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Visual and Quantitative Analysis of Higher Order Arborization Overlaps for Neural Circuit Research

Nicolas Swoboda, Judith Moosburner, Stefan Bruckner, Jai Y. Yu, Barry J. Dickson, Katja Bühler

INPROCEEDINGS, Proceedings of the Eurographics Workshop on Visual Computing for Biology and Medicine, 2014

Abstract

Neuroscientists investigate neural circuits in the brain of the common fruit fly Drosophila melanogaster to discover how complex behavior is generated. Hypothesis building on potential connections between individual neurons is an essential step in the discovery of circuits that govern a specific behavior. Overlaps of arborizations of two or more neurons indicate a potential anatomical connection, i.e. the presence of joint synapses responsible for signal transmission between neurons. Obviously, the number of higher order overlaps (i.e. overlaps of three and more arborizations) increases exponentially with the number of neurons under investigation making it almost impossible to precompute quantitative information for all possible combinations. Thus, existing solutions are restricted to pairwise comparison of overlaps as they are relying on precomputed overlap quantification. Analyzing overlaps by visual inspection of more than two arborizations in 2D sections or in 3D is impeded by visual clutter or occlusion. This work contributes a novel tool that complements existing methods for potential connectivity exploration by providing for the first time the possibility to compute and visualize higher order arborization overlaps on the fly and to interactively explore this information in its spatial anatomical context and on a quantitative level. Qualitative evaluation with neuroscientists and non-expert users demonstrated the utility and usability of the tool.

Published

Proceedings of the Eurographics Workshop on Visual Computing for Biology and Medicine

  • Series: VCBM
  • Pages: 107–116

Media

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BibTeX

@inproceedings{Swoboda14Visual,
 author = {Nicolas Swoboda and Judith Moosburner and Stefan Bruckner and Jai
	Y. Yu and Barry J. Dickson and Katja B{\"u}hler},
 title  = {Visual and Quantitative Analysis of Higher Order Arborization Overlaps for Neural Circuit 
           Research},
 booktitle = {Proceedings of the Eurographics Workshop on Visual Computing for Biology and Medicine},
 series = {VCBM},
 year = {2014},
 pages = {107--116},
 abstract = {Neuroscientists investigate neural circuits in the brain of the common fruit fly 
  Drosophila melanogaster to discover how complex behavior is generated. Hypothesis building on 
  potential connections between individual neurons is an essential step in the discovery of circuits 
  that govern a specific behavior. Overlaps of arborizations of two or more neurons indicate a 
  potential anatomical connection, i.e. the presence of joint synapses responsible for signal 
  transmission between neurons. Obviously, the number of higher order overlaps (i.e. overlaps of 
  three and more arborizations) increases exponentially with the number of neurons under 
  investigation making it almost impossible to precompute quantitative information for all 
  possible combinations. Thus, existing solutions are restricted to pairwise comparison of overlaps 
  as they are relying on precomputed overlap quantification. Analyzing overlaps by visual inspection 
  of more than two arborizations in 2D sections or in 3D is impeded by visual clutter or occlusion. 
  This work contributes a novel tool that complements existing methods for potential connectivity 
  exploration by providing for the first time the possibility to compute and visualize higher order 
  arborization overlaps on the fly and to interactively explore this information in its spatial 
  anatomical context and on a quantitative level. Qualitative evaluation with neuroscientists and 
  non-expert users demonstrated the utility and usability of the tool.},



}






 Last Modified: Jean-Paul Balabanian, 2016-11-03