Analyzing Large Connectome Graphs With BossDB Network Tools

Modern connectomics enables large-scale, comparative network neuroscience across individuals, species, development, and evolution. The field now regularly produces extensive maps of neural connectivity exceeding hundreds of millions of synapses in continuous volumes. When connectomes are deposited in central archives such as BossDB with standardized metadata, researchers can pose previously intractable questions about neuronal networks. Here, we present step-by-step protocols for connectome dataset discovery and access, scalable graph construction and analysis, and reproducible comparative connectomics using BossDB, Motif Studio, DotMotif, Neuroglancer, neuPrint, and Python-based workflows. These protocols target bench neuroscientists and computational biologists and emphasize replicability, cloud-friendly options, and publication-quality visualization. © 2025 Wiley Periodicals LLC. Basic Protocol 1: Discovering connectome datasets and computing summary statistics with BossDB and Motif Studio Basic Protocol 2: Writing queries with DotMotif Basic Protocol 3: Querying known network motifs locally with DotMotif Support Protocol 1: Provisioning ad hoc graph databases for large-scale graph analysis Support Protocol 2: Querying structures and systems in the cloud with neuPrint Basic Protocol 4: Viewing anatomical motif features with BossDB and Neuroglancer.

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Publication Details

Journal
Current Protocols
Published
2025-12-01
DOI
https://doi.org/10.1002/cpz1.70273
Primary Topic
Functional Brain Connectivity Studies
Type
article
Field-Weighted Citation Impact
0.00
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article

Analyzing Large Connectome Graphs With BossDB Network Tools

Jordan Matelsky, Michael S. Robinette, Daniel Xenes, Brock A. Wester et al.
Current Protocols
Functional Brain Connectivity Studies
article

Analyzing Large Connectome Graphs With BossDB Network Tools

Jordan Matelsky, Michael S. Robinette, Daniel Xenes, Brock A. Wester, H. Martínez, Akshita Panigrahi
article en

Abstract

Modern connectomics enables large-scale, comparative network neuroscience across individuals, species, development, and evolution. The field now regularly produces extensive maps of neural connectivity exceeding hundreds of millions of synapses in continuous volumes. When connectomes are deposited in central archives such as BossDB with standardized metadata, researchers can pose previously intractable questions about neuronal networks. Here, we present step-by-step protocols for connectome dataset discovery and access, scalable graph construction and analysis, and reproducible comparative connectomics using BossDB, Motif Studio, DotMotif, Neuroglancer, neuPrint, and Python-based workflows. These protocols target bench neuroscientists and computational biologists and emphasize replicability, cloud-friendly options, and publication-quality visualization. © 2025 Wiley Periodicals LLC. Basic Protocol 1: Discovering connectome datasets and computing summary statistics with BossDB and Motif Studio Basic Protocol 2: Writing queries with DotMotif Basic Protocol 3: Querying known network motifs locally with DotMotif Support Protocol 1: Provisioning ad hoc graph databases for large-scale graph analysis Support Protocol 2: Querying structures and systems in the cloud with neuPrint Basic Protocol 4: Viewing anatomical motif features with BossDB and Neuroglancer.

Current ProtocolsVol. 5(12)
Johns Hopkins University Applied Physics Laboratory (US), University of Pennsylvania (US)
Openalex Percentile: Top 32%
Functional Brain Connectivity Studies
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