17 research outputs found

    A proposal for a coordinated effort for the determination of brainwide neuroanatomical connectivity in model organisms at a mesoscopic scale

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    In this era of complete genomes, our knowledge of neuroanatomical circuitry remains surprisingly sparse. Such knowledge is however critical both for basic and clinical research into brain function. Here we advocate for a concerted effort to fill this gap, through systematic, experimental mapping of neural circuits at a mesoscopic scale of resolution suitable for comprehensive, brain-wide coverage, using injections of tracers or viral vectors. We detail the scientific and medical rationale and briefly review existing knowledge and experimental techniques. We define a set of desiderata, including brain-wide coverage; validated and extensible experimental techniques suitable for standardization and automation; centralized, open access data repository; compatibility with existing resources, and tractability with current informatics technology. We discuss a hypothetical but tractable plan for mouse, additional efforts for the macaque, and technique development for human. We estimate that the mouse connectivity project could be completed within five years with a comparatively modest budget.Comment: 41 page

    Homologous organization of cerebellar pathways to sensory, motor, and associative forebrain.

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    Cerebellar outputs take polysynaptic routes to reach the rest of the brain, impeding conventional tracing. Here, we quantify pathways between the cerebellum and forebrain by using transsynaptic tracing viruses and a whole-brain analysis pipeline. With retrograde tracing, we find that most descending paths originate from the somatomotor cortex. Anterograde tracing of ascending paths encompasses most thalamic nuclei, especially ventral posteromedial, lateral posterior, mediodorsal, and reticular nuclei. In the neocortex, sensorimotor regions contain the most labeled neurons, but we find higher densities in associative areas, including orbital, anterior cingulate, prelimbic, and infralimbic cortex. Patterns of ascending expression correlate with c-Fos expression after optogenetic inhibition of Purkinje cells. Our results reveal homologous networks linking single areas of the cerebellar cortex to diverse forebrain targets. We conclude that shared areas of the cerebellum are positioned to provide sensory-motor information to regions implicated in both movement and nonmotor function

    Novel application of stochastic modeling techniques to long-term, high-resolution time-lapse microscopy of cortical axons

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    Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Brain and Cognitive Sciences, 2010.Cataloged from PDF version of thesis.Includes bibliographical references (p. 64-70).Axons exhibit a rich variety of behaviors, such as elongation, turning, branching, and fasciculation, all in service of the complex goal of wiring up the brain. In order to quantify these behaviors, I have developed a system for in vitro imaging of axon growth cones with time-lapse fluorescence microscopy. Image tiles are automatically captured and assembled into a mosaic image of a square millimeter region. GFP-expressing mouse cortical neurons can be imaged once every few minutes for up to weeks if phototoxicity is minimized. Looking at the data, the trajectories of axon growth cones seem to alternate between long, straight segments and sudden turns. I first rigorously test the idea that the straight segments are generated from a biased random walk by analyzing the correlation between growth cone steps in the time and frequency domain. To formalize and test the intuition that sharp turns join straight segments, I fit a hidden Markov model to time series of growth cone velocity vectors.(cont.) The hidden state variable represents the bias direction of a biased random walk, and specifies the mean and variance of a Gaussian distribution from which velocities are drawn. Rotational symmetry is used to constrain the transition probabilities of the hidden variable, as well as the Gaussian distributions for the hidden states. Maximum likelihood estimation of the model parameters shows that the most probable behavior is to remain in the same hidden state. The second most probable behavior is to turn by about 40 degrees. Smaller angle turns are highly improbable, consistent with the idea that the axon makes sudden turns. When the same hidden Markov model was applied to artificially generated meandering trajectories, the transition probabilities were significant only for small angle turns. This novel application of stochastic models to growth cone trajectories provides a quantitative framework for testing interventions (eg. pharmacological, activity-related, etc.) that can impact axonal growth cone movement and turning. For example, manipulations that inhibit actin polymerization increase the frequency and angle of turns made by the growth cone. More generally, axon behaviors may be useful in deducing computational principles for wiring up circuits.by Neville Espi Sanjana.Ph.D

    Interactions Between Microbial, Neuronal, and Immune Cells in the Digestive System

