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Related Concept Videos

Brain Imaging01:14

Brain Imaging

Brain imaging technologies provide critical insights into both the structure and function of the human brain, enabling medical professionals and researchers to diagnose, study, and treat neurological disorders or psychiatric disorders more effectively.
These technologies include computerized axial tomography (CAT or CT scans), positron-emission tomography (PET scans),  magnetic resonance imaging (MRI),  functional magnetic resonance imaging (fMRI), and Transcranial Magnetic Stimulation (TMS).

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Related Experiment Video

Updated: Jun 25, 2026

A Pipeline for 3D Multimodality Image Integration and Computer-assisted Planning in Epilepsy Surgery
09:41

A Pipeline for 3D Multimodality Image Integration and Computer-assisted Planning in Epilepsy Surgery

Published on: May 20, 2016

Distributed XQuery-Based Integration and Visualization of Multimodality Brain Mapping Data.

Landon T Detwiler1, Dan Suciu, Joshua D Franklin

  • 1Department of Biological Structure, University of Washington Seattle, WA, USA.

Frontiers in Neuroinformatics
|February 10, 2009
PubMed
Summary
This summary is machine-generated.

This study introduces a lightweight distributed query architecture for small research teams to integrate heterogeneous brain data. The system, DXBrain, simplifies data sharing by enabling distributed XQuery execution and visualization, bridging the gap between ad hoc methods and large-scale efforts.

Keywords:
XQuerybrain mappingbrain visualizationdata integrationdistributed query processingneuroinformaticsquery shippingsemantic web

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Published on: March 21, 2019

Related Experiment Videos

Last Updated: Jun 25, 2026

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09:41

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Published on: May 20, 2016

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08:36

Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms

Published on: March 21, 2019

Area of Science:

  • Neuroscience
  • Computer Science
  • Data Science

Background:

  • Small research groups face challenges integrating distributed and heterogeneous brain data.
  • Existing large-scale data sharing initiatives are often too complex for individual investigators.
  • Ad hoc data sharing methods among collaborators are common but inefficient.

Purpose of the Study:

  • To develop a lightweight, distributed query architecture for integrating heterogeneous brain data.
  • To facilitate data sharing and analysis for small groups of collaborating neuroscientists.
  • To provide a user-friendly system for querying distributed brain data sources.

Main Methods:

  • Implemented a distributed query architecture using web services accessible via arbitrary query languages.
  • Developed a Distributed XQuery Processor (DXQP) to execute distributed XQueries and integrate XML results.
  • Created a web-based application, DXBrain, for users to create, execute, and visualize distributed XQueries.

Main Results:

  • Demonstrated the system's ability to integrate distributed brain mapping data sources.
  • Showcased the ease of adding and querying new data sources.
  • Presented results including a 3-D brain visualization.

Conclusions:

  • The developed system effectively bridges the gap between ad hoc data sharing and large-scale national efforts.
  • DXBrain offers a practical solution for small research teams needing to integrate diverse brain data.
  • The system requires users to understand XQuery and data source schemata, a manageable burden for knowledgeable users.