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About Virtual Fly Brain

Virtual Fly Brain (VFB) is an interactive tool for neurobiologists to explore the detailed neuroanatomy, neuron connectivity and gene expression of Drosophila melanogaster. Our goal is to make it easier for researchers to find relevant anatomical information and reagents. We integrate the neuroanatomical and expression data from the published literature, as well as image datasets onto the same brain template, making it possible to run cross searches, find similar neurons and compare image data on our 3D Viewer.

1 - How to cite us

Citation information for Virtual Fly Brain including APA, MLA, Chicago, and BibTeX formats. Use these citations when referencing VFB data, tools, or resources in your research publications.

How to Cite Virtual Fly Brain

If you use Virtual Fly Brain data, tools, or resources in your research, please cite our work using the citation formats below. Proper citation helps support continued development and funding of this resource.

Primary Citation

Use this citation when referencing Virtual Fly Brain in general, including use of the website, data, or tools:

APA

Court, R., Costa, M., Pilgrim, C., Millburn, G., Holmes, A., McLachlan, A., Larkin, A., Matentzoglu, N., Kir, H., Parkinson, H., Brown, N. H., O’Kane, C. J., Armstrong, J. D., Jefferis, G. S. X. E., & Osumi-Sutherland, D. (2023). Virtual Fly Brain—An interactive atlas of the Drosophila nervous system. Frontiers in Physiology, 14. https://doi.org/10.3389/fphys.2023.1076533

MLA

Court, Robert, et al. “Virtual Fly Brain—An Interactive Atlas of the Drosophila Nervous System.” Frontiers in Physiology, vol. 14, 2023, https://doi.org/10.3389/fphys.2023.1076533.

Chicago

Court, Robert, Costa, Marta, Pilgrim, Clare, Millburn, Gillian, Holmes, Alex, McLachlan, Alex, Larkin, Aoife et al. “Virtual Fly Brain—An interactive atlas of the Drosophila nervous system.” Frontiers in Physiology 14, (2023). https://doi.org/10.3389/fphys.2023.1076533.

BibTeX

@article{10.3389/fphys.2023.1076533,
  author = {Robert Court and Marta Costa and Clare Pilgrim and Gillian Millburn and Alex Holmes and Alex McLachlan and Aoife Larkin and Nicolas Matentzoglu and Huseyin Kir and Helen Parkinson and Nicolas H. Brown and Cahir J. O'Kane and J. Douglas Armstrong and Gregory S. X. E. Jefferis and David Osumi-Sutherland},
  title = "{Virtual Fly Brain—An interactive atlas of the Drosophila nervous system}",
  journal = {Frontiers in Physiology},
  volume = {14},
  publisher = {Frontiers Media {SA}},
  year = {2023},
  month = {jan},
  abstract = "{As a model organism, Drosophila is uniquely placed to contribute to our understanding of how brains control complex behavior. Not only does it have complex adaptive behaviors, but also a uniquely powerful genetic toolkit, increasingly complete dense connectomic maps of the central nervous system and a rapidly growing set of transcriptomic profiles of cell types. But this also poses a challenge: Given the massive amounts of available data, how are researchers to Find, Access, Integrate and Reuse (FAIR) relevant data in order to develop an integrated anatomical and molecular picture of circuits, inform hypothesis generation, and find reagents for experiments to test these hypotheses? The Virtual Fly Brain (virtualflybrain.org) web application & API provide a solution to this problem, using FAIR principles to integrate 3D images of neurons and brain regions, connectomics, transcriptomics and reagent expression data covering the whole CNS in both larva and adult. Users can search for neurons, neuroanatomy and reagents by name, location, or connectivity, via text search, clicking on 3D images, search-by-image, and queries by type (e.g., dopaminergic neuron) or properties (e.g., synaptic input in the antennal lobe). Returned results include cross-registered 3D images that can be explored in linked 2D and 3D browsers or downloaded under open licenses, and extensive descriptions of cell types and regions curated from the literature. These solutions are potentially extensible to cover similar atlasing and data integration challenges in vertebrates.}",
  issn = {1664-042X},
  doi = {https://doi.org/10.3389/fphys.2023.1076533},
  url = {https://doi.org/10.3389/fphys.2023.1076533},
}

Additional Citations

Drosophila Anatomy Ontology

If you specifically use or reference the Drosophila anatomy ontology developed as part of Virtual Fly Brain, please also cite:

Acknowledgements

When appropriate, please also acknowledge the specific data sources integrated into Virtual Fly Brain that you have used, such as JFRC, FlyBase, FlyCircuit, and datasets from individual research groups.

2 - Privacy Notice

Virtual Fly Brain Privacy Notice

Last updated: February 2026

The Virtual Fly Brain (VFB) project is committed to protecting your privacy and keeping you informed about how your personal information is used. This privacy notice explains how we collect, use, and protect your personal data when you visit our website.

What information do we collect?

We collect information about your visit to our website through Google Analytics, a web analytics service provided by Google, Inc. This includes:

  • Your IP address (anonymized)
  • Browser type and version
  • Operating system
  • Referring website
  • Pages visited and time spent on each page
  • Geographic location (country/city level only)

We do not collect any personally identifiable information such as names, email addresses, or contact details unless you voluntarily provide them (for example, through our contact forms or feedback mechanisms).

How do we use this information?

