Visual Queries in Neuronal Data Exploration

Information

• Publication Type: Master Thesis
• Workgroup(s)/Project(s):
  • Visualization Group
• Date: June 2010
• TU Wien Library:
• Diploma Examination: 2009
• First Supervisor:
  • Eduard Gröller
  • Stefan Bruckner

Abstract

The major goal of neuroscientists’ work is to explain specific behavior of living beings, especially humans. However, human behavioral traits are complex and difficult to comprehend. For this purpose, the researchers explore the anatomy and morphology of neuronal circuits of simpler species to identify their meaning and functionality. The fruit fly Drosophila melanogaster is a favorite organism in neurobiology research because it facilitates studies of complex systems on a simple model. For this purpose, large databases of neuronal structures acquired by microscopy scans were built and adapted for computer-aided exploration and visualization. Commodity products feature standard visualization techniques tailored for exploration of biological structures. However, orientation in large collections of structures still poses a problem. Traditional table-view database interfaces allow filtering of items and accessing known subsets of data, but do not support selection based on spatial relationships. In this thesis, we address this problem in the following way. We describe a system which facilitates visual exploration of a large collection of neuroanatomical structures. We combined standard visualization techniques with a novel visual approach for exploration and queries. Our system provides three basic types of queries. Path queries use an intuitive sketching interface and give access to structures located in the proximity of the sketched path. Object queries select objects based on their mutual spatial distance. Semantic queries allow fast browsing using semantic relationships stored in the database. The system was designed in an interdisciplinary collaboration with domain experts, who affirmed that availability of such a system would be very useful for their research.

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BibTeX

@mastersthesis{Solteszova-2009-VQN,
  title =      "Visual Queries in Neuronal Data Exploration",
  author =     "Veronika Solteszova",
  year =       "2010",
  abstract =   "The major goal of neuroscientists’ work is to explain
               specific behavior of living beings, especially humans.
               However, human behavioral traits are complex and difficult
               to comprehend. For this purpose, the researchers explore the
               anatomy and morphology of neuronal circuits of simpler
               species to identify their meaning and functionality. The
               fruit fly Drosophila melanogaster is a favorite organism in
               neurobiology research because it facilitates studies of
               complex systems on a simple model. For this purpose, large
               databases of neuronal structures acquired by microscopy
               scans were built and adapted for computer-aided exploration
               and visualization. Commodity products feature standard
               visualization techniques tailored for exploration of
               biological structures. However, orientation in large
               collections of structures still poses a problem. Traditional
               table-view database interfaces allow filtering of items and
               accessing known subsets of data, but do not support
               selection based on spatial relationships. In this thesis, we
               address this problem in the following way. We describe a
               system which facilitates visual exploration of a large
               collection of neuroanatomical structures. We combined
               standard visualization techniques with a novel visual
               approach for exploration and queries. Our system provides
               three basic types of queries. Path queries use an intuitive
               sketching interface and give access to structures located in
               the proximity of the sketched path. Object queries select
               objects based on their mutual spatial distance. Semantic
               queries allow fast browsing using semantic relationships
               stored in the database. The system was designed in an
               interdisciplinary collaboration with domain experts, who
               affirmed that availability of such a system would be very
               useful for their research.",
  month =      jun,
  address =    "Favoritenstrasse 9-11/E193-02, A-1040 Vienna, Austria",
  school =     "Institute of Computer Graphics and Algorithms, Vienna
               University of Technology ",
  URL =        "https://www.cg.tuwien.ac.at/research/publications/2010/Solteszova-2009-VQN/",
}