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Visualization and Quantification for Interactive Analysis of Neural Connectivity in Drosophila

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

JOURNAL ARTICLE: Computer Graphics Forum, vol. 36, no. 1, pp. 160–171, 2017. DOI: 10.1111/cgf.12792

Abstract

Neurobiologists investigate the brain of the common fruit fly Drosophila melanogaster to discover neural circuits and link them to complex behavior. Formulating new hypotheses about connectivity requires potential connectivity information between individual neurons, indicated by overlaps of arborizations of two or more neurons. As the number of higher order overlaps (i.e., overlaps of three or more arborizations) increases exponentially with the number of neurons under investigation, visualization is impeded by clutter and quantification becomes a burden. Existing solutions are restricted to visual or quantitative analysis of pairwise overlaps, as they rely on precomputed overlap data. We present 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 both its spatial anatomical context and on a quantitative level. Qualitative evaluation by neuroscientists and non-experts demonstrated the utility and usability of the tool

Published

Computer Graphics Forum

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BibTeX

@ARTICLE{Swoboda-2017-VQI,
  author = {Nicolas Swoboda and Judith Moosburner and Stefan Bruckner and Jai
	Y. Yu and Barry J. Dickson and Katja B{\"u}hler},
  title = {Visualization and Quantification for Interactive Analysis of Neural
	Connectivity in Drosophila},
  journal = {Computer Graphics Forum},
  year = {2017},
  volume = {36},
  pages = {160--171},
  number = {1},
  month = jan,
  abstract = {Neurobiologists investigate the brain of the common fruit fly Drosophila
	melanogaster to discover neural circuits and link them to complex
	behavior. Formulating new hypotheses about connectivity requires
	potential connectivity information between individual neurons, indicated
	by overlaps of arborizations of two or more neurons. As the number
	of higher order overlaps (i.e., overlaps of three or more arborizations)
	increases exponentially with the number of neurons under investigation,
	visualization is impeded by clutter and quantification becomes a
	burden. Existing solutions are restricted to visual or quantitative
	analysis of pairwise overlaps, as they rely on precomputed overlap
	data. We present 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 both its spatial anatomical context and on a quantitative level.
	Qualitative evaluation by neuroscientists and non-experts demonstrated
	the utility and usability of the tool},
  doi = {10.1111/cgf.12792},
  keywords = {visual analysis, neurobiology},
}






 Last Modified: Stefan Bruckner, 2017-10-13