The information collected helps us:

  • Understand how our website is used
  • Improve the user experience and content
  • Identify technical issues
  • Analyze website traffic patterns
  • Support our research by understanding user interests in neuroanatomical data

Cookies and Website Privacy

We use Google Analytics cookies to collect this information. These are small text files stored on your device. You can control cookies through your browser settings, and you can opt out of Google Analytics tracking by visiting Google Analytics Opt-out.

For more information about Google’s privacy practices, please see Google’s Privacy Policy.

Our processing of your personal data is based on:

  • Legitimate interests: To improve our website and research services
  • Consent: Where you have provided it for specific purposes

Data Sharing and Disclosure

We do not sell, rent, or trade your personal information. Information collected by Google Analytics may be processed by Google on servers located in the United States. Google is committed to complying with the EU-U.S. Privacy Shield framework.

Data Retention

Analytics data is retained for up to 26 months, after which it is automatically deleted.

Your Rights

Under data protection law, you have rights including:

  • Access: Request a copy of your personal data
  • Rectification: Correct inaccurate data
  • Erasure: Request deletion of your data
  • Restriction: Limit how we process your data
  • Objection: Object to processing based on legitimate interests
  • Portability: Receive your data in a structured format

Contact Us

If you have questions about this privacy notice or wish to exercise your rights, please contact:

Data Protection Officer
University of Edinburgh
Old College
South Bridge
Edinburgh EH8 9YL
Email: dpo@ed.ac.uk

VFB Project Team
Email: data@virtualflybrain.org

Changes to this Privacy Notice

We may update this privacy notice from time to time. Any changes will be posted on this page with an updated revision date.

This privacy notice is supported by the University of Edinburgh’s wider privacy policies. For more information, visit the University Data Protection webpages.

3 - What is Virtual Fly Brain?

Virtual Fly Brain (VFB) - an interactive tool for neurobiologists to explore the detailed neuroanatomy, neuron connectivity, and gene expression of Drosophila melanogaster.

Welcome to Virtual Fly Brain (VFB) - an interactive tool for neurobiologists to explore the detailed neuroanatomy, neuron connectivity, and gene expression of Drosophila melanogaster. Our goal is to make it easier for researchers to find relevant anatomical information and reagents.

We integrate the neuroanatomical and expression data from the published literature, as well as image datasets onto the same brain template, making it possible to run cross searches, find similar neurons, and compare image data on our 3D Viewer.

4 - Virtual Fly Brain Members and Their Contributions

Meet the interdisciplinary team behind Virtual Fly Brain, including developers, curators, ontology experts, and researchers from leading UK institutions who collaborate to maintain and enhance this comprehensive Drosophila neuroscience resource.

Virtual Fly Brain Team

Virtual Fly Brain is developed and maintained by an interdisciplinary team of researchers, developers, and curators across multiple UK institutions. Our collaborative approach brings together expertise in informatics, neuroscience, ontology development, and data curation.

3D Viewer, Online Tools, Server, and Website

Institute for Adaptive and Neural Computation, School of Informatics, University of Edinburgh

Ontology Editing, FlyBase Support, and Data Annotation

Department of Genetics, University of Cambridge

  • Cahir O’Kane (Current Project PI)
  • Michael Ashburner (Original PI and Grant Holder)
  • Simon Reeve (2009-2011)
  • Nicole Staudt (2015-2016)
  • Alex Holmes (2017-2019)

Department of Physiology, Development and Neuroscience

Department of Zoology, University of Cambridge

MRC Laboratory of Molecular Biology, Cambridge

Schema Development & Web Development

Wellcome Sanger Institute, Cambridge

European Bioinformatics Institute (EMBL-EBI), Cambridge

Software Engineering, Geppetto Customisation, Graphics Design

MetaCell

MetaCell collaborates with Virtual Fly Brain on the development and enhancement of the open source Geppetto visualization platform that powers our 3D brain viewer.

For questions about team members or collaboration opportunities, please contact us.

5 - Funding

VirtualFlyBrain has been supported by grants from multiple UK research councils and charitable foundations since 2009.

Current Funding (2022-2027)

Wellcome Trust Grant 223741/Z/21/Z

  • Duration: April 1, 2022 to March 31, 2026 (extended to March 31, 2027)
  • Supporting ongoing VirtualFlyBrain development and maintenance

Historical Funding

Wellcome Trust

Grant 208379/Z/17/Z

  • Duration: October 1, 2017 to October 1, 2021

“Virtual Fly Brain: a global informatics hub for Drosophila neurobiology”

  • Grant 105023/D/14/Z: October 1, 2014 to January 31, 2018
  • Grant 105023/A/14/Z: October 1, 2014 to January 31, 2018
  • Grant 105023/C/14/Z: October 1, 2014 to September 30, 2017
  • Grant 105023/B/14/Z: October 1, 2014 to September 30, 2017

UK Research Councils

Biotechnology and Biological Sciences Research Council (BBSRC)

  • Grant BB/G02233X/1 (2009): “Standardising the representation of Drosophila anatomy and development for databases”
  • Recipients: J. Douglas Armstrong, Michael Ashburner, Cahir O’Kane, David Osumi-Sutherland

Engineering and Physical Sciences Research Council (EPSRC)

  • UK e-Science Theme Award supporting initial project establishment
  • Recipient: J. Douglas Armstrong

