To work within the group of Dr Albert Cardona at the MRC Laboratory of Molecular Biology (LMB), within a programme aimed at whole brain connectomics from volume electron microscopy. Specifically, we are seeking to recruit a data scientist with at least a year of experience with densely labelled volume electron microscopy data of nervous tissue. In particular, the candidate will be experienced in developing and applying machine learning frameworks for synapse detection and segmentation, neuron segmentation and proofreading, and quantification of neuronal structures in nanometre-resolution data sets imaged with volume electron microscopy, for the purpose of mapping neuronal wiring diagrams from volume electron microscopy. The ideal candidate will have an academic track record in the form of authored publications in the arXiv, computer vision conferences, and scientific journals, as well as accessible source code repositories demonstrating past work. The ideal candidate will have experience with the python programming language (at version 3+), and in the use of machine learning libraries with python bindings such as keras or pytorch, and has written code available in accessible source code repositories where it can be evaluated by third parties, and has deployed their code to both CPU and GPU clusters, and single servers with multiple GPUs. The ideal candidate has applied all of the above towards the generation of over-segmentations of neuronal structures, and is familiar with approaches for post-processing (proofreading) to automatically agglomerate over-segmented neuron fragments into full arbors, using biologically grounded approaches such as microtobule or endoplasmatic reticulum segmentation for validation.

This webinar features presentations from SueYeon Chung (New York University) and Srinivas Turaga (HHMI Janelia Research Campus) on theoretical and computational approaches to sensory cognition. Chung introduced a “neural manifold” framework to capture how high-dimensional neural activity is structured into meaningful manifolds reflecting object representations. She demonstrated that manifold geometry—shaped by radius, dimensionality, and correlations—directly governs a population’s capacity for classifying or separating stimuli under nuisance variations. Applying these ideas as a data analysis tool, she showed how measuring object-manifold geometry can explain transformations along the ventral visual stream and suggested that manifold principles also yield better self-supervised neural network models resembling mammalian visual cortex. Turaga described simulating the entire fruit fly visual pathway using its connectome, modeling 64 key cell types in the optic lobe. His team’s systematic approach—combining sparse connectivity from electron microscopy with simple dynamical parameters—recapitulated known motion-selective responses and produced novel testable predictions. Together, these studies underscore the power of combining connectomic detail, task objectives, and geometric theories to unravel neural computations bridging from stimuli to cognitive functions.

Pediatric high-grade gliomas (pHGG) are a devastating group of diseases that urgently require novel therapeutic options. We have previously demonstrated that pHGGs directly synapse onto neurons and the subsequent tumor cell depolarization, mediated by calcium-permeable AMPA channels, promotes their proliferation. The regulatory mechanisms governing these postsynaptic connections are unknown. Here, we investigated the role of BDNF-TrkB signaling in modulating the plasticity of the malignant synapse. BDNF ligand activation of its canonical receptor, TrkB (which is encoded for by the gene NTRK2), has been shown to be one important modulator of synaptic regulation in the normal setting. Electrophysiological recordings of glioma cell membrane properties, in response to acute neurotransmitter stimulation, demonstrate in an inward current resembling AMPA receptor (AMPAR) mediated excitatory neurotransmission. Extracellular BDNF increases the amplitude of this glutamate-induced tumor cell depolarization and this effect is abrogated in NTRK2 knockout glioma cells. Upon examining tumor cell excitability using in situ calcium imaging, we found that BDNF increases the intensity of glutamate-evoked calcium transients in GCaMP6s expressing glioma cells. Western blot analysis indicates the tumors AMPAR properties are altered downstream of BDNF induced TrkB activation in glioma. Cell membrane protein capture (via biotinylation) and live imaging of pH sensitive GFP-tagged AMPAR subunits demonstrate an increase of calcium permeable channels at the tumors postsynaptic membrane in response to BDNF. We find that BDNF-TrkB signaling promotes neuron-to-glioma synaptogenesis as measured by high-resolution confocal and electron microscopy in culture and tumor xenografts. Our analysis of published pHGG transcriptomic datasets, together with brain slice conditioned medium experiments in culture, indicates the tumor microenvironment as the chief source of BDNF ligand. Disruption of the BDNF-TrkB pathway in patient-derived orthotopic glioma xenograft models, both genetically and pharmacologically, results in an increased overall survival and reduced tumor proliferation rate. These findings suggest that gliomas leverage normal mechanisms of plasticity to modulate the excitatory channels involved in synaptic neurotransmission and they reveal the potential to target the regulatory components of glioma circuit dynamics as a therapeutic strategy for these lethal cancers.

