and temporally. By the time the optic nerve head domain is specified, the optic fissure margins are in contact and the fusion process is ongoing, the first RGCs are born in its proximity and send pioneer axons in the optic stalk. RGC differentiation continues in centrifugal waves. Later born RGC axons fasciculate with the more mature axons. Growth cones at the end of the axons respond to guidance cues to adopt a centripetal direction, maintain nerve fiber layer restriction and to leave the optic cup. Although there is extensive information on OC-OS development, we still have important unanswered questions regarding its contribution to the exit of the RGC axons out of the eye. We are still to distinguish the morphogens of the OC-OS from the axon guidance molecules which are expressed in the same place at the same time. The early RGC transcription programs responsible for axon emergence and pathfinding are also unknown. This review summarizes the molecular mechanisms for early RGC axon guidance by contextualizing mouse knock-out studies on OC-OS development with the recent transcriptomic studies on developing RGCs in an attempt to contribute to the understanding of human optic nerve developmental anomalies. The published data summarized here suggests that the developing optic nerve head provides a physical channel (the closing optic fissure) as well as molecular guidance cues for the pioneer RGC axons to exit the eye.

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.

Neural dynamics and architecture of the heading direction circuit in zebrafish

Animals generate neural representations of their heading direction. Notably, in insects, heading direction is topographically represented by the activity of neurons in the central complex. Although head direction cells have been found in vertebrates, the connectivity that endows them with their properties is unknown. Using volumetric lightsheet imaging, we find a topographical representation of heading direction in a neuronal network in the zebrafish anterior hindbrain, where a sinusoidal bump of activity rotates following directional swims of the fish and is otherwise stable over many seconds. Electron microscopy reconstructions show that, although the cell bodies are located in a dorsal region, these neurons arborize in the interpeduncular nucleus, where reciprocal inhibitory connectivity stabilizes the ring attractor network that encodes heading. These neurons resemble those found in the fly central complex, showing that similar circuit architecture principles may underlie the representation of heading direction across the animal kingdom and paving the way to an unprecedented mechanistic understanding of these networks in vertebrates.

New insights into retinal circuits through EM connectomics: what we have learnt and what remains to be learned

The retinal neural circuit is intricately wired for efficient processing of visual signals. This is well-supported by the specialized connections between retinal neurons at both the functional and ultrastructural levels. Through 3D electron microscopic (EM) reconstructions of retinal neurons and circuits we have learnt much about the specificities of connections within the retinal layers including new insights into how retinal neurons establish connections and perform sophisticated visual computations. This mini-review will summarize the retinal circuitry and provide details about the novel insights EM connectomics has brought into our understanding of the retinal circuitry. We will also discuss unresolved questions about the retinal circuitry that can be addressed by EM connectomics in the future.

Special nuclear layer contacts between starburst amacrine cells in the mouse retina

Starburst amacrine cells are a prominent neuron type in the mammalian retina that has been well-studied for its role in direction-selective information processing. One specific property of these cells is that their dendrites tightly stratify at specific depths within the inner plexiform layer (IPL), which, together with their unique expression of choline acetyltransferase (ChAT), has made them the most common depth marker for studying other retinal neurons in the IPL. This stratifying property makes it unexpected that they could routinely have dendrites reaching into the nuclear layer or that they could have somatic contact specializations, which is exactly what we have found in this study. Specifically, an electron microscopic image volume of sufficient size from a mouse retina provided us with the opportunity to anatomically observe both microscopic details and collective patterns, and our detailed cell reconstructions revealed interesting cell-cell contacts between starburst amacrine neurons. The contact characteristics differ between the respective On and Off starburst amacrine subpopulations, but both occur within the soma layers, as opposed to their regular contact laminae within the inner plexiform layer.

Asymmetric retinal direction tuning predicts optokinetic eye movements across stimulus conditions

Across species, the optokinetic reflex (OKR) stabilizes vision during self-motion. OKR occurs when ON direction-selective retinal ganglion cells (oDSGCs) detect slow, global image motion on the retina. How oDSGC activity is integrated centrally to generate behavior remains unknown. Here, we discover mechanisms that contribute to motion encoding in vertically tuned oDSGCs and leverage these findings to empirically define signal transformation between retinal output and vertical OKR behavior. We demonstrate that motion encoding in vertically tuned oDSGCs is contrast-sensitive and asymmetric for oDSGC types that prefer opposite directions. These phenomena arise from the interplay between spike threshold nonlinearities and differences in synaptic input weights, including shifts in the balance of excitation and inhibition. In behaving mice, these neurophysiological observations, along with a central subtraction of oDSGC outputs, accurately predict the trajectories of vertical OKR across stimulus conditions. Thus, asymmetric tuning across competing sensory channels can critically shape behavior.

SynapseCLR: Uncovering features of synapses in primary visual cortex through contrastive representation learning

3D electron microscopy (EM) connectomics image volumes are surpassing 1 mm³, providing information-dense, multi-scale visualizations of brain circuitry and necessitating scalable analysis techniques. We present SynapseCLR, a self-supervised contrastive learning method for 3D EM data, and use it to extract features of synapses from mouse visual cortex. SynapseCLR feature representations separate synapses by appearance and functionally important structural annotations. We demonstrate SynapseCLR's utility for valuable downstream tasks, including one-shot identification of defective synapse segmentations, dataset-wide similarity-based querying, and accurate imputation of annotations for unlabeled synapses, using manual annotation of only 0.2% of the dataset's synapses. In particular, excitatory versus inhibitory neuronal types can be assigned with >99.8% accuracy to individual synapses and highly truncated neurites, enabling neurite-enhanced connectomics analysis. Finally, we present a data-driven, unsupervised study of synaptic structural variation on the representation manifold, revealing its intrinsic axes of variation and showing that representations contain inhibitory subtype information.