Medical Research Council (MRC)

  • Ongoing institutional support for technical infrastructure development

Other Sources

Isaac Newton Trust (University of Cambridge)

  • Grant supporting David Osumi-Sutherland’s database work (2007)
  • Grant supporting Marta Costa’s research: “Neuroinformatic identification of new types of neuron in the Drosophila brain” (October 2012 - September 2013)

Wellcome Trust - Cambridge Protein Trap Project

  • Supporting BrainTrap database development
  • Recipients: Kathryn Lilley, Steve Russell, Daniel St. Johnson

Institutional Partners

VirtualFlyBrain is a collaborative project between:

  • University of Edinburgh - School of Informatics
  • University of Cambridge - Multiple departments including Genetics, Physiology Development & Neuroscience, and Zoology
  • EMBL’s European Bioinformatics Institute (EMBL-EBI) - Hinxton, UK
  • Wellcome Sanger Institute - Hinxton, UK
  • MRC Laboratory for Molecular Biology - Cambridge

Data Partnerships

VirtualFlyBrain integrates data from multiple sources through collaborative partnerships rather than direct funding arrangements:

  • FlyBase Consortium
  • FlyCircuit Project (National Tsing Hua University, Taiwan)
  • Janelia Research Campus (HHMI, USA)
  • Multiple international research laboratories

Site Visualization Tools

VirtualFlyBrain utilizes multiple visualization technologies:

Geppetto Framework

  • Open source 3D visualization platform co-developed with MetaCell Corporation
  • VirtualFlyBrain and MetaCell collaborate on ongoing development and improvements to the Geppetto ecosystem

Woolz Image Processing and IIP3D Server

  • Developed by the MRC Human Genetics Unit, University of Edinburgh
  • Provides high-performance image serving and client-side visualization tools

6 - Collaborators

Collaborators

mrchguLogo.png

The IIP3D server, Woolz software and client-side tools are developed by* MRC Human Genetics Unit (MRC HGU): Richard Baldock, Nick Burton, Bill Hill, Zsolt Husz
(*) An on-going development of the client-side tools is done in collaboration between the MRC HGU and Edinburgh University

Visit the EMAGE gene expression database to see other tools the MRC HGU have developed.

flybase.gif

Expression data is collaboratively curated by VFB and FlyBase. Phenotype data is curated by FlyBase. Expression and phenotype data displayed on VFB is stored and maintained by FlyBase.

7 - Contributors

A list of contributors to the VirtualFlyBrain project

Contributors

We would like to thank the following contributors for their help with this project:

Robbie1977 dosumis mmc46 jefferis gidili nstaudt katrinleinweber waffle-iron ajdm Clare72 matentzn billhill00 fabiomcosta hhermsen RiZKiT jaywilliams oscherler fewtrem admclachlan ah963 hkir-dev tarelli ddelpiano jrmartin adrianq mlolson borismarin ddanny frenkield slarson dlion glebkuznetsov felipetavares mihairaulea jhurliman msasinski vraow domenic niteshthali08 pgleeson ruven tst-mjibaly abilascram stweil jcupitt jsavell massimobrero jrieke mschuene psj258 gitter-badger mattearnshaw actions-user NeZanyat afonsobspinto snyk-bot leechuck MiguelAngelRG cmungall kltm fbastian selewis smanzoor dougli1sqrd hdietze tudorgroza dhimmel DoctorBud jamesaoverton sirthias balhoff jrudolph jcranky stillalex maxcom p3t0r vmunier rmorey dependabot[bot] yyz1989 KrisDavie nneubarth trautmane robsv neomorphic tomdolafi barryclark eringrand javiercejudo peteretelej bkiers c17a Daniel15 daattali esteinborn vermluh henryaj hunjaelee italohdc fleeting junefrench praseodym omgmog rnicholus yzyzsun coltonfitzgerald dijonkitchen nscyclone sunnankar schlegelp SridharJagannathan nyvanga kha7iq hoeghh github-actions[bot] enicolasgomez vidhyalongani Salam-Dalloul Aiga115

8 - Publications

Publications

For more information on the technology behind the VFB website:

For details on the anatomy ontology:

9 - VFB citation bibtex

@article{Court_2023, 
    doi = {10.3389/fphys.2023.1076533}, 
    url = {https://doi.org/10.3389/fphys.2023.1076533}, 
    year = 2023, 
    month = {jan}, 
    publisher = {Frontiers Media {SA}}, 
    volume = {14}, 
    author = {Robert Court and Marta Costa and Clare Pilgrim and Gillian Millburn and Alex Holmes and Alex McLachlan and Aoife Larkin and Nicolas       Matentzoglu and Huseyin Kir and Helen Parkinson and Nicolas H. Brown and Cahir J. O'Kane and J. Douglas Armstrong and Gregory S. X. E. Jefferis and David Osumi-Sutherland}, 
    title = {Virtual Fly Brain{\textemdash}An interactive atlas of the Drosophila nervous system}, journal = {Frontiers in Physiology}}

10 - Contact us

Get in touch with the Virtual Fly Brain team for technical support, bug reports, data contributions, collaboration opportunities, or questions about using VFB software and data.

Contact Virtual Fly Brain

We welcome feedback, questions, and collaboration opportunities from the Drosophila research community. Please choose the most appropriate contact method for your inquiry below.

