Visualization and Quantification for Interactive Analysis of Neural Connectivity in Drosophila

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dc.contributor.authorSwoboda, N.en_US
dc.contributor.authorMoosburner, J.en_US
dc.contributor.authorBruckner, S.en_US
dc.contributor.authorYu, J. Y.en_US
dc.contributor.authorDickson, B. J.en_US
dc.contributor.authorBühler, K.en_US
dc.contributor.editorChen, Min and Zhang, Hao (Richard)en_US
dc.date.accessioned2017-03-13T18:13:02Z
dc.date.available2017-03-13T18:13:02Z
dc.date.issued2017
dc.description.abstractNeurobiologists investigate the brain of the common fruit fly to discover neural circuits and link them to complex behaviour. 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.Neurobiologists investigate the brain of the common fruit fly Drosophila melanogaster to discover neural circuits and link them to complex behaviour. 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.en_US
dc.description.number1
dc.description.sectionheadersArticles
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume36
dc.identifier.doi10.1111/cgf.12792
dc.identifier.issn1467-8659
dc.identifier.urihttps://doi.org/10.1111/cgf.12792
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf12792
dc.publisher© 2017 The Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectJ.3 [Computer Applications]: Life and Medical Sciences—Biology and genetics
dc.subjectI.3.7 [Computer Graphics]: Three‐Dimensional Graphics and Realism
dc.titleVisualization and Quantification for Interactive Analysis of Neural Connectivity in Drosophilaen_US
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