Learning is known to induce the formation of new dendritic spines, but despite decades of effort, the functional properties of new spines in vivo remain unknown. Here, using a combination of longitudinal in vivo 2-photon imaging of the glutamate reporter, iGluSnFR, and correlated electron microscopy (CLEM) of dendritic spines on the apical dendrites of L2/3 excitatory neurons in the motor cortex during motor learning, we describe a framework of new spines' formation, survival, and resulting function. Specifically, our data indicate that the potentiation of a subset of clustered, pre-existing spines showing task-related activity in early sessions of learning creates a micro-environment of plasticity within dendrites, wherein multiple filopodia sample the nearby neuropil, form connections with pre-existing boutons connected to allodendritic spines, and are then selected for survival based on co-activity with nearby task-related spines. Thus, the formation and survival of new spines is determined by the functional micro-environment of dendrites. After formation, new spines show preferential co-activation with nearby task-related spines. This synchronous activity is more specific to movements than activation of the individual spines in isolation, and further, is coincident with movements that are more similar to the learned pattern. Thus, new spines functionally engage with their parent clusters to signal the learned movement. Finally, by reconstructing the axons associated with new spines, we found that they synapse with axons previously unrepresented in these dendritic domains, suggesting that the strong local co-activity structure exhibited by new spines is likely not due to axon sharing. Thus, learning involves the binding of new information streams into functional synaptic clusters to subserve the learned behavior.

Dr. Looger will present updates on a variety of molecular tools for studying & manipulating neural circuits & other preparations. Topics include genetically encoded calcium indicators (including the new ultra-fast jGCaMP8 variants), neurotransmitter sensors (improved versions for following glutamate, GABA, acetylcholine, serotonin), optogenetic effectors including the new “enhanced Magnets” dimerizers, AAV serotypes for retrograde labeling & altered tropism, probes for correlative light-electron microscopy, chemical gene switches, etc. He will make all his slides freely available - so don’t worry about hurriedly taking notes; instead focus on questions and ideas for collaboration. Please bring your suggestions for molecular tools that would be transformative for the field.

Brain microstructure plays a key role in driving the transport of drug molecules directly administered to the brain tissue as in Convection-Enhanced Delivery procedures. This study reports the first systematic attempt to characterize the cytoarchitecture of commissural, long association and projection fiber, namely: the corpus callosum, the fornix and the corona radiata. Ovine samples from three different subjects have been imaged using scanning electron microscope combined with focused ion beam milling. Particular focus has been given to the axons. For each tract, a 3D reconstruction of relatively large volumes (including a significant number of axons) has been performed. Namely, outer axonal ellipticity, outer axonal cross-sectional area and its relative perimeter have been measured. This study [1] provides useful insight into the fibrous organization of the tissue that can be described as composite material presenting elliptical tortuous tubular fibers, leading to a workflow to enable accurate simulations of drug delivery which include well-resolved microstructural features.  As a demonstration of the use of these imaging and reconstruction techniques, our research analyses the hydraulic permeability of two white matter (WM) areas (corpus callosum and fornix) whose three-dimensional microstructure was reconstructed starting from the acquisition of the electron microscopy images. Considering that the white matter structure is mainly composed of elongated and parallel axons we computed the permeability along the parallel and perpendicular directions using computational fluid dynamics [2]. The results show a statistically significant difference between parallel and perpendicular permeability, with a ratio about 2 in both the white matter structures analysed, thus demonstrating their anisotropic behaviour. This is in line with the experimental results obtained using perfusion of brain matter [3]. Moreover, we find a significant difference between permeability in corpus callosum and fornix, which suggests that also the white matter heterogeneity should be considered when modelling drug transport in the brain. Our findings, that demonstrate and quantify the anisotropic and heterogeneous character of the white matter, represent a fundamental contribution not only for drug delivery modelling but also for shedding light on the interstitial transport mechanisms in the extracellular space. These and many other discoveries will be discussed during the talk." "1. https://www.researchsquare.com/article/rs-686577/v1, 2. https://www.pnas.org/content/118/36/e2105328118, 3. https://ieeexplore.ieee.org/abstract/document/9198110

The aim of this half day virtual meeting is to consider what is currently achievable with existing techniques and to explore where advancements can be made in the short and medium term. Leading scientists in the field will highlight the questions currently being addressed using hard X-ray imaging techniques, volume electron microscopy and their combination with other imaging modalities, with a forward look to areas of opportunity becoming accessible as a result of the recent and upcoming synchrotron upgrades. We expect an exciting day filled with science focused talks and lively discussions on how the field will develop over the next few years.