Technical Support & General Questions

For help with using Virtual Fly Brain, comments, suggestions, or general questions:

Public Support Forum: support@virtualflybrain.org

Note: This email goes to our public support forum, where questions and responses are visible to the community, helping other users with similar issues.

Before emailing: Please check our support forum archives to see if your question has already been answered.

Bug Reports & Feature Requests

To report technical issues, bugs, or request new features:

GitHub Issues: Report an issue

This allows our development team to track and address technical problems efficiently.

Data Contributions & Private Inquiries

For data inclusion discussions, collaboration proposals, or confidential matters that require direct communication with our team:

Private Email: data@virtualflybrain.org

Learn more about data contributions: Contribution Guidelines

Collaboration & Partnerships

Interested in collaborating with the Virtual Fly Brain team or discussing partnership opportunities?

Contact: data@virtualflybrain.org

Questions about Data Inclusion

For questions about adding your data:

Contact: data@virtualflybrain.org

Stay Connected

11 - Archived sites hosted by Virtual Fly Brain

By maintaining these archives, VFB ensures that valuable scientific resources remain accessible to researchers often after the original hosting sites become unavailable.

11.1 - ABD1.5 CATMAID Data Viewer

This CATMAID (Collaborative Annotation Toolkit for Massive Amounts of Image Data) instance hosts the neuroanatomical data from wild-type Drosophila larval abdominal segments, providing reference datasets for mechanosensory and motor circuit studies.

Access

The ABD1.5 CATMAID instance is hosted and maintained by Virtual Fly Brain (VFB) as part of their mission to integrate and preserve key Drosophila neuroscience datasets. The instance is accessible at: https://abd1.5.catmaid.virtualflybrain.org/

This resource provides wild-type reference data for the abdominal nerve cord of first instar Drosophila larvae, serving as a baseline for comparative connectomics studies. Virtual Fly Brain ensures its long-term availability to the research community.

Source Publications

This dataset contains neuron reconstructions from multiple foundational connectomics studies:

  1. Ohyama T, Schneider-Mizell CM, Fetter RD, Aleman JV, Franconville R, Rivera-Alba M, et al. (2015). A multilevel multimodal circuit enhances action selection in Drosophila. Nature, 520(7545), 633-639. https://doi.org/10.1038/nature14297

  2. Schneider-Mizell CM, Gerhard S, Longair M, Kazimiers T, Li F, Zwart MF, et al. (2016). Quantitative neuroanatomy for connectomics in Drosophila. eLife, 5, e12059. https://doi.org/10.7554/eLife.12059

  3. Valdes-Aleman J, Fetter RD, Sales EC, Heckman EL, Venkatasubramanian L, Doe CQ, et al. (2021). Comparative Connectomics Reveals How Partner Identity, Location, and Activity Specify Synaptic Connectivity in the Drosophila Motor System. Neuron, 109(1), 105-120.e7. https://doi.org/10.1016/j.neuron.2020.10.004

Dataset Contents

The viewer provides access to:

  • Serial section electron microscopy data of Drosophila 1st instar larval CNS (1.5-segment abdominal fraction, A2-A3 segments)
  • Image resolution: 3.8 nm x 3.8 nm x 40 nm (x, y, z)
  • Wild-type control neural tissue
  • Hundreds of manually traced and reconstructed neurons
  • Synaptic connectivity information
  • Associated metadata and annotations

Reconstructed Neuron Types

This dataset includes extensive reconstructions of:

Sensory neurons:

  • Mechanosensory chordotonal neurons (lch5 subtypes)
  • Nociceptive multidendritic neurons (ddaC, ddaD, ddaE, vdaB, v’ada)
  • Polymodal sensory neurons (v’ch, vchA/B, vchB/A)

Interneurons:

  • Basin (Bs) interneurons (excitatory modulation)
  • Proprioceptive and intersegmental interneurons
  • Premotor interneurons (extensive IS premotor reconstructions)
  • Motor circuit interneurons (Looper, Pseudolooper, Scepter, Bowl, Chair classes)

Motor neurons:

  • Identified motor neurons (aCC, RP2)
  • Putative motor neurons and muscle-innervating neurons

Other circuit elements:

  • Intersegmental connections
  • Spillover neurons (anterior and posterior processes)
  • Additional circuit fragments and auxiliary neurons

Technical Details

The EM volume was prepared and imaged following protocols detailed in Ohyama et al. (2015). Neurons were reconstructed using CATMAID to obtain skeletonized structures and connectivity information. All synaptic connections represent chemical synapses.

