Graph-Based Visualization of Neuronal Connectivity Using Matrix Block Partitioning and Edge Bundling

McGraw, Tim

doi:10.1007/978-3-319-27857-5_1

Cited by 4 publications

(4 citation statements)

References 23 publications

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“…Neuron tracing algorithms and the field of connectomics were introduced for the quantitative analysis of neuron morphology and functioning. Connectomics [47] aims to develop methods to reconstruct a complete map of the nervous system [2,4,57] and the connections between neuronal structures [15,23,46]. Neuron tracing algorithms are designed to automatically or interactively extract the skeletal morphology of neurons.…”

Section: Quantitative Analysismentioning

confidence: 99%

Visualization of Neuronal Structures in Wide-Field Microscopy Brain Images

Boorboor

Jadhav

Ananth

et al. 2019

IEEE Trans. Visual. Comput. Graphics

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Wide-field microscopes are commonly used in neurobiology for experimental studies of brain samples. Available visualization tools are limited to electron, two-photon, and confocal microscopy datasets, and current volume rendering techniques do not yield effective results when used with wide-field data. We present a workflow for the visualization of neuronal structures in wide-field microscopy images of brain samples. We introduce a novel gradient-based distance transform that overcomes the out-of-focus blur caused by the inherent design of wide-field microscopes. This is followed by the extraction of the 3D structure of neurites using a multi-scale curvilinear filter and cell-bodies using a Hessian-based enhancement filter. The response from these filters is then applied as an opacity map to the raw data. Based on the visualization challenges faced by domain experts, our workflow provides multiple rendering modes to enable qualitative analysis of neuronal structures, which includes separation of cell-bodies from neurites and an intensity-based classification of the structures. Additionally, we evaluate our visualization results against both a standard image processing deconvolution technique and a confocal microscopy image of the same specimen. We show that our method is significantly faster and requires less computational resources, while producing high quality visualizations. We deploy our workflow in an immersive gigapixel facility as a paradigm for the processing and visualization of large, high-resolution, wide-field microscopy brain datasets.

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Section: Quantitative Analysismentioning

confidence: 99%

Visualization of Neuronal Structures in Wide-Field Microscopy Brain Images

Boorboor

Jadhav

Ananth

et al. 2019

IEEE Trans. Visual. Comput. Graphics

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“…For example, neuroMap [18] uses circuit wiring diagrams to represent possible connections between neurons. Other tools for high-level connectivity visualization make use of 2D projections for 3D tractography data [19], or use matrix visualizations for showing connectivity information [20].…”

Section: Visualization For Connectomicsmentioning

confidence: 99%

“…Node-link diagrams are the most common form for representing the connectivity between brain regions and/or individual neurons. McGraw [20] has worked on the macroscale level for visualization of structural connectivity that is computed from diffusion imaging. His work uses bundled edge graph layout technique to preserve the relative position of nodes, because they provide important contextual information, while minimizing the clutter and occlusion that results from visualizing networks with large number of edges.…”

Section: Network Layoutsmentioning

confidence: 99%

Abstractocyte: A Visual Tool for Exploring Nanoscale Astroglial Cells

Mohammed

Al-Awami

Beyer

et al. 2018

IEEE Trans. Visual. Comput. Graphics

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This thesis presents the design and implementation of Abstractocyte, a system for the visual analysis of astrocytes, and their relation to neurons, in nanoscale volumes of brain tissue. Astrocytes are glial cells, i.e., non-neuronal cells that support neurons and the nervous system. Even though glial cells make up around 50 percent of all cells in the mammalian brain, so far they have been far less studied than neurons. Nevertheless, the study of astrocytes has immense potential for understanding brain function. However, the complex and widely-branching structure of astrocytes requires high-resolution electron microscopy imaging and makes visualization and analysis challenging. Using Abstractocyte, biologists can explore the morphology of astrocytes at various visual abstraction levels, while simultaneously analyzing neighboring neurons and their connectivity. We define a novel, conceptual 2D abstraction space for jointly visualizing astrocytes and neurons. Neuroscientists can choose a joint visualization as a specific point in that 2D abstraction space. Dragging this point allows them to smoothly transition between different abstraction levels in an intuitive manner. We describe the design of Abstractocyte, and present three case studies in which neuroscientists have successfully used our system to assess astrocytic coverage of synapses, glycogen distribution in relation to synapses, and astrocyticmitochondria coverage.

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“…Recently, some connectome visualization projects have utilized edge bundling. Two dimensional edge bundling is used by McGraw [40] and Yang et al [63], while 3D edge bundling is used in [8,9] for representing functional connectivity that shows high levels of common interconnections (see Fig. 2).…”

Section: Visualization In Connectomicsmentioning

confidence: 99%

Exploring the Human Connectome Topology in Group Studies

Keiriz¹,

Zhan²,

Chukhman³

et al. 2017

Preprint

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Fig. 1. A screen capture of the NeuroCave visualization tool showing the average resting state functional connectome of subjects between the age of 20 and 30 years old for females in the clustering space (left) versus males in the anatomical space (right). Our tool facilitates the simultaneous exploration of multiple connectome datasets in a variety of configurations, enabling researchers to make meaningful comparisons between them and to reason about their differences.

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Graph-Based Visualization of Neuronal Connectivity Using Matrix Block Partitioning and Edge Bundling

Cited by 4 publications

References 23 publications

Visualization of Neuronal Structures in Wide-Field Microscopy Brain Images

Visualization of Neuronal Structures in Wide-Field Microscopy Brain Images

Abstractocyte: A Visual Tool for Exploring Nanoscale Astroglial Cells

Exploring the Human Connectome Topology in Group Studies

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