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    The intestine is the largest continuous environmental interface of the body. As such, it exerts homeostatic tissue functions, including digestion, sensing and absorption of nutrients, and excretion of waste products. In performing these roles, the intestine faces the unique challenge of remaining tolerant to harmless or beneficial diet- and microbederived stimuli, while simultaneously protecting against pathogen invasion. To tackle these challenges, the intestine houses both the body’s largest immune compartment, as well as a vast neuronal network, the enteric nervous system (ENS). In concert with the commensal intestinal microbiota, the enteric immune and nervous systems communicate with one another, and this crosstalk was the focus of my thesis work. The studies as presented here are divided into two parts: The first part will focus on the influence of gut microbes on the murine ENS and its functions in host physiology. The second part will investigate the dynamic interplay between gut microbes, neurons and immune cells in the murine intestine during homeostasis and upon microbial perturbations. The human intestinal tract is home to ~10 trillion commensal microbes (Sender et al., 2016). The microbiota influences key physiological processes including nutrient absorption and lipid metabolism. Further, it has been demonstrated to influence the basal activity of intestine-associated cells, including the excitability of enteric neurons (Furness et al., 2013). Alterations to the composition of the gut microbiota have a potential role in systemic disorders including obesity and diabetes (Ridaura et al., 2013). Yet, the mechanisms underlying these effects of the microbiota, and whether they are mediated by components of the ENS, are still poorly understood. In addition, the cellular circuits and molecular components that mediate gut-to-enteric neuron or gut-to-brain communication remain largely unknown. We thus aimed to determine how commensal microbes influence enteric neurons and their functions to better characterize their role in tissue function and further sought to investigate how disturbances to the microbial composition – during microbial dysbiosis and enteric infections – impact the ENS and host physiology. Using translating ribosomal affinity purification (TRAP)-sequencing, coupled with confocal microscopy, we found that enteric neurons are functionally adapted to the intestinal segment they occupy. By utilizing germ-free mice, we uncovered a stronger influence of the microbiota on distal intestine neurons, correlating with the region’s higher bacterial density. Chronic antibiotic-mediated microbial depletion reinstated our findings in germ-free mice, establishing that specific subsets of enteric neurons, including those expressing the neuropeptide cocaine and amphetamine-regulated transcript (CART), are dependent on the microbiota for their survival. Notably, these changes were not permanent, as colonization of germ-free mice and replenishment of the microbiota of antibiotic-treated mice restored neuronal numbers and neuropeptide levels. We found that murine enteric infections with different pathogens led to lasting intestinal inflammation, functional disturbances and most notably, rapid and persistent enteric neuron loss driven by a persistent alteration to the microbial composition postinfection; however, restoration of a healthy microbiota was sufficient to induce tissue recovery. Mechanistically, neuronal loss post-infection and following microbial depletion was mediated by a novel form of enteric neuronal cell death, involving the non-canonical inflammasome components NLRP6 and caspase 11. In further characterizing enteric neuronal populations, we identified a subset of intestinal CART+ neurons that were enriched in the distal intestine and modulated by the microbiota. Through microbial modulation strategies and chemogenetic targeting, we found that these enteric CART+ neurons regulate metabolic parameters including blood glucose and insulin levels. Retro- and anterograde tracing studies revealed that a subset of enteric CART+ neurons send axons to the gut sympathetic ganglion and are synaptically connected to the liver and pancreas. Together, we uncovered a gutpancreas- liver circuit that regulates glucose metabolism by sensing microbial cues. This peripherally-restricted circuit offers unique neuronal targets for the treatment of metabolic disorders, such as type 2 diabetes, which would bypass central nervous system effects. We further aimed to better characterize the role of neuro-immune interactions in the context of enteric pathologies, including post-infectious intestinal dysfunction and neuronal damage observed upon enteric infections. We further sought to determine whether a state of tolerance could be induced upon exposure to enteric pathogens, preventing tissue damage during subsequent infections. Finally, we aimed to characterize the role of extrinsic gut-projecting neurons to understand their role in sensing and responding to luminal cues, including enteric infections. Using cell sorting-independent transcriptomics, confocal imaging, genetic gainand loss-of-function approaches, surgical lesioning, chemogenetic manipulations, as well as multiple microbial manipulation strategies, we identified a critical role for enteric neuron-macrophage crosstalk in limiting ENS damage induced by a single enteric infection. A population of tissue-resident macrophages residing in close proximity to enteric neurons responded to luminal cues by upregulating a tissue-protective signature, and mediated enteric neuronal protection through adrenergic receptor signaling, and an arginase 1-polyamine program. Notably, we found engagement of macrophage adrenergic receptor signaling to be dependent on local catecholamine release by gutinnervating sympathetic neurons. We further uncovered that these sympathetic neurons on their end are tuned by enteric microbes and microbial products, in that a healthy microbiota suppresses, and absence of a microbiota, dysbiosis and infection enhance their activity. Finally, we found that previous infection with unrelated pathogens prevented infection-induced neuronal loss during subsequent, heterologous infections, suggesting a form of innate immune memory, or “trained tolerance”. Of note, while enteric bacterial and helminth infections induced distinct immune responses, these converged at the level of tissue-protective intestinal macrophages, which mediated enteric neuronal protection, aiding host fitness. Together, this work identified a functional role for interactions between sympathetic neurons, tissue-resident macrophages and enteric neurons in limiting infection-induced tissue damage. Overall, the research presented in this work uncovered that the ENS relies on the gut-resident microbiota for its homeostatic tissue function, with influence for local intestinal function and systemic metabolism. Furthermore, through communication with gut-extrinsic sympathetic neurons, tissue-resident macrophages upregulate and maintain a tissue-protective program, which protects enteric neurons from excessive damage during primary enteric infections and prevents cumulative damage during subsequent perturbations