The brain is complex over multiple length-scales, from many protein molecules forming intricate nano-machines in a synapse to many neurons forming interconnected networks across the brain. Unraveling this multi-scale complexity is fundamental to our understanding of brain function and disease. In this lecture, I will introduce advances in visualizing the complex, multi-scale structures in the brain. Emphasis will be on new imaging techniques, including cryo electron tomography and correlative light-electron microscopy that enabled revealing in situ organization of synaptic molecules, and ultra-high speed volumetric imaging method VISoR developed to map brain-wide circuits at subcellular resolution. I will also discuss challenges and opportunities for interdisciplinary research collaboration to analyze and understand the enormous data generated by these cutting-edge technologies.

Robust detection of biological structures such as neuronal dendrites in brightfield micrographs, tumor tissue in histological slides, or pathological brain regions in MRI scans is a fundamental task in bio-image analysis. Detection of those structures requests complex decision making which is often impossible with current image analysis software, and therefore typically executed by humans in a tedious and time-consuming manual procedure. Supervised pixel classification based on Deep Convolutional Neural Networks (DNNs) is currently emerging as the most promising technique to solve such complex region detection tasks. Here, a self-learning artificial neural network is trained with a small set of manually annotated images to eventually identify the trained structures from large image data sets in a fully automated way. While supervised pixel classification based on faster machine learning algorithms like Random Forests are nowadays part of the standard toolbox of bio-image analysts (e.g. Ilastik), the currently emerging tools based on deep learning are still rarely used. There is also not much experience in the community how much training data has to be collected, to obtain a reasonable prediction result with deep learning based approaches. Our software YAPiC (Yet Another Pixel Classifier) provides an easy-to-use Python- and command line interface and is purely designed for intuitive pixel classification of multidimensional images with DNNs. With the aim to integrate well in the current open source ecosystem, YAPiC utilizes the Ilastik user interface in combination with a high performance GPU server for model training and prediction. Numerous research groups at our institute have already successfully applied YAPiC for a variety of tasks. From our experience, a surprisingly low amount of sparse label data is needed to train a sufficiently working classifier for typical bioimaging applications. Not least because of this, YAPiC has become the "standard weapon” for our core facility to detect objects in hard-to-segement images. We would like to present some use cases like cell classification in high content screening, tissue detection in histological slides, quantification of neural outgrowth in phase contrast time series, or actin filament detection in transmission electron microscopy.

Dr. Looger will discuss reagents for tracking Ca2+, membrane potential ("voltage"), glutamate, GABA, acetylcholine, serotonin, dopamine, etc. He will also cover optogenetics tools and methods for correlative light/electron microscopy. They make all tools freely available to everyone and work to get them in the hands of people that have limited resources.

We study the larval stages of the marine annelid Platynereis dumerilii, a powerful experimental system for neural circuits. With serial electron microscopy, we have reconstructed the entire nervous and effector systems of a Platynereis larva. We use neurogenetics, activity imaging, and behavioural experiments to understand circuit activity and how the nervous system controls behaviour and physiology. Platynereis is one of very few systems where these different approaches can be combined to study an entire nervous system. I will talk about circuits for the whole-body coordination of locomotor cilia and a hydrodynamic startle response for predator avoidance.

Powerful new ways to image the internal structures and complex dynamics of cells are revolutionizing cell biology and bio-medical research. In this talk, I will focus on how emerging fluorescent technologies are increasing spatio-temporal resolution dramatically, permitting simultaneous multispectral imaging of multiple cellular components. In addition, results will be discussed from whole cell milling using Focused Ion Beam Electron Microscopy (FIB-SEM), which reconstructs the entire cell volume at 4 voxel resolution. Using these tools, it is now possible to begin constructing an “organelle interactome”, describing the interrelationships of different cellular organelles as they carry out critical functions. The same tools are also revealing new properties of organelles and their trafficking pathways, and how disruptions of their normal functions due to genetic mutations may contribute to important diseases.

The "mind of the worm", the first electron microscopy-based connectome of C. elegans, was an early sign of where connectomics is headed, followed by a long time of little progress in a field held back by the immense manual effort required for data acquisition and analysis. This changed over the last few years with several technological breakthroughs, which allowed increases in data set sizes by several orders of magnitude. Brain tissue can now be imaged in 3D up to a millimeter in size at nanometer resolution, revealing tissue features from synapses to the mitochondria of all contained cells. These breakthroughs in acquisition technology were paralleled by a revolution in deep-learning segmentation techniques, that equally reduced manual analysis times by several orders of magnitude, to the point where fully automated reconstructions are becoming useful. Taken together, this gives neuroscientists now access to the first wiring diagrams of thousands of automatically reconstructed neurons connected by millions of synapses, just one line of program code away. In this talk, I will cover these developments by describing the past few years' technological breakthroughs and discuss remaining challenges. Finally, I will show the potential of automated connectomics for neuroscience by demonstrating how hypotheses in reinforcement learning can now be tackled through virtual experiments in synaptic wiring diagrams of the songbird basal ganglia.

