Biology subjects

Lichtman, J. W.

Publications and source records attributed to Lichtman, J. W..

35 records · Page 2Linked to original sources

bioRxiv2023

mEMbrain: an interactive deep learning MATLAB tool for connectomic segmentation on commodity desktops

Connectomics is fundamental in propelling our understanding of the nervous systems organization, unearthing cells and wiring diagrams reconstructed from volume electron microscopy (EM) datasets. Such reconstructions, on the one hand, have benefited from ever more precise automatic segmentation methods, which leverage sophisticated deep learning architectures and advanced machine learning algorithms. On the other hand, the field of neuroscience at large, and of image processing in particular, has manifested a need for user-friendly and open source tools which enable the community to carry out advanced analyses. In line with this second vein, here we propose mEMbrain, an interactive MATLAB-based software which wraps algorithms and functions that enable labeling and segmentation of electron microscopy datasets in a user-friendly user interface compatible with Linux and Windows. Through its integration as an API to the volume annotation and segmentation tool VAST, mEMbrain encompasses functions for ground truth generation, image preprocessing, training of deep neural networks, and on-the-fly predictions for proofreading and evaluation. The final goals of our tool are to expedite manual labeling efforts and to harness MATLAB users with an array of semi-automatic approaches for instance segmentation. We tested our tool on a variety of datasets that span different species at various scales, regions of the nervous system and developmental stages. To further expedite research in connectomics, we provide an EM resource of ground truth annotation from 4 different animals and 5 datasets, amounting to around 180 hours of expert annotations, yielding more than 1.2 GB of annotated EM images. In addition, we provide a set of 4 pre-trained networks for said datasets. All tools are available from https://lichtman.rc.fas.harvard.edu/mEMbrain/. With our software, our hope is to provide a solution for lab-based neural reconstructions which does not require coding by the user, thus paving the way to affordable connectomics.

neuroscience↗

bioRxiv2022

Vimo: Visual Analysis of Neuronal Connectivity Motifs

Recent advances in high-resolution connectomics provide researchers with access to accurate petascale reconstructions of neuronal circuits and brain networks for the first time. Neuroscientists are analyzing these networks to better understand information processing in the brain. In particular, scientists are interested in identifying specific small network motifs, i.e., repeating subgraphs of the larger brain network that are believed to be neuronal building blocks. Although such motifs are typically small (e.g., 2 - 6 neurons), the vast data sizes and intricate data complexity present significant challenges to the search and analysis process. To analyze these motifs, it is crucial to review instances of a motif in the brain network and then map the graph structure to detailed 3D reconstructions of the involved neurons and synapses. We present Vimo, an interactive visual approach to analyze neuronal motifs and motif chains in large brain networks. Experts can sketch network motifs intuitively in a visual interface and specify structural properties of the involved neurons and synapses to query large connectomics datasets. Motif instances (MIs) can be explored in high-resolution 3D renderings. To simplify the analysis of MIs, we designed a continuous focus&context metaphor inspired by visual abstractions. This allows users to transition from a highly-detailed rendering of the anatomical structure to views that emphasize the underlying motif structure and synaptic connectivity. Furthermore, Vimo supports the identification of motif chains where a motif is used repeatedly (e.g., 2 - 4 times) to form a larger network structure. We evaluate Vimo in a user study and an in-depth case study with seven domain experts on motifs in a large connectome of the fruit fly, including more than 21,000 neurons and 20 million synapses. We find that Vimo enables hypothesis generation and confirmation through fast analysis iterations and connectivity highlighting.

neuroscience↗

bioRxiv2022

Connectomics of the Octopus vulgaris vertical lobe provides insight into conserved and novel principles of a memory acquisition network

We present the first analysis of the connectome of the vertical lobe (VL) of Octopus vulgaris, a brain structure mediating acquisition of long-term memory in this behaviorally advanced mollusk. Serial section electron microscopy revealed new types of interneurons, cellular components of extensive modulatory systems and multiple synaptic motifs. The sensory input to the VL is conveyed via ~1,800,000 axons that sparsely innervate two parallel and interconnected feedforward networks formed by the two types of amacrine interneurons (AM), simple AMs (SAMs) and complex AMs (CAMs). SAMs make up 89.3% of the ~25,000,000 VL cells, each receiving a synaptic input from only a single input neuron on its non-bifurcating primary neurite, suggesting that each input neuron is represented in only ~12 SAMs. This synaptic site is likely a "memory site" as it is endowed with LTP. The CAMs, a newly described AM type, comprise 1.6% of the VL cells. Their bifurcating neurites integrate multiple inputs from the input axons and SAMs. While the SAM network appears to feedforward sparse "memorizable" sensory representations into the VL output layer, the CAMs appear to monitor global activity and feedforward a balancing inhibition for "sharpening" the stimulus-specific VL output. While sharing morphological and wiring features with circuits supporting associative learning in other animals, the VL has evolved a unique circuit that enables associative learning based strictly on feedforward information flow.

