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Tiago Ferreira

Bio: Tiago Ferreira is an academic researcher from Howard Hughes Medical Institute. The author has contributed to research in topics: Biological neural network & Asparagine. The author has an hindex of 15, co-authored 27 publications receiving 3400 citations. Previous affiliations of Tiago Ferreira include McGill University & McGill University Health Centre.

Papers
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Journal ArticleDOI
09 Sep 2011-Science
TL;DR: It is shown that microglia actively engulf synaptic material and play a major role in synaptic pruning during postnatal development in mice and this work suggests that deficits in microglian function may contribute to synaptic abnormalities seen in some neurodevelopmental disorders.
Abstract: Microglia are highly motile phagocytic cells that infiltrate and take up residence in the developing brain, where they are thought to provide a surveillance and scavenging function. However, although microglia have been shown to engulf and clear damaged cellular debris after brain insult, it remains less clear what role microglia play in the uninjured brain. Here, we show that microglia actively engulf synaptic material and play a major role in synaptic pruning during postnatal development in mice. These findings link microglia surveillance to synaptic maturation and suggest that deficits in microglia function may contribute to synaptic abnormalities seen in some neurodevelopmental disorders.

3,011 citations

Journal ArticleDOI
TL;DR: The use of the Sholl Analysis software to quantify arborization directly from bitmap images correctly identified 80–86% of cells, and the utility of the method in tackling neurons that are particularly slow to reconstruct manually was explored.
Abstract: To the Editor: Neuroscientists measure the tree-like structures of neurons in order to better understand how neural circuits are constructed and how neural information is processed. In 1953, Donald Sholl published his well-known technique for quantitative analysis of the complex arbors of dendrites and axons1, but conventional methods still require reconstruction of arbors via time-consuming manual or semi-automated tracing from microscopy images. To bypass this reconstruction step and perform the Sholl technique directly on images instead, we developed Sholl Analysis (http://fiji.sc/Sholl), an open-source program for ImageJ/Fiji2 (Supplementary Fig. 1). The plug-in employs an improved algorithm to retrieve data from twoor three-dimensional (2D or 3D) bitmap images in any format supported by the Bio-Formats library (Supplementary Methods). It pairs this data retrieval with curve-fitting, regression analysis and statistical inference so that users can automatically extract a collection of Sholl-based metrics of arborization1,3 (Supplementary Note). Using individual cortical pyramidal neurons in 3D images, we found Sholl Analysis to be accurate when benchmarked against corresponding manual reconstructions (Supplementary Fig. 2). The method was also resilient to image degradation by simulated shot noise (Supplementary Fig. 3 and Supplementary Software). To further assess accuracy, and to explore the utility of Sholl Analysis in tackling neurons that are particularly slow to reconstruct manually, we studied cerebellar Purkinje cells in mice, which have large and intricate dendritic arbors. From tiled 3D image stacks of cerebellum (Fig. 1a), we selected seven Brainbow2.1-expressing Purkinje neurons and isolated their morphologies (Fig. 1b and Supplementary Note). We then used the Sholl Analysis software to retrieve ten metrics and found they were indistinguishable from those retrieved from manual reconstructions of the same 7 cells (Fig. 1c,d and Supplementary Methods). To probe the sensitivity of the Sholl Analysis software, we asked whether its metrics could be used to distinguish closelyrelated neocortical interneuron subtypes. Parvalbumin-positive (PV) interneurons in layer 5 of visual cortex can be morphologically classified into two subtypes on the basis of their axonal morphology: type 1 PV cells have ascending axons arborizing in layer 2/3, whereas axons of type 2 cells remain in layer 5 (ref. 4). Because their dendritic arbors are indistinguishable4, these two cell types otherwise appear highly similar (Fig. 1e,f). Using the Sholl Analysis software, we retrieved 18 metrics directly from 3D image stacks of 12 PV interneurons. We then used Ward’s hierarchical clustering based on these metrics to independently classify these cells (Fig. 1g and Supplementary Fig. 4). The 12 cells segregated into two groups: one group of five neurons and another of seven. We found that all the neurons but two were correctly classified, with one cell assigned incorrectly to each class (Fig. 1g). Thus, our use of the Sholl Analysis software to quantify arborization directly from bitmap images correctly identified 80–86% of cells. In agreement, linear Sholl plots of type 1 cells indicated more branching than was found for type 2 cells at a distance of 225–300 μm from the soma (Fig. 1h), which corresponds to check and inviting routine use. Second, the software can generate a summary report of the current system performance or a full report containing all individual PSF measurements and associated fitting parameters. Third, a table with the extracted resolution, planarity and colocalization data can be exported. This can be used for subsequent analysis, such as in an image processing or restoration pipeline. In addition, an average PSF from a user-selectable region of interest can be exported, for example, for image deconvolution. We used PSFj to quantify the performance of various high– numerical aperture (NA) objectives and to track day-to-day and system-to-system variation. The results showed substantial performance differences and allowed us to identify strengths and weaknesses of individual objectives as well as general shortcomings (Supplementary Figs. 1 and 2). In particular, we found that whereas lateral resolution performance generally fell short (~20–30%), axial resolution often met or exceeded expectations from the scalar approximation of the PSF commonly used in textbooks2 (Supplementary Note). Planarity was usually well corrected with variations over the FOV below the axial resolution and allowed for the detection of tilted slides caused, for example, by dust particles or misaligned slide holders or stages. Axial chromatic shifts were usually small, with little variation across the FOV (Supplementary Table 1). In contrast, chromatic shifts often showed circular symmetry and increased toward the edge of the FOV, which is a sign of lateral chromatic aberrations. Day-to-day performance variation of most objectives was relatively small (~2–6%) and comparable to single-measurement FOV variations (Supplementary Table 2). Furthermore, testing a limited number of identical objectives identified objective-toobjective and microscope-to-microscope variations of about 10% (Supplementary Tables 3 and 4). The PSFj software is open source and based on libraries from various sources, including ImageJ3 and μManager4, and it runs as a stand-alone application on the three major operating systems (using Java).