Key neuron types identifiable in this dataset include:

  • Mechanosensory chordotonal neurons (input sensory neurons)
  • Basin (Bs) interneurons (excitatory integration)
  • Drunken (Dr), Griddle (Gr), and Ladder (Ld) interneurons (inhibitory modulation)
  • Nociceptive multidendritic neurons (noxious stimulus detection)
  • Local and ascending interneurons

These neurons are uniquely identifiable based on:

  • Nerve entry point of the main neurite into the neuropil
  • Growth pattern of main axonal and dendritic branches
  • Bilateral vs ipsilateral projections
  • Position of terminal projections within the neuropil

Features

This CATMAID instance enables:

  • Browser-based visualization of serial section electron microscopy data
  • Navigation through image stacks
  • Viewing of neuron reconstructions
  • Analysis of synaptic connectivity
  • Data export functionality

Available Tools

Citation Guidelines

When using this data, please cite the relevant research:

  1. For mechanosensory and motor circuit data: Valdes-Aleman J, et al. (2021). Comparative Connectomics Reveals How Partner Identity, Location, and Activity Specify Synaptic Connectivity in the Drosophila Motor System. Neuron, 109(1), 105-120.e7. https://doi.org/10.1016/j.neuron.2020.10.004

  2. For foundational circuit architecture and quantitative neuroanatomy: Ohyama T, et al. (2015). A multilevel multimodal circuit enhances action selection in Drosophila. Nature, 520(7545), 633-639. https://doi.org/10.1038/nature14297

  3. For quantitative neuroanatomy methodology: Schneider-Mizell CM, et al. (2016). Quantitative neuroanatomy for connectomics in Drosophila. eLife, 5, e12059. https://doi.org/10.7554/eLife.12059

  4. The CATMAID platform: Saalfeld S, Cardona A, Hartenstein V, Tomančák P (2009) CATMAID: collaborative annotation toolkit for massive amounts of image data. Bioinformatics 25(15): 1984-1986. https://doi.org/10.1093/bioinformatics/btp266

Maintenance & Support

This resource is archived, hosted, and maintained by Virtual Fly Brain (VFB - https://virtualflybrain.org) as part of their commitment to preserving and making accessible critical Drosophila neuroscience data resources.

11.2 - BrainTrap

BrainTrap is a database of 3D protein expression patterns in the Drosophila brain, providing interactive visualization and exploration of confocal datasets showing reporter gene expression and protein localization.

https://braintrap.virtualflybrain.org/

Overview

BrainTrap was developed as part of a large-scale collaborative research project to collect protein expression location information from protein-trap lines generated by the Cambridge Protein Trap (CPT) project. The database provides detailed 3D confocal datasets showing protein expression patterns throughout the adult Drosophila brain.

Features

  • Interactive web-based viewer for exploring 3D confocal datasets
  • Full-size images throughout the brain volume can be viewed interactively
  • Secondary immunohistochemical label (anti-brp) aids navigation and helps identify brain structures
  • Searchable annotations linked to the FlyBase Drosophila anatomy ontology
  • Anatomical search criteria can be specified using:
    • Automatic term completion
    • Hierarchical browser for the ontology
  • Annotation provenance tracking with highlighted expression locations
  • Downloadable confocal dataset files in original format
  • XML format annotation data export
  • Gene comparison tables for selected genes

Original Publication

Knowles-Barley S, Longair M and Armstrong JD (2010). BrainTrap: a database of 3D protein expression patterns in the Drosophila brain. Database, Vol. 2010, Article ID baq005, doi:10.1093/database/baq005 (https://doi.org/10.1093/database/baq005)

Funding

Original development was funded by:

  • Engineering and Physical Sciences Research Council (EPSRC)
  • Medical Research Council
  • Biotechnology and Biological Sciences Research Council (BBSRC)
  • British Society for Developmental Biology
  • Society for Experimental Biology
  • Virtual Fly Brain e-Science Institute (ESI) Theme

The fly lines were generated by the Cambridge Protein Trap Project, supported by a Wellcome Trust grant to Kathryn Lilley, Steve Russell and Daniel St. Johnson.

Current Maintenance

This resource is currently archived and maintained by Virtual Fly Brain (VFB).

Current website: https://braintrap.virtualflybrain.org/

Source code repository: https://github.com/VirtualFlyBrain/BrainTrap

Original Development

School of Informatics
The University of Edinburgh
Edinburgh, EH8 9AB, UK

Citation

If you use BrainTrap in your research, please cite:

Knowles-Barley S, Longair M and Armstrong JD (2010). BrainTrap: a database of 3D protein expression patterns in the Drosophila brain. Database, Vol. 2010, Article ID baq005, doi:10.1093/database/baq005 (https://doi.org/10.1093/database/baq005)

11.3 - FAFB CATMAID Data Viewer

This CATMAID (Collaborative Annotation Toolkit for Massive Amounts of Image Data) instance hosts neuroanatomical data from the Full Adult Fly Brain (FAFB) electron microscopy dataset, featuring manually traced neurons from numerous research publications.

Neuron traced in Drosophila adult brain EM volume in early 2018

Access

The FAFB CATMAID instance is hosted and maintained by Virtual Fly Brain (VFB) as part of their mission to integrate and preserve key Drosophila neuroscience datasets. The instance is accessible at: https://fafb.catmaid.virtualflybrain.org/

This resource provides access to the FAFB dataset and its associated neural reconstructions. Virtual Fly Brain ensures its long-term availability to the research community.

Source Publications

Primary Resources

Contributing Publications

The database includes neurons traced and published in numerous studies. Each neuron is annotated with its source publication. Major contributing publications include:

Full references for specific neurons can be found on Virtual Fly Brain by searching for their skeleton ID (skid).