neuroscience↗

bioRxiv2022

Extensive Soma-Soma Plate-Like Contact Sites (Ephapses) Connect Suprachiasmatic Nucleus Neurons

AO_SCPLOWBSTRACTC_SCPLOWThe hypothalamic suprachiasmatic nucleus (SCN) is the central pacemaker for mammalian circadian rhythms. As such, this ensemble of cell-autonomous neuronal oscillators with divergent periods must maintain coordinated oscillations. To investigate ultrastructural features enabling such synchronization, 805 coronal ultrathin sections of mouse SCN tissue were imaged with electron microscopy and aligned into a volumetric stack, from which selected neurons within the SCN core were reconstructed in silica. We found that clustered SCN core neurons were physically connected to each other via multiple large soma-to-soma plate-like contacts. In some cases, a sliver of a glial process was interleaved. These contacts were large, covering on average [~]21% of apposing neuronal somata. It is possible that contacts may be the electrophysiological substrate for synchronization between SCN neurons. Such plate-like contacts may explain why synchronization of SCN neurons is maintained even when chemical synaptic transmission or electrical synaptic transmission via gap junctions is blocked. Such ephaptic contact-mediated synchronization among nearby neurons may therefore underlie the wave-like oscillations of circadian core clock genes and calcium signals observed in the SCN. SO_SCPLOWIGNIFICANCEC_SCPLOWThree-dimensional reconstruction of SCN tissue via serial electron microscopy revealed a novel structural feature of SCN neurons that may account for inter-neuronal synchronization that persists even when usual mechanisms of neuronal communication are blocked. We found that SCN core neurons are connected by multiple soma-soma contact specializations, ultrastructural elements that could enable synchronization of tightly packed neurons organized in clustered networks. This extensive network of plate-like soma-soma contacts among clustered SCN neurons may provide insight into how [~]20,000 autonomous neuronal oscillators with a broad range of intrinsic periods remain synchronized in the absence of ordinary communication modalities, thereby conferring the resilience required for the SCN to function as the mammalian circadian pacemaker.

neuroscience↗

bioRxiv2022

3D reconstruction of the cerebellar germinal layer reveals intercytoplasmic connections between developing granule cells

SummaryThe difficulty of retrieving high-resolution, in vivo evidence of the proliferative- and migratory processes occurring in neural germinal zones has limited our understanding of neurodevelopmental mechanisms. Here, we employed a connectomic approach using a high-resolution, serial-sectioning scanning electron microscopy volume to investigate the laminar cytoarchitecture of the transient external granular layer (EGL) of the developing cerebellum, where granule cells coordinate a series of mitotic and migratory events. By integrating image segmentation, 3D reconstruction, and deep learning approaches, we discovered and characterized anatomically complex intercellular connections bridging pairs of cerebellar granule cells throughout the EGL. Connected cells were either mitotic, migratory, or transitioning between these two cell stages, displaying a chronological continuum of proliferative and migratory events never previously observed in vivo at this resolution. This unprecedented ultra-structural characterization poses intriguing hypotheses about intercellular connectivity between developing progenitors, and its possible role in the development of the central nervous system (CNS).

neuroscience↗

bioRxiv2022

Multi-Layered Maps of Neuropil with Segmentation-Guided Contrastive Learning

Maps of the nervous system that identify individual cells along with their type, subcellular components, and connectivity have the potential to reveal fundamental organizational principles of neural circuits. Volumetric nanometer-resolution imaging of brain tissue provides the raw data needed to build such maps, but inferring all the relevant cellular and subcellular annotation layers is challenging. Here, we present Segmentation-Guided Contrastive Learning of Representations ("SegCLR"), a self-supervised machine learning technique that produces highly informative representations of cells directly from 3d electron microscope imagery and segmentations. When applied to volumes of human and mouse cerebral cortex, SegCLR enabled the classification of cellular subcompartments (axon, dendrite, soma, astrocytic process) with 4,000-fold less labeled data compared to fully supervised approaches. Surprisingly, SegCLR also enabled inference of cell types (neurons, glia, and subtypes of each) from fragments with lengths as small as 10 micrometers, a task that can be difficult for humans to perform and whose feasibility greatly enhances the utility of imaging portions of brains in which many neuron fragments terminate at a volume boundary. These predictions were further augmented via Gaussian process uncertainty estimation to enable analyses restricted to high confidence subsets of the data. Finally, SegCLR enabled detailed exploration of layer-5 pyramidal cell subtypes and automated large-scale statistical analysis of upstream and downstream synaptic partners in mouse visual cortex.