497 citations

Journal ArticleDOI
19 Sep 2019-Cell
TL;DR: A robust and efficient platform for imaging and reconstructing complete neuronal morphologies, including axonal arbors that span substantial portions of the brain are presented and axonal shapes revealed previously unknown subtypes of projection neurons and suggest organizational principles of long-range connectivity.

309 citations

Journal ArticleDOI
TL;DR: SNT as discussed by the authors is an end-to-end framework for neuronal morphometry and whole-brain connectomics that supports tracing, proof-editing, visualization, quantification and modeling of neuroanatomy.
Abstract: SNT is an end-to-end framework for neuronal morphometry and whole-brain connectomics that supports tracing, proof-editing, visualization, quantification and modeling of neuroanatomy. With an open architecture, a large user base, community-based documentation, support for complex imagery and several model organisms, SNT is a flexible resource for the broad neuroscience community. SNT is both a desktop application and multi-language scripting library, and it is available through the Fiji distribution of ImageJ.

86 citations

Posted ContentDOI
14 Jul 2020-bioRxiv
TL;DR: SNT is a unifying framework for neuronal morphometry and analysis of single-cell connectomics for the widely used Fiji and ImageJ platforms and establishes an end-to-end platform for tracing, proof-editing, visualization, quantification, and modeling of neuroanatomy.
Abstract: Summary Quantification of neuronal morphology is essential for understanding neuronal connectivity and many software tools have been developed for neuronal reconstruction and morphometry. However, such tools remain domain-specific, tethered to specific imaging modalities, and were not designed to accommodate the rich metadata generated by recent whole-brain cellular connectomics. To address these limitations, we created SNT: a unifying framework for neuronal morphometry and analysis of single-cell connectomics for the widely used Fiji and ImageJ platforms. We demonstrate that SNT —that replaces the popular Simple Neurite Tracer software— can be used to tackle important problems in contemporary neuroscience, validate its utility, and illustrate how it establishes an end-to-end platform for tracing, proof-editing, visualization, quantification, and modeling of neuroanatomy. With an open and scriptable architecture, a large user base, and thorough community-based documentation, SNT is an accessible and scalable resource for the broad neuroscience community that synergizes well with existing software.

78 citations


Cited by
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Journal ArticleDOI
TL;DR: ImageJ2 as mentioned in this paper is the next generation of ImageJ, which provides a host of new functionality and separates concerns, fully decoupling the data model from the user interface.
Abstract: ImageJ is an image analysis program extensively used in the biological sciences and beyond. Due to its ease of use, recordable macro language, and extensible plug-in architecture, ImageJ enjoys contributions from non-programmers, amateur programmers, and professional developers alike. Enabling such a diversity of contributors has resulted in a large community that spans the biological and physical sciences. However, a rapidly growing user base, diverging plugin suites, and technical limitations have revealed a clear need for a concerted software engineering effort to support emerging imaging paradigms, to ensure the software’s ability to handle the requirements of modern science. We rewrote the entire ImageJ codebase, engineering a redesigned plugin mechanism intended to facilitate extensibility at every level, with the goal of creating a more powerful tool that continues to serve the existing community while addressing a wider range of scientific requirements. This next-generation ImageJ, called “ImageJ2” in places where the distinction matters, provides a host of new functionality. It separates concerns, fully decoupling the data model from the user interface. It emphasizes integration with external applications to maximize interoperability. Its robust new plugin framework allows everything from image formats, to scripting languages, to visualization to be extended by the community. The redesigned data model supports arbitrarily large, N-dimensional datasets, which are increasingly common in modern image acquisition. Despite the scope of these changes, backwards compatibility is maintained such that this new functionality can be seamlessly integrated with the classic ImageJ interface, allowing users and developers to migrate to these new methods at their own pace. Scientific imaging benefits from open-source programs that advance new method development and deployment to a diverse audience. ImageJ has continuously evolved with this idea in mind; however, new and emerging scientific requirements have posed corresponding challenges for ImageJ’s development. The described improvements provide a framework engineered for flexibility, intended to support these requirements as well as accommodate future needs. Future efforts will focus on implementing new algorithms in this framework and expanding collaborations with other popular scientific software suites.

