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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

CONFERENCE PAPER: In Proceedings of VCBM 2014, pp. 107–116, 2014. VCBM 2014 Best Paper Honorable Mention. DOI: 10.2312/vcbm.20141189

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 VCBM 2014

  • Pages: 107–116
  • Event: VCBM 2014
  • Location: Vienna, Austria
  • Date: September 2014
  • DOI: 10.2312/vcbm.20141189
  • Note: VCBM 2014 Best Paper Honorable Mention

Documents and Links

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BibTeX

@INPROCEEDINGS{Swoboda-2014-VQA,
  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 VCBM 2014},
  year = {2014},
  pages = {107--116},
  month = sep,
  note = {VCBM 2014 Best Paper Honorable Mention},
  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.},
  doi = {10.2312/vcbm.20141189},
  event = {VCBM 2014},
  keywords = {visual analysis, neurobiology},
  location = {Vienna, Austria},
}






 Last Modified: Stefan Bruckner, 2017-06-14