    THE FIRST 3D MODEL OF THE OLFACTORY BULB:A STUDY ON ODOR LEARNING AND REPRESENTATION

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    Le attuali tecniche sperimentali non permettono di studiare come il bulbo olfattivo processa gli odori, quindi ne abbiamo sviluppato un modello tridimensionale su larga scala. Questi riproduce in maniera realistica gli stimoli dovuti alla presenza di odori naturali, le morfologie di cellule mitrali e granulari, insieme alla loro connettivit\ue0. Il nostro modello ritorna predizioni che sono sperimentalmente verificabili, fornendo un potente strumento per lo studio delle computazioni del bulbo olfattivo, quali ad esempio l'apprendimento e la rappresentazione degli odori. Con l'apprendimento di un odore, il bulbo olfattivo si auto-organizza in gruppi di colonne, ciascuna in corrispondenza di un singolo glomerulo o unit\ue0 glomerulare. Usando il nostro modello, abbiamo identificato i meccanismi su cui si basa la formazione di una o pi\uf9 colonne/unit\ue0 glomerulari in seguito alla presentazione di un odore. In aggiunta, abbiamo esaminato come le interazioni fra unit\ue0 glomerulari durante l'apprendimento possono influenzare la configurazione finale delle colonne. In seguito, abbiamo studiato come il bulbo olfattivo elabora gli ingressi provenienti dai recettori olfattivi attivati dagli odori naturali. Questo avviene su due livelli computazionali: lo strato glomerulare al livello di input, e lo strato delle cellule granulari al livello di output verso la corteccia olfattiva. Ci\uf2 suggerisce che le funzioni postulate nei circuiti glomerulari hanno come ruolo primario la trasformazione di un input complesso e disorganizzato in una rappresentazione dove i livelli di attivazione sono normalizzati, e il loro contrasto intensificato. Tuttavia l\u2019output del livello glomerulare non pu\uf2 sincronizzare l\u2019attivit\ue0 dei glomerulari. Pertanto, a livello delle cellule granulari, le interazioni dendrodendritiche inducono una decorrelazione temporale dei pattern rappresentativi dei vari odori, a sua volta dipendente da quella precedentemente realizzata nel livello glomerulare. Questi risultati forniscono importanti indizi riguardanti la computazione/rappresentazione del bulbo olfattivo, dimostrando l'importanza della sua auto-organizzazione modulare in unit\ue0 glomerulari. La sua organizzazione a strati \ue8 particolarmente importante per la rappresentazione degli odori naturali, dal momento che le aree da essi attivate sulla superficie del bubo sono sovrapposte.How the olfactory bulb processes odor input cannot be easily addressed using standard experimental techniques, therefore we have developed a large scale model of olfactory bulb, using realistic three-dimensional inputs, cell morphologies of mitral and granule cells, and connectivity. The model makes experimentally testable prediction, providing a powerful framework for investigating the olfactory bulb computations, such as the odor learning and representation. By the odor learning, the olfactory bulb organizes itself in synaptic columnar clusters related to individual glomeruli, called glomerular units. Using our 3D model, we identify the mechanisms for forming one or more glomerular units in response to a given odor, how and to what extent the glomerular units interfere or interact with each other during learning. Together, we have analyzed how the olfactory bulb processes inputs from olfactory receptor neurons activated by natural odors. This is realized through two computational tiers: the glomerular layer at the site of input, and the granule cell level at the site of output to the olfactory cortex. We suggest that the postulated functions of glomerular circuits have as their primary role transforming a complex and disorganized input into a contrast-enhanced and normalized representation, but cannot provide for synchronization of the distributed glomerular outputs. By contrast, at the granule cell layer, the dendrodendritic interactions mediate temporal decorrelation, which we show is dependent on the preceding contrast enhancement by the glomerular layer. The results provide the first insights into the successive operations in the olfactory bulb, and demonstrate the significance of the modular organization around glomeruli. This layered organization is especially important for natural odor inputs, because they activate many overlapping glomeruli

    Use of functional neuroimaging and optogenetics to explore deep brain stimulation targets for the treatment of Parkinson's disease and epilepsy