neuroscience↗

bioRxiv2022

Post-embryonic maturation of the C. elegans motor circuit

During development, animals can maintain behavioral output even as the underlying circuits structurally remodel. After hatching, C. elegans undergoes substantial motor neuron expansion and synapse re-wiring while the animal continuously moves with an undulatory pattern. To understand how the circuit transitions from its juvenile to mature configuration without disrupting functional output, we reconstructed the C. elegans motor circuit by electron microscopy across larval development. We observed: 1) Embryonic motor neurons transiently interact with the developing post-embryonic motor neurons prior to remodeling of their juvenile wiring; 2) Post-embryonic neurons initiate synapse development with their future partners as their neurites navigate through the juvenile nerve cords; 3) Embryonic and post-embryonic neurons sequentially build structural machinery needed for the adult circuit before the embryonic neurons relinquish their roles to post-embryonic neurons; 4) This transition is repeated region by region along the body in an anterior to posterior sequence, following the birth order of post-embryonic neurons. Through this orchestrated, programmed and gradual rewiring, the motor circuit transforms from asymmetric to symmetric wiring. These maturation strategies support the continuous maintenance of motor patterns as the juvenile circuit develops into the adult configuration. HighlightsO_LIPost-embryonic motor circuit maturation was reconstructed by synapse-resolution serial EM. C_LIO_LIMotor patterns are maintained as the circuit matures from asymmetric to symmetric configuration. C_LIO_LIProgrammed rewiring gradually and sequentially transforms the circuit structure. C_LIO_LIPreparatory and communicative wiring-rewiring allows maturation without functional disruption. C_LI

neuroscience↗

bioRxiv2021

Neuromuscular connectomes across development reveal synaptic ordering rules

In mammals, the connections between motor neurons and muscle fibers profoundly reorganize in the early postnatal period. To better understand this synaptic rewiring we traced out all the connectivity in muscles at successive ages in the mouse using serial section scanning electron microscopy in a muscle at birth and Brainbow-based and XFP-based fluorescent reconstructions in neonatal and older muscles respectively. Our data indicate that axons prune about 85% of their branches in the first two weeks of postnatal life, and that while much of this pruning leaves neuromuscular junctions with only one remaining axon (a [~]8-fold reduction), it also causes a [~]6-fold reduction in the number of muscle fibers that possess more than one neuromuscular junction. Unexpectedly, the simplification of the wiring diagram was not haphazard but rather was constrained by the tendency for neurons to maintain co-innervation the longest with other neurons based on their proximity in an abstract rank order. This synaptic ordering preference was even significant at birth when connectivity was the most overlapping but became more striking as development proceeded and was even obvious in the few adult muscle fibers that retained more than one axon at different neuromuscular junctions. Analysis of properties of muscle fibers sharing axons at developing ages and changes in the physical distance between neuromuscular junctions that were maintained in young versus older muscles suggests that the rank order of motor neurons is based on their relative similarity in activity patterns. This same ranking governs both the close-proximity synaptic competitions within neuromuscular junctions and the long-distance competitions that remove or maintain synapses millimeters apart meaning that all neuromuscular rewiring is based on the same global activity ordering rule. We think it is likely that this ranking is related to the ultimate recruitment order of motor axon activity as first described by (Henneman, 1957). Thus the emerging structure of neuromuscular circuitry is a product of its function: initial nearly all-to-all connectivity gives rise to a well-organized system of axons, allowing for the orderly recruitment of neurons during a smoothly graded behavior.

neuroscience↗

bioRxiv2021

Denoising-based Image Compression for Connectomics

Connectomic reconstruction of neural circuits relies on nanometer resolution microscopy which produces on the order of a petabyte of imagery for each cubic millimeter of brain tissue. The cost of storing such data is a significant barrier to broadening the use of connectomic approaches and scaling to even larger volumes. We present an image compression approach that uses machine learning-based denoising and standard image codecs to compress raw electron microscopy imagery of neuropil up to 17-fold with negligible loss of 3d reconstruction and synaptic detection accuracy.

