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

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.

, booktitle = {
Eurographics Workshop on Visual Computing for Biology and Medicine
}, editor = {
Ivan Viola and Katja Buehler and Timo Ropinski
}, title = {{
Visual and Quantitative Analysis of Higher Order Arborization Overlaps for Neural Circuit Research
}}, author = {
Swoboda, Nicolas
Moosburner, Judith
Bruckner, Stefan
Yu, Jai Y.
Dickson, Barry J.
Bühler, Katja
}, year = {
}, publisher = {
The Eurographics Association
}, ISSN = {
}, ISBN = {
}, DOI = {
} }