A Survey of Visualization and Analysis in High‐Resolution Connectomics

Beyer, Johanna; Troidl, Jakob; Boorboor, Saeed; Hadwiger, Markus; Kaufman, Arie; Pfister, Hanspeter

doi:10.1111/cgf.14574

Cited by 15 publications

(9 citation statements)

References 232 publications

(371 reference statements)

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“…Electron Microscopy can also uncover single neuron morphology and local connectomics with nanometric synapse level resolution. Using EM to reconstruct neuron wiring and connectivity involves multiple steps: high-throughput data acquisition, image registration, image segmentation, proofreading, and tracking ( Beyer et al, 2022 ). Unlike confocal or light sheet microscopy, 3D EM neuron reconstruction requires physical sectioning of the sample.…”

Section: Image Processing: Quantifying Connectivitymentioning

confidence: 99%

Between neurons and networks: investigating mesoscale brain connectivity in neurological and psychiatric disorders

Caznok Silveira,

Antunes,

Athié

et al. 2024

Front. Neurosci.

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The study of brain connectivity has been a cornerstone in understanding the complexities of neurological and psychiatric disorders. It has provided invaluable insights into the functional architecture of the brain and how it is perturbed in disorders. However, a persistent challenge has been achieving the proper spatial resolution, and developing computational algorithms to address biological questions at the multi-cellular level, a scale often referred to as the mesoscale. Historically, neuroimaging studies of brain connectivity have predominantly focused on the macroscale, providing insights into inter-regional brain connections but often falling short of resolving the intricacies of neural circuitry at the cellular or mesoscale level. This limitation has hindered our ability to fully comprehend the underlying mechanisms of neurological and psychiatric disorders and to develop targeted interventions. In light of this issue, our review manuscript seeks to bridge this critical gap by delving into the domain of mesoscale neuroimaging. We aim to provide a comprehensive overview of conditions affected by aberrant neural connections, image acquisition techniques, feature extraction, and data analysis methods that are specifically tailored to the mesoscale. We further delineate the potential of brain connectivity research to elucidate complex biological questions, with a particular focus on schizophrenia and epilepsy. This review encompasses topics such as dendritic spine quantification, single neuron morphology, and brain region connectivity. We aim to showcase the applicability and significance of mesoscale neuroimaging techniques in the field of neuroscience, highlighting their potential for gaining insights into the complexities of neurological and psychiatric disorders.

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Section: Image Processing: Quantifying Connectivitymentioning

confidence: 99%

Between neurons and networks: investigating mesoscale brain connectivity in neurological and psychiatric disorders

Caznok Silveira,

Antunes,

Athié

et al. 2024

Front. Neurosci.

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“…Proofreading systems for editing the annotations and segmentation may have additional storage requirements such as a graph of connected segments (Anderson et al, 2011;Ai-Awami et al, 2016;Dorkenwald et al, 2021). An excellent overview of the visualization landscape can be found in a recent survey by Beyer et al (2022) and in the VAST paper by Berger et al (2018).…”

Section: Related Workmentioning

confidence: 99%

“…Therefore, we will only briefly treat the most closely related systems to confine ourselves to the available space. Again, please consult Berger et al (2018) and Beyer et al (2022) for more information.…”

Section: Skeletonizationmentioning

confidence: 99%

“…There are many types of data involved in such investigations (Pfister et al, 2014;Beyer et al, 2022), but at the microscale, they typically consist of stacks of single-channel electron or multichannel confocal microscopy images. Electron micrograph stacks are processed into (usually dense) per-voxel 32 or 64bit labelings ("segmentations") and intermediate representations such as three-channel 32-bit floating point voxel affinities.…”

Section: Introductionmentioning

confidence: 99%

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Igneous: Distributed dense 3D segmentation meshing, neuron skeletonization, and hierarchical downsampling

Silversmith¹,

Zlateski²,

Bae³

et al. 2022

Front. Neural Circuits

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Three-dimensional electron microscopy images of brain tissue and their dense segmentations are now petascale and growing. These volumes require the mass production of dense segmentation-derived neuron skeletons, multi-resolution meshes, image hierarchies (for both modalities) for visualization and analysis, and tools to manage the large amount of data. However, open tools for large-scale meshing, skeletonization, and data management have been missing. Igneous is a Python-based distributed computing framework that enables economical meshing, skeletonization, image hierarchy creation, and data management using cloud or cluster computing that has been proven to scale horizontally. We sketch Igneous's computing framework, show how to use it, and characterize its performance and data storage.

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“…Visual analysis approaches have been used in many subareas of connectomics, including interactive proofreading [GWB*21, DMM*22], volume exploration [BAAK*13], and neighborhood- [TCG*22] and morphology analysis [MAAB*18, CLL*21]. Beyer et al [BTB*22] provide a comprehensive survey of visualization methods in connectomics. Most neural connectivity visualizations use nodelink diagrams [SCHT09, BAAK*13].…”

Section: Related Workmentioning

confidence: 99%

Vimo: Visual Analysis of Neuronal Connectivity Motifs

Troidl

Warchol

Choi

et al. 2022

Preprint

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Recent advances in high-resolution connectomics provide researchers access to accurate reconstructions of vast neuronal circuits and brain networks for the first time. Neuroscientists anticipate analyzing these networks to gain a better understanding of information processing in the brain. In particular, scientists are interested in identifying specific network motifs, i.e., repeating subgraphs of the larger brain network that are believed to be neuronal building blocks. To analyze these motifs, it is crucial to review instances of a motif in the brain network and then map the graph structure to the 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 of the involved neurons and synapses. To reduce visual clutter and simplify the analysis of MIs, we designed a continuous focus&context metaphor inspired by continuous visual abstractions that allows the user to transition from the 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 to form a longer synaptic chain. We evaluate Vimo in a user study with seven domain experts and an in-depth case study on motifs in the central complex (CX) of the fruit fly brain.

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A Survey of Visualization and Analysis in High‐Resolution Connectomics

Cited by 15 publications

References 232 publications

Between neurons and networks: investigating mesoscale brain connectivity in neurological and psychiatric disorders

Between neurons and networks: investigating mesoscale brain connectivity in neurological and psychiatric disorders

Igneous: Distributed dense 3D segmentation meshing, neuron skeletonization, and hierarchical downsampling

Vimo: Visual Analysis of Neuronal Connectivity Motifs

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