neuroscience↗

bioRxiv2021

A connectomic study of a petascale fragment of human cerebral cortex

We acquired a rapidly preserved human surgical sample from the temporal lobe of the cerebral cortex. We stained a 1 mm3 volume with heavy metals, embedded it in resin, cut more than 5000 slices at [~]30 nm and imaged these sections using a high-speed multibeam scanning electron microscope. We used computational methods to render the three-dimensional structure containing 57,216 cells, hundreds of millions of neurites and 133.7 million synaptic connections. The 1.4 petabyte electron microscopy volume, the segmented cells, cell parts, blood vessels, myelin, inhibitory and excitatory synapses, and 104 manually proofread cells are available to peruse online. Many interesting and unusual features were evident in this dataset. Glia outnumbered neurons 2:1 and oligodendrocytes were the most common cell type in the volume. Excitatory spiny neurons comprised 69% of the neuronal population, and excitatory synapses also were in the majority (76%). The synaptic drive onto spiny neurons was biased more strongly toward excitation (70%) than was the case for inhibitory interneurons (48%). Despite incompleteness of the automated segmentation caused by split and merge errors, we could automatically generate (and then validate) connections between most of the excitatory and inhibitory neuron types both within and between layers. In studying these neurons we found that deep layer excitatory cell types can be classified into new subsets, based on structural and connectivity differences, and that chandelier interneurons not only innervate excitatory neuron initial segments as previously described, but also each others initial segments. Furthermore, among the thousands of weak connections established on each neuron, there exist rarer highly powerful axonal inputs that establish multi-synaptic contacts (up to [~]20 synapses) with target neurons. Our analysis indicates that these strong inputs are specific, and allow small numbers of axons to have an outsized role in the activity of some of their postsynaptic partners.

neuroscience↗

bioRxiv2021

Ultrastructural analysis of dendritic spine necks reveals a continuum of spine morphologies

Dendritic spines are membranous protrusions, with a bulbous head connected to the dendrite by a thin neck, and receive essentially all excitatory inputs in most mammalian neurons. Spines have a wide variety of morphologies that likely have a significant effect on their biochemical and electrical properties. The question of whether spines belong to distinct morphological or functional subtypes or constitute a continuum is still open. To discern this, it is important to measure spine necks objectively. Recent advances in electron microscopy enable automatic reconstructions of 3D spines with nanometer precision. Analyzing ultrastructural reconstructions from mouse neocortical neurons with computer vision algorithms, we demonstrate that the vast majority of spines can be rigorously separated into head and neck components. Analysis of the head and neck morphologies reveals a continuous distribution of parameters. The spine neck diameter, but not the neck length, was correlated with the head volume. Spines with larger head volumes often had a spine apparatus and pairs of spines in a post-synaptic cell contacted by the same axon had similar head volumes. Our data are consistent with a lack of morphological categories of spines and indicate that the morphologies of the spine neck and head are independently regulated. These results have repercussions for our understanding of the function of dendritic spines in neuronal circuits.

neuroscience↗

bioRxiv2020

Connectomes across development reveal principles of brain maturation in C. elegans

From birth to adulthood, an animals nervous system changes as its body grows and its behaviours mature. The form and extent of circuit remodelling across the connectome is unknown. We used serial-section electron microscopy to reconstruct the full brain of eight isogenic C. elegans individuals across postnatal stages to learn how it changes with age. The overall geometry of the brain is preserved from birth to adulthood. Upon this constant scaffold, substantial changes in chemical synaptic connectivity emerge. Comparing connectomes among individuals reveals substantial connectivity differences that make each brain partly unique. Comparing connectomes across maturation reveals consistent wiring changes between different neurons. These changes alter the strength of existing connections and create new connections. Collective changes in the network alter information processing. Over development, the central decision-making circuitry is maintained whereas sensory and motor pathways substantially remodel. With age, the brain progressively becomes more feedforward and discernibly modular. Developmental connectomics reveals principles that underlie brain maturation.

neuroscience↗

bioRxiv2019

An individual interneuron participates in many kinds of inhibition and spans much of the mouse visual thalamus

One way to assess a neurons function is to describe all its inputs and outputs. With this goal in mind, we used serial section electron microscopy to map 899 synaptic inputs and 623 outputs in one inhibitory interneuron in a large volume of the mouse visual thalamus. This neuron innervated 256 thalamocortical cells spread across functionally distinct subregions of the visual thalamus. All but one of its neurites were bifunctional, innervating thalamocortical and local interneurons while also receiving synapses from the retina. We observed a wide variety of local synaptic motifs. While this neuron innervated many cells weakly, with single en passant synapses, it also deployed specialized branches that climbed along other dendrites to form strong multi-synaptic connections with a subset of partners. This neurons diverse range of synaptic relationships allows it to participate in a mix of global and local processing but defies assigning it a single circuit function.

neuroscience↗

bioRxiv2019

The rich get richer: synaptic remodeling between climbing fibers and Purkinje cells in the developing cerebellum begins with positive feedback addition of synapses.