Dataset Contents

The viewer provides access to:

  • Complete electron microscopy volume of an adult Drosophila melanogaster brain
  • Manually traced neuron reconstructions from multiple research groups
  • Synaptic connectivity information
  • Associated metadata and annotations

Features

This CATMAID instance enables:

  • Browser-based visualization of the serial section electron microscopy data
  • Navigation through image stacks
  • Viewing of neuron reconstructions
  • Analysis of synaptic connectivity
  • Data export functionality

Available Tools

Citation Guidelines

When using this data, please cite:

  1. The FAFB EM dataset: Zheng Z, et al. (2018) A Complete Electron Microscopy Volume of the Brain of Adult Drosophila melanogaster. Cell, 174(3), 730-743.e22. https://doi.org/10.1016/j.cell.2018.06.019

  2. The CATMAID platform: Saalfeld S, Cardona A, Hartenstein V, Tomančák P (2009) CATMAID: collaborative annotation toolkit for massive amounts of image data. Bioinformatics 25(15): 1984-1986. https://doi.org/10.1093/bioinformatics/btp266

  3. The specific publication(s) associated with any neurons you analyze or reference (see Contributing Publications section)

Maintenance & Support

This resource is archived, hosted, and maintained by Virtual Fly Brain (VFB - https://virtualflybrain.org) as part of their commitment to preserving and making accessible critical Drosophila neuroscience data resources.

11.4 - FANC CATMAID Data Viewer

This CATMAID (Collaborative Annotation Toolkit for Massive Amounts of Image Data) instance hosts neuroanatomical data from the Female Adult Nerve Cord (FANC) electron microscopy dataset, available in both the original EM space and aligned to the JRC2018 VNC female template.

Figure showing FANC Motor and sensory neuron reconstructions

Access

The FANC CATMAID instance is hosted and maintained by Virtual Fly Brain (VFB) as part of their mission to integrate and preserve key Drosophila neuroscience datasets. The instance provides two views of the data:

  1. Original EM stack and tracings (Project ID 1): https://fanc.catmaid.virtualflybrain.org/

  2. Neurons aligned to JRC2018 VNC female template (Project ID 2): https://fanc.catmaid.virtualflybrain.org/

This resource provides access to both the original FANC dataset and template-aligned reconstructions. Virtual Fly Brain ensures its long-term availability to the research community.

Source Publication

The data is from the research published in:

Fushiki A, et al. (2021) A circuit mechanism for the propagation of waves of muscle contraction in Drosophila. Cell, 184(3), 759-774.e20. https://doi.org/10.1016/j.cell.2020.12.013

see: https://www.lee.hms.harvard.edu/resources

Dataset Contents

The viewer provides access to:

  • Complete electron microscopy volume of an adult female Drosophila ventral nerve cord
  • Manually traced neuron reconstructions in original EM space
  • Template-aligned neurons in JRC2018 VNC female template space
  • Synaptic connectivity information
  • Associated metadata and annotations

Features

This CATMAID instance enables:

  • Browser-based visualization of the serial section electron microscopy data
  • Navigation through image stacks
  • Viewing of neuron reconstructions in both original and template space
  • Analysis of synaptic connectivity
  • Data export functionality

Available Tools

Note: Both views (original and aligned) can be accessed through the same API using different project IDs (pid).

Citation Guidelines

When using this data, please cite:

  1. The FANC dataset: Fushiki A, et al. (2021) A circuit mechanism for the propagation of waves of muscle contraction in Drosophila. Cell, 184(3), 759-774.e20. https://doi.org/10.1016/j.cell.2020.12.013

  2. The CATMAID platform: Saalfeld S, Cardona A, Hartenstein V, Tomančák P (2009) CATMAID: collaborative annotation toolkit for massive amounts of image data. Bioinformatics 25(15): 1984-1986. https://doi.org/10.1093/bioinformatics/btp266

Maintenance & Support

This resource is archived, hosted, and maintained by Virtual Fly Brain (VFB - https://virtualflybrain.org) as part of their commitment to preserving and making accessible critical Drosophila neuroscience data resources. The aligned neurons are also available through the Virtual Fly Brain website.

11.5 - FLYBRAIN Neuron Database (NDB)

FLYBRAIN NDB is an extension to the Flybrain, an Online Atlas of the Drosophila Nervous System. It collected images and descriptions of single identified neurons in the Drosophila brain, providing morphological information of all fly brain neurons identified at the time.

https://flybrain-ndb.virtualflybrain.org/

Database Structure

FLYBRAIN NDB is a relational database searchable by two main criteria:

Search neurons by:

  • Name (full or partial)
  • Areas of arborizations
  • Distribution of pre- or postsynaptic sites (where known)
  • Keywords in documentation

Search molecular markers including:

  • Antibodies
  • Drosophila strains (e.g., GAL4 enhancer-trap lines)
  • Specific neural pathways

Data Categories

  • Visual Neurons
  • Olfactory Neurons
  • Auditory Neurons
  • Gustatory Neurons
  • Central Complex Neurons
  • Clonal Units
  • Brain Region Definitions
  • GAL4 and LexAV Strain Collections

Brain Explorer Features

The online brain browsing system allows users to:

  • Rotate volume-rendered images
  • Create sections
  • Adjust magnification
  • Browse confocal data

Terms of Use

Access

  • FLYBRAIN NDB is freely available
  • No login or registration required
  • All contents © 2008 FLYBRAIN NDB or their original publication
  • Copyright is noted in respective images

Usage Rights

  • Free use for non-profit, educational, and scientific purposes with proper citation
  • Republication or commercial use requires consent from the FLYBRAIN NDB manager

Citation Guidelines

Citing the Database

When citing the database as a whole, use: “Flybrain Neuron Database (https://flybrain-ndb.VirtualFlyBrain.org)”

Citing Specific Records

Format: [Neuron type], [Author(s)], ([Year]) Flybrain Neuron Database (https://flybrain-ndb.VirtualFlyBrain.org), acc. [number]

Example: “LC10 neuron, Otsuna, H., and Ito, K. (2007) Flybrain Neuron Database (https://flybrain-ndb.VirtualFlyBrain.org), acc. 10010”

Important Notes:

  • Include accession numbers when citing specific neurons
  • Cite original publications where applicable
  • Multiple contributors may exist for each record

Current Maintenance

This resource is currently archived and maintained by Virtual Fly Brain (VFB).