4,093 citations

Journal ArticleDOI
25 Apr 2013-Nature
TL;DR: This Review discusses how macrophage regulate normal physiology and development, and provides several examples of their pathophysiological roles in disease, and defines the ‘hallmarks’ of macrophages according to the states that they adopt during the performance of their various roles.
Abstract: Macrophages, the most plastic cells of the haematopoietic system, are found in all tissues and show great functional diversity. They have roles in development, homeostasis, tissue repair and immunity. Although tissue macrophages are anatomically distinct from one another, and have different transcriptional profiles and functional capabilities, they are all required for the maintenance of homeostasis. However, these reparative and homeostatic functions can be subverted by chronic insults, resulting in a causal association of macrophages with disease states. In this Review, we discuss how macrophages regulate normal physiology and development, and provide several examples of their pathophysiological roles in disease. We define the 'hallmarks' of macrophages according to the states that they adopt during the performance of their various roles, taking into account new insights into the diversity of their lineages, identities and regulation. It is essential to understand this diversity because macrophages have emerged as important therapeutic targets in many human diseases.

3,368 citations

Journal ArticleDOI
TL;DR: Current studies indicate that even in the normal brain, microglia have highly motile processes by which they scan their territorial domains, and microglial cells are considered the most susceptible sensors of brain pathology.
Abstract: Microglial cells are the resident macrophages in the central nervous system. These cells of mesodermal/mesenchymal origin migrate into all regions of the central nervous system, disseminate through the brain parenchyma, and acquire a specific ramified morphological phenotype termed "resting microglia." Recent studies indicate that even in the normal brain, microglia have highly motile processes by which they scan their territorial domains. By a large number of signaling pathways they can communicate with macroglial cells and neurons and with cells of the immune system. Likewise, microglial cells express receptors classically described for brain-specific communication such as neurotransmitter receptors and those first discovered as immune cell-specific such as for cytokines. Microglial cells are considered the most susceptible sensors of brain pathology. Upon any detection of signs for brain lesions or nervous system dysfunction, microglial cells undergo a complex, multistage activation process that converts them into the "activated microglial cell." This cell form has the capacity to release a large number of substances that can act detrimental or beneficial for the surrounding cells. Activated microglial cells can migrate to the site of injury, proliferate, and phagocytose cells and cellular compartments.

2,998 citations

Journal ArticleDOI
24 May 2012-Neuron
TL;DR: It is shown that microglia engulf presynaptic inputs during peak retinogeniculate pruning and that engulfment is dependent upon neural activity and themicroglia-specific phagocytic signaling pathway, complement receptor 3(CR3)/C3.

2,864 citations

Journal ArticleDOI
TL;DR: Postmortem studies have enabled the staging of the progression of both amyloid and tangle pathologies, and the development of diagnostic criteria that are now used worldwide, and these cross-sectional neuropathological data have been largely validated by longitudinal in vivo studies using modern imaging biomarkers such as amyloids PET and volumetric MRI.
Abstract: The neuropathological hallmarks of Alzheimer disease (AD) include “positive” lesions such as amyloid plaques and cerebral amyloid angiopathy, neurofibrillary tangles, and glial responses, and “negative” lesions such as neuronal and synaptic loss. Despite their inherently cross-sectional nature, postmortem studies have enabled the staging of the progression of both amyloid and tangle pathologies, and, consequently, the development of diagnostic criteria that are now used worldwide. In addition, clinicopathological correlation studies have been crucial to generate hypotheses about the pathophysiology of the disease, by establishing that there is a continuum between “normal” aging and AD dementia, and that the amyloid plaque build-up occurs primarily before the onset of cognitive deficits, while neurofibrillary tangles, neuron loss, and particularly synaptic loss, parallel the progression of cognitive decline. Importantly, these cross-sectional neuropathological data have been largely validated by longitudinal in vivo studies using modern imaging biomarkers such as amyloid PET and volumetric MRI.

2,449 citations