During postnatal development, cerebellar climbing fibers strongly innervate a subset of their original Purkinje cell targets and eliminate their connections from the rest. In the adult, each climbing fiber innervates a small number of Purkinje cells and each Purkinje cell is innervated by a single climbing fiber. To get insight about the processes responsible for this remapping, we reconstructed serial electron microscopy datasets from mice during the first postnatal week. In contrast to adult connectivity, individual neonatal climbing fibers innervate many nearby Purkinje cells, and multiple climbing fibers innervate each Purkinje cell. Between postnatal days 3 and 7, Purkinje cells retract long dendrites and grow many proximal dendritic processes. On this changing landscape, individual climbing fibers selectively add many synapses to a subset of Purkinje cell targets in a positive-feedback manner, without pruning synapses from other Purkinje cells. The active zone sizes of synapses associated with powerful versus weak inputs are indistinguishable. These results show that changes in synapse number rather than synapse size are the predominant form of early developmental plasticity. Finally, although multiple climbing fibers innervate each Purkinje cell in early postnatal development, the number of climbing fibers and Purkinje cells in a local cerebellar region nearly match. Thus, initial over-innervation of Purkinje cells by climbing fibers is economical, in that the number of axons entering a region is enough to assure that each axon ends up with a postsynaptic target, and that none branched there in vain.\n\nHIGHLIGHTSO_LIDeveloping climbing fibers establish synapses on many neighboring Purkinje cells unlike the sparse pattern of innervation in later life\nC_LIO_LIClimbing fibers add many synapses onto a few of their Purkinje targets before the pruning stage in a rich-get-richer type process\nC_LIO_LIThe synapse sizes of strengthened and weakened climbing fiber inputs are indistinguishable.\nC_LIO_LIExuberant branching of climbing fiber axons in early postnatal life appears to be economical because the numbers of axons and Purkinje cells in a local region match, ensuring that each axon can establish a long-lasting connection there\nC_LI\n\nBLURBHigh-resolution serial electron microscopy reconstructions reveal that climbing fiber-Purkinje cell synaptic refinement in the developing cerebellum begins with significant synapse addition. Climbing fibers focus their synapses onto a smaller number of Purkinje cells by selectively adding synapses onto some target cells. All axons that project to a region in development play a role in the final connectivity.

neuroscience↗

bioRxiv2017

Neuronal tracing and analysis by multispectral tracing in densely labeled mouse brain

Accurate and complete neuronal wiring diagrams are necessary for understanding brain function at many scales from long-range interregional projections to microcircuits. Traditionally, light microscopy-based anatomical reconstructions use monochromatic labeling and therefore necessitate sparse labeling to eliminate tracing ambiguity between intermingled neurons. Consequently, our knowledge of neuronal morphology has largely been based on averaged estimations across many samples. Recently developed second-generation Brainbow tools promise to circumvent this limitation by revealing fine anatomical details of many unambiguously identifiable neurons in densely labeled samples. Yet, a means to quantify and analyze the information is currently lacking. Therefore, we developed nTracer, an ImageJ plugin capable of rapidly and accurately reconstructing whole-cell morphology of large neuronal populations in densely labeled brains.

neuroscience↗

bioRxiv2017

Lamellar Junctions In The Endolymphatic Sac Act As A Relief Valve To Regulate Inner Ear Pressure

The inner ear is a fluid-filled closed-epithelial structure whose normal function requires maintenance of an internal hydrostatic pressure and fluid composition by unknown mechanisms. The endolymphatic sac (ES) is a dead-end epithelial tube connected to the inner ear. ES defects can cause distended ear tissue, a pathology often seen in hearing and balance disorders. Using live imaging of zebrafish larvae, we reveal that the ES undergoes cycles of slow pressure-driven inflation followed by rapid deflation every 1-3 hours. Using serial-section electron microscopy and adaptive optics lattice light-sheet microscopy, we find a pressure relief valve in the ES comprised of thin overlapping basal lamellae that dynamically extend over neighboring cells before rupturing under pressure leading to ES collapse. The unexpected discovery of a physical relief valve in the ear emphasizes the need for further study into how organs control fluid pressure, volume, flow, and ion homeostasis in development and disease.

developmental biology↗

bioRxiv2017

Whole-Brain Serial-Section Electron Microscopy In Larval Zebrafish

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.

neuroscience↗