Source code repository: https://github.com/VirtualFlyBrain/flybrain-ndb

Original Development

© 2010 FLYBRAIN Neuron Database
Original Contact: Kazunori Shinomiya

11.6 - IAV-ROBO CATMAID Data Viewer

This CATMAID (Collaborative Annotation Toolkit for Massive Amounts of Image Data) instance hosts the neuroanatomical data from the IAV mechanosensory circuit study published in Valdes-Aleman et al. 2021.

Access

The IAV-ROBO CATMAID instance is hosted and maintained by Virtual Fly Brain (VFB) as part of their mission to integrate and preserve key Drosophila neuroscience datasets. The instance is accessible at: https://iav-robo.catmaid.virtualflybrain.org/

This resource provides a direct view into the dataset used to study the organization of proprioceptive circuits in Drosophila larvae. Virtual Fly Brain ensures its long-term availability to the research community.

Source Publication

This data is from the research published in:

Valdes-Aleman J, et al. (2021). Comparative Connectomics Reveals How Partner Identity, Location, and Activity Specify Synaptic Connectivity in the Drosophila Motor System. Neuron, 109(1), 105-120.e7. https://doi.org/10.1016/j.neuron.2020.10.004

Dataset Contents

The viewer provides access to:

  • Serial section electron microscopy data of Drosophila 1st instar larval CNS (1.5-segment fraction, A1/A2 segment)
  • Image resolution: 3.8 nm x 3.8 nm x 40 nm (x, y, z)
  • Genotype: w;; iav-GAL4/UAS-FraRobo
  • Manually traced neuron reconstructions showing shifted mechanosensory projections
  • Synaptic connectivity information
  • Associated metadata and annotations

Technical Details

The EM volume was prepared and imaged following protocols detailed in Ohyama et al. (2015). Neurons were reconstructed using CATMAID to obtain skeletonized structures and connectivity information. All synaptic connections represent chemical synapses.

Despite the FraRobo-induced lateral shift in terminal projections, neurons remain uniquely identifiable based on:

  • Nerve entry point of the main neurite into the neuropil
  • Growth pattern of main axonal and dendritic branches
  • Bilateral vs ipsilateral projections

For example, mechanosensory chordotonal neurons can be identified by their:

  • Eight stereotypic entry points per hemisegment
  • Most lateral position among sensory neurons in their nerve bundle
  • Further lateral shift due to FraRobo expression

Features

This CATMAID instance enables:

  • Browser-based visualization of the serial section electron microscopy data
  • Navigation through image stacks
  • Viewing of neuron reconstructions
  • Analysis of synaptic connectivity
  • Data export functionality

Available Tools

Citation Guidelines

When using this data, please cite both:

  1. The original research: Valdes-Aleman J, et al. (2021). Comparative Connectomics Reveals How Partner Identity, Location, and Activity Specify Synaptic Connectivity in the Drosophila Motor System. Neuron, 109(1), 105-120.e7. https://doi.org/10.1016/j.neuron.2020.10.004

  2. The CATMAID platform: Saalfeld S, Cardona A, Hartenstein V, Tomančák P (2009) CATMAID: collaborative annotation toolkit for massive amounts of image data. Bioinformatics 25(15): 1984-1986. https://doi.org/10.1093/bioinformatics/btp266

Maintenance & Support

This resource is archived, hosted, and maintained by Virtual Fly Brain (VFB - https://virtualflybrain.org) as part of their commitment to preserving and making accessible critical Drosophila neuroscience data resources.

11.7 - IAV-TNT CATMAID Data Viewer

This CATMAID (Collaborative Annotation Toolkit for Massive Amounts of Image Data) instance hosts the neuroanatomical data from the IAV mechanosensory circuit study published in Valdes-Aleman et al. 2021.

Access

The IAV-TNT CATMAID instance is hosted and maintained by Virtual Fly Brain (VFB) as part of their mission to integrate and preserve key Drosophila neuroscience datasets. The instance is accessible at: https://iav-tnt.catmaid.virtualflybrain.org/

This resource provides a direct view into the dataset used to study the organization of proprioceptive circuits in Drosophila larvae. Virtual Fly Brain ensures its long-term availability to the research community.