The Manookin lab is investigating the structure and function of neural circuits within the retina and developing techniques for treating blindness. Many blinding diseases, such as retinitis pigmentosa, cause death of the rods and cones, but spare other cell types within the retina. Thus, many techniques for restoring visual function following blindness are based on the premise that other cells within the retina remain viable and capable of performing their various roles in visual processing. There are more than 80 different neuronal types in the human retina and these form the components of the specialized circuits that transform the signals from photoreceptors into a neural code responsible for our perception of color, form, and motion, and thus visual experience. The Manookin laboratory is investigating the function and connectivity of neural circuits in the retina using a variety of techniques including electrophysiology, calcium imaging, and electron microscopy. This knowledge is being used to develop more effective techniques for restoring visual function following blindness.

The ability of the brain to encode and store information depends on the plastic nature of the individual synapses. The increase and decrease in synaptic strength, mediated through the structural plasticity of the spine, are important for learning, memory, and cognitive function. Dendritic spines are small structures that contain the synapse. They come in a variety of shapes (stubby, thin, or mushroom-shaped) and a wide range of sizes that protrude from the dendrite. These spines are the regions where the postsynaptic biochemical machinery responds to the neurotransmitters. Spines are dynamic structures, changing in size, shape, and number during development and aging. While spines and synapses have inspired neuromorphic engineering, the biophysical events underlying synaptic and structural plasticity of single spines remain poorly understood. Our current focus is on understanding the biophysical events underlying structural plasticity. I will discuss recent efforts from my group — first, a systems biology approach to construct a mathematical model of biochemical signaling and actin-mediated transient spine expansion in response to calcium influx caused by NMDA receptor activation and a series of spatial models to study the role of spine geometry and organelle location within the spine for calcium and cyclic AMP signaling. Second, I will discuss how mechanics of membrane-cytoskeleton interactions can give insight into spine shape region. And I will conclude with some new efforts in using reconstructions from electron microscopy to inform computational domains. I will conclude with how geometry and mechanics plays an important role in our understanding of fundamental biological phenomena and some general ideas on bio-inspired engineering.

Powerful new ways to image the internal structures and complex dynamics of cells are revolutionizing cell biology and bio-medical research. In this talk, I will focus on how emerging fluorescent technologies are increasing spatio-temporal resolution dramatically, permitting simultaneous multispectral imaging of multiple cellular components. In addition, results will be discussed from whole cell milling using Focused Ion Beam Electron Microscopy (FIB-SEM), which reconstructs the entire cell volume at 4 voxel resolution. Using these tools, it is now possible to begin constructing an “organelle interactome”, describing the interrelationships of different cellular organelles as they carry out critical functions. The same tools are also revealing new properties of organelles and their trafficking pathways, and how disruptions of their normal functions due to genetic mutations may contribute to important diseases.

Africa is blessed with a rich diversity and abundance in rodent and avian populations. This natural endowment on the continent portends research opportunities to study unique anatomical profiles and investigate animal models that may confer better neural architecture to study neurodegenerative diseases, adult neurogenesis, stroke and stem cell therapies. To this end, African researchers are beginning to pay closer attention to some of her indigenous rodents and birds in an attempt to develop spontaneous laboratory models for homegrown neuroscience-based research. For this presentation, I will be showing studies in our lab, involving cellular neuroanatomy of two rodents, the African giant rat (AGR) and Greater cane rat (GCR), Eidolon Bats (EB) and also the Striped Owl (SO). Using histological stains (Cresyl violet and Rapid Golgi) and immunohistochemical biomarkers (GFAP, NeuN, CNPase, Iba-1, Collagen 2, Doublecortin, Ki67, Calbindin, etc), and Electron Microscopy, morphology and functional organizations of neuronal and glial populations of the AGR , GCR, EB and SO brains have been described, with our work ongoing. In addition, the developmental profiles of the prenatal GCR brains have been chronicled across its entire gestational period. Brains of embryos/foetuses were harvested for gross morphological descriptions and then processed using immunofluorescence biomarkers to determine the pattern, onset, duration and peak of neurogenesis (Pax6, Tbr1, Tbr2, NF, HuCD, MAP2) and the onset and peak of glial cell expressions and myelination in the prenatal GCR. The outcome of these research efforts has shown unique neuroanatomical expressions and networks amongst Africa’s rich biodiversity. It is hopeful that continuous effort in this regard will provide sufficient basic research data on neural developments and cellular neuroanatomy with subsequent translational consequences.