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    Deep brain stimulation (DBS) is a neurosurgical therapy for Parkinson’s disease and epilepsy. In DBS, an electrode is stereotactically implanted in a specific region of the brain and electrical pulses are delivered using a subcutaneous pacemaker-like stimulator. DBS-therapy has proven to effectively suppress tremor or seizures in pharmaco-resistant Parkinson’s disease and epilepsy patients respectively. It is most commonly applied in the subthalamic nucleus for Parkinson’s disease, or in the anterior thalamic nucleus for epilepsy. Despite the rapidly growing use of DBS at these classic brain structures, there are still non-responders to the treatment. This creates a need to explore other brain structures as potential DBS-targets. However, research in patients is restricted mainly because of ethical reasons. Therefore, in order to search for potential new DBS targets, animal research is indispensable. Previous animal studies of DBS-relevant circuitry largely relied on electrophysiological recordings at predefined brain areas with assumed relevance to DBS therapy. Due to their inherent regional biases, such experimental techniques prevent the identification of less recognized brain structures that might be suitable DBS targets. Therefore, functional neuroimaging techniques, such as functional Magnetic Resonance Imaging and Positron Emission Tomography, were used in this thesis because they allow to visualize and to analyze the whole brain during DBS. Additionally, optogenetics, a new technique that uses light instead of electricity, was employed to manipulate brain cells with unprecedented selectivity

    A Pipeline for Automated Assessment of Cell Location in 3D Mouse Brain Image Sets

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    Mapping the neuronal connectivity of the mouse brain has long been hampered by the laborious and time-consuming process of slicing, staining and imaging the brain tissue. Recent developments in automated 3D fluorescence microscopy, such as serial two- photon tomography (STP) and light sheet fluorescence microscopy, now allow for automated rapid 3D imaging of a complete mouse brain at cellular resolution. In combination with transsynaptic viral tracers, this paves the way for high-throughput brain mapping studies, which could greatly advance our understanding of the function of the brain. Because transsynaptic tracers label synaptically connected cells, the analysis of these whole-brain scans requires detection of fluorescently labelled cells and anatomical segmentation of the data, which are very labour- and time-intensive manual tasks and prevent high-throughput analysis. This thesis presents and validates two software tools to automate anatomical segmentation and cell detection in serial two photon (STP) scans of the mouse brain. Automated mouse atlas propagation (aMAP) segments the scans into anatomical regions by matching a 3D reference atlas to the data using affine and free-form image registration. The fast automated cell counting tool (FACCT) then detects fluorescently labelled cells in the dataset with a novel approach of stepwise data reduction combined with object detection using artificial neuronal networks. The tools are optimised for large datasets and are capable of processing a 2.5TB STP scan in under two days. The performance of aMAP and FACCT is evaluated on STP scans from retrograde connectivity tracing experiments using rabies virus injections in the primary visual corte

    Optical microscopy to study the role of cytoskeleton in cell locomotion and virus trafficking

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    3. General conclusions 150 The interest in optical microscopy is constanly growing, mainly because of its unique features in examining biological systems in four dimensions (x-y-z-t)1 . The work presented here was focused on biological applications of optical microscopy by exploring and improving the spatial and temporal resolution performances and by futher developing optical tools for manipulating biological samples. First, I studied the resolution performances of the system in the three dimensional space and I contributed in improving the experimental spatial resolution of microscope by applying deconvolution. In this respect, theoretical modelling can characterize the image formation process of the microscope, but only experimental measurement of the PSF can quantify the limitations of the real system. Indeed, experimental PSF presents shape assymetry due to spherical aberrations introduced by optical elements, while theoretical PSF is symmetric and account only for the resolution limits of an ideal imaging system. The disadvantage of experimental PSF is that could be corrupted by noise, otherwise deconvolution with the theoretical PSF offer only a qualitative improvement of the image, because the introduced artefacts cannot be quantified. Deconvolution of the acquired data with experimental PSF...3. General conclusions 150 The interest in optical microscopy is constanly growing, mainly because of its unique features in examining biological systems in four dimensions (x-y-z-t)1 . The work presented here was focused on biological applications of optical microscopy by exploring and improving the spatial and temporal resolution performances and by futher developing optical tools for manipulating biological samples. First, I studied the resolution performances of the system in the three dimensional space and I contributed in improving the experimental spatial resolution of microscope by applying deconvolution. In this respect, theoretical modelling can characterize the image formation process of the microscope, but only experimental measurement of the PSF can quantify the limitations of the real system. Indeed, experimental PSF presents shape assymetry due to spherical aberrations introduced by optical elements, while theoretical PSF is symmetric and account only for the resolution limits of an ideal imaging system. The disadvantage of experimental PSF is that could be corrupted by noise, otherwise deconvolution with the theoretical PSF offer only a qualitative improvement of the image, because the introduced artefacts cannot be quantified. Deconvolution of the acquired data with experimental PSF...Department of Genetics and MicrobiologyKatedra genetiky a mikrobiologieFaculty of SciencePřírodovědecká fakult
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