Source Publication

This data is from the research published in:

Valdes-Aleman J, et al. (2021). Comparative Connectomics Reveals How Partner Identity, Location, and Activity Specify Synaptic Connectivity in the Drosophila Motor System. Neuron, 109(1), 105-120.e7. https://doi.org/10.1016/j.neuron.2020.10.004

Dataset Contents

The viewer provides access to:

  • Serial section electron microscopy data of Drosophila 1st instar larval CNS (Control 1: whole-CNS volume, A1 segment)
  • Image resolution: 3.8 nm x 3.8 nm x 40 nm (x, y, z)
  • Manually traced neuron reconstructions
  • Synaptic connectivity information
  • Associated metadata and annotations

Technical Details

The EM volume was prepared and imaged following protocols detailed in Ohyama et al. (2015). Neurons were reconstructed using CATMAID to obtain skeletonized structures and connectivity information. All synaptic connections represent chemical synapses.

The neurons are uniquely identifiable based on key morphological features:

  • Nerve entry point of the main neurite into the neuropil
  • Growth pattern of main axonal and dendritic branches
  • Bilateral vs ipsilateral projections
  • Position of terminal projections within the medio-lateral, dorso-ventral and antero-posterior axes

Features

This CATMAID instance enables:

  • Browser-based visualization of the serial section electron microscopy data
  • Navigation through image stacks
  • Viewing of neuron reconstructions
  • Analysis of synaptic connectivity
  • Data export functionality

Available Tools

Citation Guidelines

When using this data, please cite both:

  1. The original research: Valdes-Aleman J, et al. (2021). Comparative Connectomics Reveals How Partner Identity, Location, and Activity Specify Synaptic Connectivity in the Drosophila Motor System. Neuron, 109(1), 105-120.e7. https://doi.org/10.1016/j.neuron.2020.10.004

  2. The CATMAID platform: Saalfeld S, Cardona A, Hartenstein V, Tomančák P (2009) CATMAID: collaborative annotation toolkit for massive amounts of image data. Bioinformatics 25(15): 1984-1986. https://doi.org/10.1093/bioinformatics/btp266

Maintenance & Support

This resource is archived, hosted, and maintained by Virtual Fly Brain (VFB - https://virtualflybrain.org) as part of their commitment to preserving and making accessible critical Drosophila neuroscience data resources.

11.8 - L1EM CATMAID Data Viewer

This CATMAID (Collaborative Annotation Toolkit for Massive Amounts of Image Data) instance hosts neuroanatomical data from the Drosophila first instar larva (L1) electron microscopy dataset, featuring manually traced neurons from numerous research publications.

Drosopila Larval CNS 70% traced back in 2017

Access

The L1EM CATMAID instance is hosted and maintained by Virtual Fly Brain (VFB) as part of their mission to integrate and preserve key Drosophila neuroscience datasets. The instance is accessible at: https://l1em.catmaid.virtualflybrain.org/

This resource provides access to the L1EM dataset and its associated neural reconstructions. Virtual Fly Brain ensures its long-term availability to the research community.

Source Publication

Primary Resource

Contributing Publications

The database includes neurons traced and published in numerous studies. Each neuron is annotated with its source publication. Major contributing publications include:

  • Andrade et al. (2019)
  • Barnes et al. (2022)
  • Berck, Khandelwal et al. (2016)
  • Burgos et al. (2018)
  • Carreira-Rosario, Arzan Zarin, Clark et al. (2018)
  • Eichler, Li, Litwin-Kumar et al. (2017)
  • Eschbach, Fushiki et al. (2020, 2020b)
  • Fushiki et al. (2016)
  • Gerhard et al. (2017)
  • Heckscher et al. (2015)
  • Hueckesfeld et al. (2020)
  • Imambocus et al.
  • Jovanic et al. (2019)
  • Jovanic, Schneider-Mizell et al. (2016)
  • Larderet, Fritsch et al. (2017)
  • Mark et al. (2019)
  • Miroschnikow et al. (2018)
  • Ohyama, Schneider-Mizell et al. (2015)
  • Schlegel et al. (2016)
  • Takagi et al. (2017)
  • Tastekin et al. (2018)
  • Valdes-Aleman et al. (2021)
  • Winding, Pedigo et al. (2023)
  • Zarin, Mark et al. (2019)
  • Zwart et al. (2016)

Full references for specific neurons can be found on Virtual Fly Brain by searching for their skeleton ID (skid).

Dataset Contents

The viewer provides access to:

  • Complete electron microscopy volume of a Drosophila first instar larva brain
  • Manually traced neuron reconstructions from multiple research groups
  • Synaptic connectivity information
  • Associated metadata and annotations

Features

This CATMAID instance enables:

  • Browser-based visualization of the serial section electron microscopy data
  • Navigation through image stacks
  • Viewing of neuron reconstructions
  • Analysis of synaptic connectivity
  • Data export functionality

Available Tools

Citation Guidelines

When using this data, please cite:

  1. The L1EM dataset: Winding M, et al. (2023) The connectome of an insect brain. Science, 379(6636):eadd9330. https://doi.org/10.1126/science.add9330

  2. The CATMAID platform: Saalfeld S, Cardona A, Hartenstein V, Tomančák P (2009) CATMAID: collaborative annotation toolkit for massive amounts of image data. Bioinformatics 25(15): 1984-1986. https://doi.org/10.1093/bioinformatics/btp266

  3. The specific publication(s) associated with any neurons you analyze or reference (see Contributing Publications section)

Maintenance & Support

This resource is archived, hosted, and maintained by Virtual Fly Brain (VFB - https://virtualflybrain.org) as part of their commitment to preserving and making accessible critical Drosophila neuroscience data resources.